The cudd package
The University of Colorado decision diagram package.
Fabio Somenzi
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Cudd_AddHook() Adds a function to a hook.
Cudd_ApaAdd() Adds two arbitrary precision integers.
Cudd_ApaCompareRatios() Compares the ratios of two arbitrary precision
integers to two unsigned ints.
Cudd_ApaCompare() Compares two arbitrary precision integers.
Cudd_ApaCopy() Makes a copy of an arbitrary precision integer.
Cudd_ApaCountMinterm() Counts the number of minterms of a DD.
Cudd_ApaIntDivision() Divides an arbitrary precision integer by an
integer.
Cudd_ApaNumberOfDigits() Finds the number of digits for an arbitrary
precision integer.
Cudd_ApaPowerOfTwo() Sets an arbitrary precision integer to a power
of two.
Cudd_ApaPrintDecimal() Prints an arbitrary precision integer in
decimal format.
Cudd_ApaPrintDensity() Prints the density of a BDD or ADD using
arbitrary precision arithmetic.
Cudd_ApaPrintExponential() Prints an arbitrary precision integer in
exponential format.
Cudd_ApaPrintHex() Prints an arbitrary precision integer in
hexadecimal format.
Cudd_ApaPrintMintermExp() Prints the number of minterms of a BDD or ADD
in exponential format using arbitrary precision
arithmetic.
Cudd_ApaPrintMinterm() Prints the number of minterms of a BDD or ADD
using arbitrary precision arithmetic.
Cudd_ApaSetToLiteral() Sets an arbitrary precision integer to a one-
digit literal.
Cudd_ApaShiftRight() Shifts right an arbitrary precision integer by
one binary place.
Cudd_ApaShortDivision() Divides an arbitrary precision integer by a
digit.
Cudd_ApaSubtract() Subtracts two arbitrary precision integers.
Cudd_AutodynDisableZdd() Disables automatic dynamic reordering of ZDDs.
Cudd_AutodynDisable() Disables automatic dynamic reordering.
Cudd_AutodynEnableZdd() Enables automatic dynamic reordering of ZDDs.
Cudd_AutodynEnable() Enables automatic dynamic reordering of BDDs
and ADDs.
Cudd_AverageDistance() Computes the average distance between adjacent
nodes.
Cudd_BddToAdd() Converts a BDD to a 0-1 ADD.
Cudd_BddToCubeArray() Builds a positional array from the BDD of a
cube.
Cudd_BiasedOverApprox() Extracts a dense superset from a BDD with the
biased underapproximation method.
Cudd_BiasedUnderApprox() Extracts a dense subset from a BDD with the
biased underapproximation method.
Cudd_CProjection() Computes the compatible projection of R w.r.t.
cube Y.
Cudd_CheckKeys() Checks for several conditions that should not
occur.
Cudd_CheckZeroRef() Checks the unique table for nodes with non-zero
reference counts.
Cudd_ClassifySupport() Classifies the variables in the support of two
DDs.
Cudd_ClearErrorCode() Clear the error code of a manager.
Cudd_CofMinterm() Computes the fraction of minterms in the on-set
of all the positive cofactors of a BDD or ADD.
Cudd_Cofactor() Computes the cofactor of f with respect to g.
Cudd_Complement() Returns the complemented version of a pointer.
Cudd_CountLeaves() Counts the number of leaves in a DD.
Cudd_CountMinterm() Counts the number of minterms of a DD.
Cudd_CountPathsToNonZero() Counts the number of paths to a non-zero
terminal of a DD.
Cudd_CountPath() Counts the number of paths of a DD.
Cudd_CubeArrayToBdd() Builds the BDD of a cube from a positional
array.
Cudd_DagSize() Counts the number of nodes in a DD.
Cudd_DeadAreCounted() Tells whether dead nodes are counted towards
triggering reordering.
Cudd_DebugCheck() Checks for inconsistencies in the DD heap.
Cudd_Decreasing() Determines whether a BDD is negative unate in a
variable.
Cudd_DelayedDerefBdd() Decreases the reference count of BDD node n.
Cudd_Density() Computes the density of a BDD or ADD.
Cudd_Deref() Decreases the reference count of node.
Cudd_DisableGarbageCollection()
Disables garbage collection.
Cudd_DisableReorderingReporting()
Disables reporting of reordering stats.
Cudd_DumpBlifBody() Writes a blif body representing the argument
BDDs.
Cudd_DumpBlif() Writes a blif file representing the argument
BDDs.
Cudd_DumpDDcal() Writes a DDcal file representing the argument
BDDs.
Cudd_DumpDaVinci() Writes a daVinci file representing the argument
BDDs.
Cudd_DumpDot() Writes a dot file representing the argument
DDs.
Cudd_DumpFactoredForm() Writes factored forms representing the argument
BDDs.
Cudd_Dxygtdxz() Generates a BDD for the function d(x,y) >
d(x,z).
Cudd_Dxygtdyz() Generates a BDD for the function d(x,y) >
d(y,z).
Cudd_EnableGarbageCollection() Enables garbage collection.
Cudd_EnableReorderingReporting()
Enables reporting of reordering stats.
Cudd_EpdCountMinterm() Counts the number of minterms of a DD with
extended precision.
Cudd_EqualSupNorm() Compares two ADDs for equality within
tolerance.
Cudd_EquivDC() Tells whether F and G are identical wherever D
is 0.
Cudd_EstimateCofactorSimple() Estimates the number of nodes in a cofactor of
a DD.
Cudd_EstimateCofactor() Estimates the number of nodes in a cofactor of
a DD.
Cudd_Eval() Returns the value of a DD for a given variable
assignment.
Cudd_ExpectedUsedSlots() Computes the expected fraction of used slots in
the unique table.
Cudd_E() Returns the else child of an internal node.
Cudd_FindEssential() Finds the essential variables of a DD.
Cudd_FindTwoLiteralClauses() Finds the two literal clauses of a DD.
Cudd_FirstCube() Finds the first cube of a decision diagram.
Cudd_FirstNode() Finds the first node of a decision diagram.
Cudd_FirstPrime() Finds the first prime of a Boolean function.
Cudd_ForeachCube() Iterates over the cubes of a decision diagram.
Cudd_ForeachNode() Iterates over the nodes of a decision diagram.
Cudd_ForeachPrime() Iterates over the primes of a Boolean function.
Cudd_FreeTree() Frees the variable group tree of the manager.
Cudd_FreeZddTree() Frees the variable group tree of the manager.
Cudd_GarbageCollectionEnabled()
Tells whether garbage collection is enabled.
Cudd_GenFree() Frees a CUDD generator.
Cudd_Increasing() Determines whether a BDD is positive unate in a
variable.
Cudd_IndicesToCube() Builds a cube of BDD variables from an array of
indices.
Cudd_Init() Creates a new DD manager.
Cudd_IsComplement() Returns 1 if a pointer is complemented.
Cudd_IsConstant() Returns 1 if the node is a constant node.
Cudd_IsGenEmpty() Queries the status of a generator.
Cudd_IsInHook() Checks whether a function is in a hook.
Cudd_IsNonConstant() Returns 1 if a DD node is not constant.
Cudd_IterDerefBdd() Decreases the reference count of BDD node n.
Cudd_LargestCube() Finds a largest cube in a DD.
Cudd_MakeBddFromZddCover() Converts a ZDD cover to a BDD graph.
Cudd_MakeTreeNode() Creates a new variable group.
Cudd_MakeZddTreeNode() Creates a new ZDD variable group.
Cudd_MinHammingDist() Returns the minimum Hamming distance between f
and minterm.
Cudd_NewApaNumber() Allocates memory for an arbitrary precision
integer.
Cudd_NextCube() Generates the next cube of a decision diagram
onset.
Cudd_NextNode() Finds the next node of a decision diagram.
Cudd_NextPrime() Generates the next prime of a Boolean function.
Cudd_NodeReadIndex() Returns the index of the node.
Cudd_NotCond() Complements a DD if a condition is true.
Cudd_Not() Complements a DD.
Cudd_OutOfMem() Warns that a memory allocation failed.
Cudd_OverApprox() Extracts a dense superset from a BDD with
Shiple's underapproximation method.
Cudd_Prime() Returns the next prime >= p.
Cudd_PrintDebug() Prints to the standard output a DD and its
statistics.
Cudd_PrintInfo() Prints out statistics and settings for a CUDD
manager.
Cudd_PrintLinear() Prints the linear transform matrix.
Cudd_PrintMinterm() Prints a disjoint sum of products.
Cudd_PrintTwoLiteralClauses() Prints the two literal clauses of a DD.
Cudd_PrintVersion() Prints the package version number.
Cudd_PrioritySelect() Selects pairs from R using a priority function.
Cudd_Quit() Deletes resources associated with a DD manager.
Cudd_Random() Portable random number generator.
Cudd_ReadArcviolation() Returns the current value of the arcviolation
parameter used in group sifting.
Cudd_ReadBackground() Reads the background constant of the manager.
Cudd_ReadCacheHits() Returns the number of cache hits.
Cudd_ReadCacheLookUps() Returns the number of cache look-ups.
Cudd_ReadCacheSlots() Reads the number of slots in the cache.
Cudd_ReadCacheUsedSlots() Reads the fraction of used slots in the cache.
Cudd_ReadDead() Returns the number of dead nodes in the unique
table.
Cudd_ReadEpsilon() Reads the epsilon parameter of the manager.
Cudd_ReadErrorCode() Returns the code of the last error.
Cudd_ReadGarbageCollectionTime()
Returns the time spent in garbage collection.
Cudd_ReadGarbageCollections() Returns the number of times garbage collection
has occurred.
Cudd_ReadGroupcheck() Reads the groupcheck parameter of the manager.
Cudd_ReadIndex() Returns the current position in the order of
variable index.
Cudd_ReadInvPermZdd() Returns the index of the ZDD variable currently
in the i-th position of the order.
Cudd_ReadInvPerm() Returns the index of the variable currently in
the i-th position of the order.
Cudd_ReadIthClause() Accesses the i-th clause of a DD.
Cudd_ReadKeys() Returns the number of nodes in the unique
table.
Cudd_ReadLinear() Reads an entry of the linear transform matrix.
Cudd_ReadLogicZero() Returns the logic zero constant of the manager.
Cudd_ReadLooseUpTo() Reads the looseUpTo parameter of the manager.
Cudd_ReadMaxCacheHard() Reads the maxCacheHard parameter of the
manager.
Cudd_ReadMaxCache() Returns the soft limit for the cache size.
Cudd_ReadMaxGrowthAlternate() Reads the maxGrowthAlt parameter of the
manager.
Cudd_ReadMaxGrowth() Reads the maxGrowth parameter of the manager.
Cudd_ReadMaxLive() Reads the maximum allowed number of live nodes.
Cudd_ReadMaxMemory() Reads the maximum allowed memory.
Cudd_ReadMemoryInUse() Returns the memory in use by the manager
measured in bytes.
Cudd_ReadMinDead() Reads the minDead parameter of the manager.
Cudd_ReadMinHit() Reads the hit rate that causes resizinig of the
computed table.
Cudd_ReadMinusInfinity() Reads the minus-infinity constant from the
manager.
Cudd_ReadNextReordering() Returns the threshold for the next dynamic
reordering.
Cudd_ReadNodeCount() Reports the number of nodes in BDDs and ADDs.
Cudd_ReadNodesDropped() Returns the number of nodes dropped.
Cudd_ReadNodesFreed() Returns the number of nodes freed.
Cudd_ReadNumberXovers() Reads the current number of crossovers used by
the genetic algorithm for reordering.
Cudd_ReadOne() Returns the one constant of the manager.
Cudd_ReadPeakLiveNodeCount() Reports the peak number of live nodes.
Cudd_ReadPeakNodeCount() Reports the peak number of nodes.
Cudd_ReadPermZdd() Returns the current position of the i-th ZDD
variable in the order.
Cudd_ReadPerm() Returns the current position of the i-th
variable in the order.
Cudd_ReadPlusInfinity() Reads the plus-infinity constant from the
manager.
Cudd_ReadPopulationSize() Reads the current size of the population used
by the genetic algorithm for reordering.
Cudd_ReadRecomb() Returns the current value of the recombination
parameter used in group sifting.
Cudd_ReadRecursiveCalls() Returns the number of recursive calls.
Cudd_ReadReorderingCycle() Reads the reordCycle parameter of the manager.
Cudd_ReadReorderingTime() Returns the time spent in reordering.
Cudd_ReadReorderings() Returns the number of times reordering has
occurred.
Cudd_ReadSiftMaxSwap() Reads the siftMaxSwap parameter of the manager.
Cudd_ReadSiftMaxVar() Reads the siftMaxVar parameter of the manager.
Cudd_ReadSize() Returns the number of BDD variables in
existance.
Cudd_ReadSlots() Returns the total number of slots of the unique
table.
Cudd_ReadStderr() Reads the stderr of a manager.
Cudd_ReadStdout() Reads the stdout of a manager.
Cudd_ReadSwapSteps() Reads the number of elementary reordering
steps.
Cudd_ReadSymmviolation() Returns the current value of the symmviolation
parameter used in group sifting.
Cudd_ReadTree() Returns the variable group tree of the manager.
Cudd_ReadUniqueLinks() Returns the number of links followed in the
unique table.
Cudd_ReadUniqueLookUps() Returns the number of look-ups in the unique
table.
Cudd_ReadUsedSlots() Reads the fraction of used slots in the unique
table.
Cudd_ReadVars() Returns the i-th element of the vars array.
Cudd_ReadZddOne() Returns the ZDD for the constant 1 function.
Cudd_ReadZddSize() Returns the number of ZDD variables in
existance.
Cudd_ReadZddTree() Returns the variable group tree of the manager.
Cudd_ReadZero() Returns the zero constant of the manager.
Cudd_RecursiveDerefZdd() Decreases the reference count of ZDD node n.
Cudd_RecursiveDeref() Decreases the reference count of node n.
Cudd_ReduceHeap() Main dynamic reordering routine.
Cudd_Ref() Increases the reference count of a node, if it
is not saturated.
Cudd_Regular() Returns the regular version of a pointer.
Cudd_RemapOverApprox() Extracts a dense superset from a BDD with the
remapping underapproximation method.
Cudd_RemapUnderApprox() Extracts a dense subset from a BDD with the
remapping underapproximation method.
Cudd_RemoveHook() Removes a function from a hook.
Cudd_ReorderingReporting() Returns 1 if reporting of reordering stats is
enabled.
Cudd_ReorderingStatusZdd() Reports the status of automatic dynamic
reordering of ZDDs.
Cudd_ReorderingStatus() Reports the status of automatic dynamic
reordering of BDDs and ADDs.
Cudd_SetArcviolation() Sets the value of the arcviolation parameter
used in group sifting.
Cudd_SetBackground() Sets the background constant of the manager.
Cudd_SetEpsilon() Sets the epsilon parameter of the manager to
ep.
Cudd_SetGroupcheck() Sets the parameter groupcheck of the manager to
gc.
Cudd_SetLooseUpTo() Sets the looseUpTo parameter of the manager.
Cudd_SetMaxCacheHard() Sets the maxCacheHard parameter of the manager.
Cudd_SetMaxGrowthAlternate() Sets the maxGrowthAlt parameter of the manager.
Cudd_SetMaxGrowth() Sets the maxGrowth parameter of the manager.
Cudd_SetMaxLive() Sets the maximum allowed number of live nodes.
Cudd_SetMaxMemory() Sets the maximum allowed memory.
Cudd_SetMinHit() Sets the hit rate that causes resizinig of the
computed table.
Cudd_SetNextReordering() Sets the threshold for the next dynamic
reordering.
Cudd_SetNumberXovers() Sets the number of crossovers used by the
genetic algorithm for reordering.
Cudd_SetPopulationSize() Sets the size of the population used by the
genetic algorithm for reordering.
Cudd_SetRecomb() Sets the value of the recombination parameter
used in group sifting.
Cudd_SetReorderingCycle() Sets the reordCycle parameter of the manager.
Cudd_SetSiftMaxSwap() Sets the siftMaxSwap parameter of the manager.
Cudd_SetSiftMaxVar() Sets the siftMaxVar parameter of the manager.
Cudd_SetStderr() Sets the stderr of a manager.
Cudd_SetStdout() Sets the stdout of a manager.
Cudd_SetSymmviolation() Sets the value of the symmviolation parameter
used in group sifting.
Cudd_SetTree() Sets the variable group tree of the manager.
Cudd_SetVarMap() Registers a variable mapping with the manager.
Cudd_SetZddTree() Sets the ZDD variable group tree of the
manager.
Cudd_SharingSize() Counts the number of nodes in an array of DDs.
Cudd_ShortestLength() Find the length of the shortest path(s) in a
DD.
Cudd_ShortestPath() Finds a shortest path in a DD.
Cudd_ShuffleHeap() Reorders variables according to given
permutation.
Cudd_SolveEqn() Implements the solution of F(x,y) = 0.
Cudd_SplitSet() Returns m minterms from a BDD.
Cudd_Srandom() Initializer for the portable random number
generator.
Cudd_StdPostReordHook() Sample hook function to call after reordering.
Cudd_StdPreReordHook() Sample hook function to call before reordering.
Cudd_SubsetCompress() Find a dense subset of BDD f.
Cudd_SubsetHeavyBranch() Extracts a dense subset from a BDD with the
heavy branch heuristic.
Cudd_SubsetShortPaths() Extracts a dense subset from a BDD with the
shortest paths heuristic.
Cudd_SubsetWithMaskVars() Extracts a subset from a BDD.
Cudd_SupersetCompress() Find a dense superset of BDD f.
Cudd_SupersetHeavyBranch() Extracts a dense superset from a BDD with the
heavy branch heuristic.
Cudd_SupersetShortPaths() Extracts a dense superset from a BDD with the
shortest paths heuristic.
Cudd_SupportIndex() Finds the variables on which a DD depends.
Cudd_SupportSize() Counts the variables on which a DD depends.
Cudd_Support() Finds the variables on which a DD depends.
Cudd_SymmProfile() Prints statistics on symmetric variables.
Cudd_TurnOffCountDead() Causes the dead nodes not to be counted towards
triggering reordering.
Cudd_TurnOnCountDead() Causes the dead nodes to be counted towards
triggering reordering.
Cudd_T() Returns the then child of an internal node.
Cudd_UnderApprox() Extracts a dense subset from a BDD with
Shiple's underapproximation method.
Cudd_VectorSupportIndex() Finds the variables on which a set of DDs
depends.
Cudd_VectorSupportSize() Counts the variables on which a set of DDs
depends.
Cudd_VectorSupport() Finds the variables on which a set of DDs
depends.
Cudd_VerifySol() Checks the solution of F(x,y) = 0.
Cudd_V() Returns the value of a constant node.
Cudd_Xeqy() Generates a BDD for the function x==y.
Cudd_Xgty() Generates a BDD for the function x > y.
Cudd_addAgreement() f if f==g; background if f!=g.
Cudd_addApply() Applies op to the corresponding discriminants
of f and g.
Cudd_addBddInterval() Converts an ADD to a BDD.
Cudd_addBddIthBit() Converts an ADD to a BDD by extracting the i-th
bit from the leaves.
Cudd_addBddPattern() Converts an ADD to a BDD.
Cudd_addBddStrictThreshold() Converts an ADD to a BDD.
Cudd_addBddThreshold() Converts an ADD to a BDD.
Cudd_addCmpl() Computes the complement of an ADD a la C
language.
Cudd_addCompose() Substitutes g for x_v in the ADD for f.
Cudd_addComputeCube() Computes the cube of an array of ADD variables.
Cudd_addConstrain() Computes f constrain c for ADDs.
Cudd_addConst() Returns the ADD for constant c.
Cudd_addDiff() Returns plusinfinity if f=g; returns min(f,g)
if f!=g.
Cudd_addDivide() Integer and floating point division.
Cudd_addEvalConst() Checks whether ADD g is constant whenever ADD f
is 1.
Cudd_addExistAbstract() Existentially Abstracts all the variables in
cube from f.
Cudd_addFindMax() Finds the maximum discriminant of f.
Cudd_addFindMin() Finds the minimum discriminant of f.
Cudd_addGeneralVectorCompose() Composes an ADD with a vector of ADDs.
Cudd_addHamming() Computes the Hamming distance ADD.
Cudd_addHarwell() Reads in a matrix in the format of the Harwell-
Boeing benchmark suite.
Cudd_addIteConstant() Implements ITEconstant for ADDs.
Cudd_addIte() Implements ITE(f,g,h).
Cudd_addIthBit() Extracts the i-th bit from an ADD.
Cudd_addIthVar() Returns the ADD variable with index i.
Cudd_addLeq() Determines whether f is less than or equal to
g.
Cudd_addLog() Natural logarithm of an ADD.
Cudd_addMatrixMultiply() Calculates the product of two matrices
represented as ADDs.
Cudd_addMaximum() Integer and floating point max.
Cudd_addMinimum() Integer and floating point min.
Cudd_addMinus() Integer and floating point subtraction.
Cudd_addMonadicApply() Applies op to the discriminants of f.
Cudd_addNand() NAND of two 0-1 ADDs.
Cudd_addNegate() Computes the additive inverse of an ADD.
Cudd_addNewVarAtLevel() Returns a new ADD variable at a specified
level.
Cudd_addNewVar() Returns a new ADD variable.
Cudd_addNonSimCompose() Composes an ADD with a vector of 0-1 ADDs.
Cudd_addNor() NOR of two 0-1 ADDs.
Cudd_addOneZeroMaximum() Returns 1 if f > g and 0 otherwise.
Cudd_addOrAbstract() Disjunctively abstracts all the variables in
cube from the 0-1 ADD f.
Cudd_addOr() Disjunction of two 0-1 ADDs.
Cudd_addOuterSum() Takes the minimum of a matrix and the outer sum
of two vectors.
Cudd_addPermute() Permutes the variables of an ADD.
Cudd_addPlus() Integer and floating point addition.
Cudd_addRead() Reads in a sparse matrix.
Cudd_addResidue() Builds an ADD for the residue modulo m of an n-
bit number.
Cudd_addRestrict() ADD restrict according to Coudert and Madre's
algorithm (ICCAD90).
Cudd_addRoundOff() Rounds off the discriminants of an ADD.
Cudd_addScalarInverse() Computes the scalar inverse of an ADD.
Cudd_addSetNZ() This operator sets f to the value of g wherever
g != 0.
Cudd_addSwapVariables() Swaps two sets of variables of the same size (x
and y) in the ADD f.
Cudd_addThreshold() f if f>=g; 0 if f<g.
Cudd_addTimesPlus() Calculates the product of two matrices
represented as ADDs.
Cudd_addTimes() Integer and floating point multiplication.
Cudd_addTriangle() Performs the triangulation step for the
shortest path computation.
Cudd_addUnivAbstract() Universally Abstracts all the variables in cube
from f.
Cudd_addVectorCompose() Composes an ADD with a vector of 0-1 ADDs.
Cudd_addWalsh() Generates a Walsh matrix in ADD form.
Cudd_addXeqy() Generates an ADD for the function x==y.
Cudd_addXnor() XNOR of two 0-1 ADDs.
Cudd_addXor() XOR of two 0-1 ADDs.
Cudd_bddAdjPermuteX() Rearranges a set of variables in the BDD B.
Cudd_bddAndAbstractLimit() Takes the AND of two BDDs and simultaneously
abstracts the variables in cube. Returns NULL
if too many nodes are required.
Cudd_bddAndAbstract() Takes the AND of two BDDs and simultaneously
abstracts the variables in cube.
Cudd_bddAndLimit() Computes the conjunction of two BDDs f and g.
Returns NULL if too many nodes are required.
Cudd_bddAnd() Computes the conjunction of two BDDs f and g.
Cudd_bddApproxConjDecomp() Performs two-way conjunctive decomposition of a
BDD.
Cudd_bddApproxDisjDecomp() Performs two-way disjunctive decomposition of a
BDD.
Cudd_bddBindVar() Prevents sifting of a variable.
Cudd_bddBooleanDiff() Computes the boolean difference of f with
respect to x.
Cudd_bddCharToVect() Computes a vector whose image equals a non-zero
function.
Cudd_bddClippingAndAbstract() Approximates the conjunction of two BDDs f and
g and simultaneously abstracts the variables in
cube.
Cudd_bddClippingAnd() Approximates the conjunction of two BDDs f and
g.
Cudd_bddClosestCube() Finds a cube of f at minimum Hamming distance
from g.
Cudd_bddCompose() Substitutes g for x_v in the BDD for f.
Cudd_bddComputeCube() Computes the cube of an array of BDD variables.
Cudd_bddConstrainDecomp() BDD conjunctive decomposition as in McMillan's
CAV96 paper.
Cudd_bddConstrain() Computes f constrain c.
Cudd_bddCorrelationWeights() Computes the correlation of f and g for given
input probabilities.
Cudd_bddCorrelation() Computes the correlation of f and g.
Cudd_bddExistAbstract() Existentially abstracts all the variables in
cube from f.
Cudd_bddGenConjDecomp() Performs two-way conjunctive decomposition of a
BDD.
Cudd_bddGenDisjDecomp() Performs two-way disjunctive decomposition of a
BDD.
Cudd_bddIntersect() Returns a function included in the intersection
of f and g.
Cudd_bddIsNsVar() Checks whether a variable is next state.
Cudd_bddIsPiVar() Checks whether a variable is primary input.
Cudd_bddIsPsVar() Checks whether a variable is present state.
Cudd_bddIsVarEssential() Determines whether a given variable is
essential with a given phase in a BDD.
Cudd_bddIsVarHardGroup() Checks whether a variable is set to be in a
hard group.
Cudd_bddIsVarToBeGrouped() Checks whether a variable is set to be grouped.
Cudd_bddIsVarToBeUngrouped() Checks whether a variable is set to be
ungrouped.
Cudd_bddIsop() Computes a BDD in the interval between L and U
with a simple sum-of-produuct cover.
Cudd_bddIteConstant() Implements ITEconstant(f,g,h).
Cudd_bddIterConjDecomp() Performs two-way conjunctive decomposition of a
BDD.
Cudd_bddIterDisjDecomp() Performs two-way disjunctive decomposition of a
BDD.
Cudd_bddIte() Implements ITE(f,g,h).
Cudd_bddIthVar() Returns the BDD variable with index i.
Cudd_bddLICompaction() Performs safe minimization of a BDD.
Cudd_bddLeqUnless() Tells whether f is less than of equal to G
unless D is 1.
Cudd_bddLeq() Determines whether f is less than or equal to
g.
Cudd_bddLiteralSetIntersection()
Computes the intesection of two sets of
literals represented as BDDs.
Cudd_bddMakePrime() Expands cube to a prime implicant of f.
Cudd_bddMinimize() Finds a small BDD that agrees with
f over c.
Cudd_bddNPAnd() Computes f non-polluting-and g.
Cudd_bddNand() Computes the NAND of two BDDs f and g.
Cudd_bddNewVarAtLevel() Returns a new BDD variable at a specified
level.
Cudd_bddNewVar() Returns a new BDD variable.
Cudd_bddNor() Computes the NOR of two BDDs f and g.
Cudd_bddOr() Computes the disjunction of two BDDs f and g.
Cudd_bddPermute() Permutes the variables of a BDD.
Cudd_bddPickArbitraryMinterms()
Picks k on-set minterms evenly distributed from
given DD.
Cudd_bddPickOneCube() Picks one on-set cube randomly from the given
DD.
Cudd_bddPickOneMinterm() Picks one on-set minterm randomly from the
given DD.
Cudd_bddPrintCover() Prints a sum of prime implicants of a BDD.
Cudd_bddReadPairIndex() Reads a corresponding pair index for a given
index.
Cudd_bddRead() Reads in a graph (without labels) given as a
list of arcs.
Cudd_bddRealignDisable() Disables realignment of ZDD order to BDD order.
Cudd_bddRealignEnable() Enables realignment of BDD order to ZDD order.
Cudd_bddRealignmentEnabled() Tells whether the realignment of BDD order to
ZDD order is enabled.
Cudd_bddResetVarToBeGrouped() Resets a variable not to be grouped.
Cudd_bddRestrict() BDD restrict according to Coudert and Madre's
algorithm (ICCAD90).
Cudd_bddSetNsVar() Sets a variable type to next state.
Cudd_bddSetPairIndex() Sets a corresponding pair index for a given
index.
Cudd_bddSetPiVar() Sets a variable type to primary input.
Cudd_bddSetPsVar() Sets a variable type to present state.
Cudd_bddSetVarHardGroup() Sets a variable to be a hard group.
Cudd_bddSetVarToBeGrouped() Sets a variable to be grouped.
Cudd_bddSetVarToBeUngrouped() Sets a variable to be ungrouped.
Cudd_bddSqueeze() Finds a small BDD in a function interval.
Cudd_bddSwapVariables() Swaps two sets of variables of the same size (x
and y) in the BDD f.
Cudd_bddTransfer() Convert a BDD from a manager to another one.
Cudd_bddUnbindVar() Allows the sifting of a variable.
Cudd_bddUnivAbstract() Universally abstracts all the variables in cube
from f.
Cudd_bddVarConjDecomp() Performs two-way conjunctive decomposition of a
BDD.
Cudd_bddVarDisjDecomp() Performs two-way disjunctive decomposition of a
BDD.
Cudd_bddVarIsBound() Tells whether a variable can be sifted.
Cudd_bddVarIsDependent() Checks whether a variable is dependent on
others in a function.
Cudd_bddVarMap() Remaps the variables of a BDD using the default
variable map.
Cudd_bddVectorCompose() Composes a BDD with a vector of BDDs.
Cudd_bddXnor() Computes the exclusive NOR of two BDDs f and g.
Cudd_bddXorExistAbstract() Takes the exclusive OR of two BDDs and
simultaneously abstracts the variables in cube.
Cudd_bddXor() Computes the exclusive OR of two BDDs f and g.
Cudd_tlcInfoFree() Frees a DdTlcInfo Structure.
Cudd_zddChange() Substitutes a variable with its complement in a
ZDD.
Cudd_zddComplement() Computes a complement cover for a ZDD node.
Cudd_zddCountDouble() Counts the number of minterms of a ZDD.
Cudd_zddCountMinterm() Counts the number of minterms of a ZDD.
Cudd_zddCount() Counts the number of minterms in a ZDD.
Cudd_zddCoverPathToString() Converts a path of a ZDD representing a cover
to a string.
Cudd_zddDagSize() Counts the number of nodes in a ZDD.
Cudd_zddDiffConst() Performs the inclusion test for ZDDs (P implies
Q).
Cudd_zddDiff() Computes the difference of two ZDDs.
Cudd_zddDivideF() Modified version of Cudd_zddDivide.
Cudd_zddDivide() Computes the quotient of two unate covers.
Cudd_zddDumpDot() Writes a dot file representing the argument
ZDDs.
Cudd_zddFirstPath() Finds the first path of a ZDD.
Cudd_zddForeachPath() Iterates over the paths of a ZDD.
Cudd_zddIntersect() Computes the intersection of two ZDDs.
Cudd_zddIsop() Computes an ISOP in ZDD form from BDDs.
Cudd_zddIte() Computes the ITE of three ZDDs.
Cudd_zddIthVar() Returns the ZDD variable with index i.
Cudd_zddNextPath() Generates the next path of a ZDD.
Cudd_zddPortFromBdd() Converts a BDD into a ZDD.
Cudd_zddPortToBdd() Converts a ZDD into a BDD.
Cudd_zddPrintCover() Prints a sum of products from a ZDD
representing a cover.
Cudd_zddPrintDebug() Prints to the standard output a ZDD and its
statistics.
Cudd_zddPrintMinterm() Prints a disjoint sum of product form for a
ZDD.
Cudd_zddPrintSubtable() Prints the ZDD table.
Cudd_zddProduct() Computes the product of two covers represented
by ZDDs.
Cudd_zddReadNodeCount() Reports the number of nodes in ZDDs.
Cudd_zddRealignDisable() Disables realignment of ZDD order to BDD order.
Cudd_zddRealignEnable() Enables realignment of ZDD order to BDD order.
Cudd_zddRealignmentEnabled() Tells whether the realignment of ZDD order to
BDD order is enabled.
Cudd_zddReduceHeap() Main dynamic reordering routine for ZDDs.
Cudd_zddShuffleHeap() Reorders ZDD variables according to given
permutation.
Cudd_zddSubset0() Computes the negative cofactor of a ZDD w.r.t.
a variable.
Cudd_zddSubset1() Computes the positive cofactor of a ZDD w.r.t.
a variable.
Cudd_zddSymmProfile() Prints statistics on symmetric ZDD variables.
Cudd_zddUnateProduct() Computes the product of two unate covers.
Cudd_zddUnion() Computes the union of two ZDDs.
Cudd_zddVarsFromBddVars() Creates one or more ZDD variables for each BDD
variable.
Cudd_zddWeakDivF() Modified version of Cudd_zddWeakDiv.
Cudd_zddWeakDiv() Applies weak division to two covers.
**********************************************************************
External functions and data strucures of the CUDD package. To
turn on the gathering of statistics, define DD_STATS. To link with
mis, define DD_MIS. Modified by Abelardo Pardo to interface it to
VIS.
int
Cudd_AddHook(
DdManager * dd,
DD_HFP f,
Cudd_HookType where
)
Adds a function to a hook. A hook is a list of application-provided
functions called on certain occasions by the package. Returns 1 if the
function is successfully added; 2 if the function was already in the list; 0
otherwise.
Side Effects: None
DdApaDigit
Cudd_ApaAdd(
int digits,
DdApaNumber a,
DdApaNumber b,
DdApaNumber sum
)
Adds two arbitrary precision integers. Returns the carry out of the most
significant digit.
Side Effects: The result of the sum is stored in parameter sum.
int
Cudd_ApaCompareRatios(
int digitsFirst,
DdApaNumber firstNum,
unsigned int firstDen,
int digitsSecond,
DdApaNumber secondNum,
unsigned int secondDen
)
Compares the ratios of two arbitrary precision integers to two unsigned
ints. Returns 1 if the first number is larger; 0 if they are equal; -1 if
the second number is larger.
Side Effects: None
int
Cudd_ApaCompare(
int digitsFirst,
DdApaNumber first,
int digitsSecond,
DdApaNumber second
)
Compares two arbitrary precision integers. Returns 1 if the first number is
larger; 0 if they are equal; -1 if the second number is larger.
Side Effects: None
void
Cudd_ApaCopy(
int digits,
DdApaNumber source,
DdApaNumber dest
)
Makes a copy of an arbitrary precision integer.
Side Effects: Changes parameter dest.
DdApaNumber
Cudd_ApaCountMinterm(
DdManager * manager,
DdNode * node,
int nvars,
int * digits
)
Counts the number of minterms of a DD. The function is assumed to depend on
nvars variables. The minterm count is represented as an arbitrary precision
unsigned integer, to allow for any number of variables CUDD supports.
Returns a pointer to the array representing the number of minterms of the
function rooted at node if successful; NULL otherwise.
Side Effects: The number of digits of the result is returned in parameter
digits.
unsigned int
Cudd_ApaIntDivision(
int digits,
DdApaNumber dividend,
unsigned int divisor,
DdApaNumber quotient
)
Divides an arbitrary precision integer by a 32-bit unsigned integer. Returns
the remainder of the division. This procedure relies on the assumption that
the number of bits of a DdApaDigit plus the number of bits of an unsigned
int is less the number of bits of the mantissa of a double. This guarantees
that the product of a DdApaDigit and an unsigned int can be represented
without loss of precision by a double. On machines where this assumption is
not satisfied, this procedure will malfunction.
Side Effects: The quotient is returned in parameter quotient.
int
Cudd_ApaNumberOfDigits(
int binaryDigits
)
Finds the number of digits for an arbitrary precision integer given the
maximum number of binary digits. The number of binary digits should be
positive. Returns the number of digits if successful; 0 otherwise.
Side Effects: None
void
Cudd_ApaPowerOfTwo(
int digits,
DdApaNumber number,
int power
)
Sets an arbitrary precision integer to a power of two. If the power of two
is too large to be represented, the number is set to 0.
Side Effects: The result is returned in parameter number.
int
Cudd_ApaPrintDecimal(
FILE * fp,
int digits,
DdApaNumber number
)
Prints an arbitrary precision integer in decimal format. Returns 1 if
successful; 0 otherwise.
Side Effects: None
int
Cudd_ApaPrintDensity(
FILE * fp,
DdManager * dd,
DdNode * node,
int nvars
)
Prints the density of a BDD or ADD using arbitrary precision arithmetic.
Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_ApaPrintExponential(
FILE * fp,
int digits,
DdApaNumber number,
int precision
)
Prints an arbitrary precision integer in exponential format. Returns 1 if
successful; 0 otherwise.
Side Effects: None
int
Cudd_ApaPrintHex(
FILE * fp,
int digits,
DdApaNumber number
)
Prints an arbitrary precision integer in hexadecimal format. Returns 1 if
successful; 0 otherwise.
Side Effects: None
int
Cudd_ApaPrintMintermExp(
FILE * fp,
DdManager * dd,
DdNode * node,
int nvars,
int precision
)
Prints the number of minterms of a BDD or ADD in exponential format using
arbitrary precision arithmetic. Parameter precision controls the number of
signficant digits printed. Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_ApaPrintMinterm(
FILE * fp,
DdManager * dd,
DdNode * node,
int nvars
)
Prints the number of minterms of a BDD or ADD using arbitrary precision
arithmetic. Returns 1 if successful; 0 otherwise.
Side Effects: None
void
Cudd_ApaSetToLiteral(
int digits,
DdApaNumber number,
DdApaDigit literal
)
Sets an arbitrary precision integer to a one-digit literal.
Side Effects: The result is returned in parameter number.
void
Cudd_ApaShiftRight(
int digits,
DdApaDigit in,
DdApaNumber a,
DdApaNumber b
)
Shifts right an arbitrary precision integer by one binary place. The most
significant binary digit of the result is taken from parameter
in.
Side Effects: The result is returned in parameter b.
DdApaDigit
Cudd_ApaShortDivision(
int digits,
DdApaNumber dividend,
DdApaDigit divisor,
DdApaNumber quotient
)
Divides an arbitrary precision integer by a digit.
Side Effects: The quotient is returned in parameter quotient.
DdApaDigit
Cudd_ApaSubtract(
int digits,
DdApaNumber a,
DdApaNumber b,
DdApaNumber diff
)
Subtracts two arbitrary precision integers. Returns the borrow out of the
most significant digit.
Side Effects: The result of the subtraction is stored in parameter
diff.
void
Cudd_AutodynDisableZdd(
DdManager * unique
)
Disables automatic dynamic reordering of ZDDs.
Side Effects: None
void
Cudd_AutodynDisable(
DdManager * unique
)
Disables automatic dynamic reordering.
Side Effects: None
void
Cudd_AutodynEnableZdd(
DdManager * unique,
Cudd_ReorderingTy method
)
Enables automatic dynamic reordering of ZDDs. Parameter method is used to
determine the method used for reordering ZDDs. If CUDD_REORDER_SAME is
passed, the method is unchanged.
Side Effects: None
void
Cudd_AutodynEnable(
DdManager * unique,
Cudd_ReorderingTy method
)
Enables automatic dynamic reordering of BDDs and ADDs. Parameter method is
used to determine the method used for reordering. If CUDD_REORDER_SAME is
passed, the method is unchanged.
Side Effects: None
double
Cudd_AverageDistance(
DdManager * dd
)
Computes the average distance between adjacent nodes in the manager.
Adjacent nodes are node pairs such that the second node is the then child,
else child, or next node in the collision list.
Side Effects: None
DdNode *
Cudd_BddToAdd(
DdManager * dd,
DdNode * B
)
Converts a BDD to a 0-1 ADD. Returns a pointer to the resulting ADD if
successful; NULL otherwise.
Side Effects: None
int
Cudd_BddToCubeArray(
DdManager * dd,
DdNode * cube,
int * array
)
Builds a positional array from the BDD of a cube. Array must have one entry
for each BDD variable. The positional array has 1 in i-th position if the
variable of index i appears in true form in the cube; it has 0 in i-th
position if the variable of index i appears in complemented form in the
cube; finally, it has 2 in i-th position if the variable of index i does not
appear in the cube. Returns 1 if successful (the BDD is indeed a cube); 0
otherwise.
Side Effects: The result is in the array passed by reference.
DdNode *
Cudd_BiasedOverApprox(
DdManager * dd, manager
DdNode * f, function to be superset
DdNode * b, bias function
int numVars, number of variables in the support of f
int threshold, when to stop approximation
double quality1, minimum improvement for accepted changes
when b=1
double quality0 minimum improvement for accepted changes
when b=0
)
Extracts a dense superset from a BDD. The procedure is identical to the
underapproximation procedure except for the fact that it works on the
complement of the given function. Extracting the subset of the complement
function is equivalent to extracting the superset of the function. Returns a
pointer to the BDD of the superset if successful. NULL if intermediate
result causes the procedure to run out of memory. The parameter numVars is
the maximum number of variables to be used in minterm calculation. The
optimal number should be as close as possible to the size of the support of
f. However, it is safe to pass the value returned by Cudd_ReadSize for
numVars when the number of variables is under 1023. If numVars is larger
than 1023, it will overflow. If a 0 parameter is passed then the procedure
will compute a value which will avoid overflow but will cause underflow with
2046 variables or more.
Side Effects: None
DdNode *
Cudd_BiasedUnderApprox(
DdManager * dd, manager
DdNode * f, function to be subset
DdNode * b, bias function
int numVars, number of variables in the support of f
int threshold, when to stop approximation
double quality1, minimum improvement for accepted changes
when b=1
double quality0 minimum improvement for accepted changes
when b=0
)
Extracts a dense subset from a BDD. This procedure uses a biased remapping
technique and density as the cost function. The bias is a function. This
procedure tries to approximate where the bias is 0 and preserve the given
function where the bias is 1. Returns a pointer to the BDD of the subset if
successful. NULL if the procedure runs out of memory. The parameter numVars
is the maximum number of variables to be used in minterm calculation. The
optimal number should be as close as possible to the size of the support of
f. However, it is safe to pass the value returned by Cudd_ReadSize for
numVars when the number of variables is under 1023. If numVars is larger
than 1023, it will cause overflow. If a 0 parameter is passed then the
procedure will compute a value which will avoid overflow but will cause
underflow with 2046 variables or more.
Side Effects: None
DdNode *
Cudd_CProjection(
DdManager * dd,
DdNode * R,
DdNode * Y
)
Computes the compatible projection of relation R with respect to cube Y.
Returns a pointer to the c-projection if successful; NULL otherwise. For a
comparison between Cudd_CProjection and Cudd_PrioritySelect, see the
documentation of the latter.
Side Effects: None
int
Cudd_CheckKeys(
DdManager * table
)
Checks for the following conditions: Wrong sizes of subtables.
Wrong number of keys found in unique subtable. Wrong number of dead
found in unique subtable. Wrong number of keys found in the constant
table Wrong number of dead found in the constant table Wrong number
of total slots found Wrong number of maximum keys found Wrong number
of total dead found Reports the average length of non-empty lists.
Returns the number of subtables for which the number of keys is wrong.
Side Effects: None
int
Cudd_CheckZeroRef(
DdManager * manager
)
Checks the unique table for nodes with non-zero reference counts. It is
normally called before Cudd_Quit to make sure that there are no memory leaks
due to missing Cudd_RecursiveDeref's. Takes into account that reference
counts may saturate and that the basic constants and the projection
functions are referenced by the manager. Returns the number of nodes with
non-zero reference count. (Except for the cases mentioned above.)
Side Effects: None
int
Cudd_ClassifySupport(
DdManager * dd, manager
DdNode * f, first DD
DdNode * g, second DD
DdNode ** common, cube of shared variables
DdNode ** onlyF, cube of variables only in f
DdNode ** onlyG cube of variables only in g
)
Classifies the variables in the support of two DDs f and
g, depending on whther they appear in both DDs, only in
f, or only in g. Returns 1 if successful; 0
otherwise.
Side Effects: The cubes of the three classes of variables are returned as
side effects.
void
Cudd_ClearErrorCode(
DdManager * dd
)
Clear the error code of a manager.
Side Effects: None
double *
Cudd_CofMinterm(
DdManager * dd,
DdNode * node
)
Computes the fraction of minterms in the on-set of all the positive
cofactors of DD. Returns the pointer to an array of doubles if successful;
NULL otherwise. The array has as many positions as there are BDD variables
in the manager plus one. The last position of the array contains the
fraction of the minterms in the ON-set of the function represented by the
BDD or ADD. The other positions of the array hold the variable signatures.
Side Effects: None
DdNode *
Cudd_Cofactor(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the cofactor of f with respect to g; g must be the BDD or the ADD
of a cube. Returns a pointer to the cofactor if successful; NULL otherwise.
Side Effects: None
Cudd_Complement(
node
)
Returns the complemented version of a pointer.
Side Effects: none
int
Cudd_CountLeaves(
DdNode * node
)
Counts the number of leaves in a DD. Returns the number of leaves in the DD
rooted at node if successful; CUDD_OUT_OF_MEM otherwise.
Side Effects: None
double
Cudd_CountMinterm(
DdManager * manager,
DdNode * node,
int nvars
)
Counts the number of minterms of a DD. The function is assumed to depend on
nvars variables. The minterm count is represented as a double, to allow for
a larger number of variables. Returns the number of minterms of the function
rooted at node if successful; (double) CUDD_OUT_OF_MEM otherwise.
Side Effects: None
double
Cudd_CountPathsToNonZero(
DdNode * node
)
Counts the number of paths to a non-zero terminal of a DD. The path count is
represented as a double, to allow for a larger number of variables. Returns
the number of paths of the function rooted at node.
Side Effects: None
double
Cudd_CountPath(
DdNode * node
)
Counts the number of paths of a DD. Paths to all terminal nodes are counted.
The path count is represented as a double, to allow for a larger number of
variables. Returns the number of paths of the function rooted at node if
successful; (double) CUDD_OUT_OF_MEM otherwise.
Side Effects: None
DdNode *
Cudd_CubeArrayToBdd(
DdManager * dd,
int * array
)
Builds a cube from a positional array. The array must have one integer entry
for each BDD variable. If the i-th entry is 1, the variable of index i
appears in true form in the cube; If the i-th entry is 0, the variable of
index i appears complemented in the cube; otherwise the variable does not
appear in the cube. Returns a pointer to the BDD for the cube if successful;
NULL otherwise.
Side Effects: None
int
Cudd_DagSize(
DdNode * node
)
Counts the number of nodes in a DD. Returns the number of nodes in the graph
rooted at node.
Side Effects: None
int
Cudd_DeadAreCounted(
DdManager * dd
)
Tells whether dead nodes are counted towards triggering reordering. Returns
1 if dead nodes are counted; 0 otherwise.
Side Effects: None
int
Cudd_DebugCheck(
DdManager * table
)
Checks for inconsistencies in the DD heap: node has illegal index
live node has dead children node has illegal Then or Else pointers
BDD/ADD node has identical children ZDD node has zero then child
wrong number of total nodes wrong number of dead nodes ref
count error at node Returns 0 if no inconsistencies are found;
DD_OUT_OF_MEM if there is not enough memory; 1 otherwise.
Side Effects: None
DdNode *
Cudd_Decreasing(
DdManager * dd,
DdNode * f,
int i
)
Determines whether the function represented by BDD f is negative unate
(monotonic decreasing) in variable i. Returns the constant one is f is unate
and the (logical) constant zero if it is not. This function does not
generate any new nodes.
Side Effects: None
void
Cudd_DelayedDerefBdd(
DdManager * table,
DdNode * n
)
Enqueues node n for later dereferencing. If the queue is full decreases the
reference count of the oldest node N to make room for n. If N dies,
recursively decreases the reference counts of its children. It is used to
dispose of a BDD that is currently not needed, but may be useful again in
the near future. The dereferencing proper is done as in Cudd_IterDerefBdd.
Side Effects: None
double
Cudd_Density(
DdManager * dd, manager
DdNode * f, function whose density is sought
int nvars size of the support of f
)
Computes the density of a BDD or ADD. The density is the ratio of the number
of minterms to the number of nodes. If 0 is passed as number of variables,
the number of variables existing in the manager is used. Returns the density
if successful; (double) CUDD_OUT_OF_MEM otherwise.
Side Effects: None
void
Cudd_Deref(
DdNode * node
)
Decreases the reference count of node. It is primarily used in recursive
procedures to decrease the ref count of a result node before returning it.
This accomplishes the goal of removing the protection applied by a previous
Cudd_Ref.
Side Effects: None
void
Cudd_DisableGarbageCollection(
DdManager * dd
)
Disables garbage collection. Garbage collection is initially enabled. This
function may be called to disable it. However, garbage collection will still
occur when a new node must be created and no memory is left, or when garbage
collection is required for correctness. (E.g., before reordering.)
Side Effects: None
int
Cudd_DisableReorderingReporting(
DdManager * dd
)
Disables reporting of reordering stats. Returns 1 if successful; 0
otherwise.
Side Effects: Removes functions from the pre-reordering and post-reordering
hooks.
int
Cudd_DumpBlifBody(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes a blif body representing the argument BDDs as a network of
multiplexers. No header (.model, .inputs, and .outputs) and footer (.end)
are produced by this function. One multiplexer is written for each BDD node.
It returns 1 in case of success; 0 otherwise (e.g., out-of-memory, file
system full, or an ADD with constants different from 0 and 1).
Cudd_DumpBlifBody does not close the file: This is the caller
responsibility. Cudd_DumpBlifBody uses a minimal unique subset of the
hexadecimal address of a node as name for it. If the argument inames is non-
null, it is assumed to hold the pointers to the names of the inputs.
Similarly for onames. This function prints out only .names part.
Side Effects: None
int
Cudd_DumpBlif(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
char * mname, model name (or NULL)
FILE * fp pointer to the dump file
)
Writes a blif file representing the argument BDDs as a network of
multiplexers. One multiplexer is written for each BDD node. It returns 1 in
case of success; 0 otherwise (e.g., out-of-memory, file system full, or an
ADD with constants different from 0 and 1). Cudd_DumpBlif does not close the
file: This is the caller responsibility. Cudd_DumpBlif uses a minimal unique
subset of the hexadecimal address of a node as name for it. If the argument
inames is non-null, it is assumed to hold the pointers to the names of the
inputs. Similarly for onames.
Side Effects: None
int
Cudd_DumpDDcal(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes a DDcal file representing the argument BDDs. It returns 1 in case of
success; 0 otherwise (e.g., out-of-memory or file system full).
Cudd_DumpDDcal does not close the file: This is the caller responsibility.
Cudd_DumpDDcal uses a minimal unique subset of the hexadecimal address of a
node as name for it. If the argument inames is non-null, it is assumed to
hold the pointers to the names of the inputs. Similarly for onames.
Side Effects: None
int
Cudd_DumpDaVinci(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes a daVinci file representing the argument BDDs. It returns 1 in case
of success; 0 otherwise (e.g., out-of-memory or file system full).
Cudd_DumpDaVinci does not close the file: This is the caller responsibility.
Cudd_DumpDaVinci uses a minimal unique subset of the hexadecimal address of
a node as name for it. If the argument inames is non-null, it is assumed to
hold the pointers to the names of the inputs. Similarly for onames.
Side Effects: None
int
Cudd_DumpDot(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes a file representing the argument DDs in a format suitable for the
graph drawing program dot. It returns 1 in case of success; 0 otherwise
(e.g., out-of-memory, file system full). Cudd_DumpDot does not close the
file: This is the caller responsibility. Cudd_DumpDot uses a minimal unique
subset of the hexadecimal address of a node as name for it. If the argument
inames is non-null, it is assumed to hold the pointers to the names of the
inputs. Similarly for onames. Cudd_DumpDot uses the following convention to
draw arcs: solid line: THEN arcs; dotted line: complement
arcs; dashed line: regular ELSE arcs. The dot options are chosen
so that the drawing fits on a letter-size sheet.
Side Effects: None
int
Cudd_DumpFactoredForm(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes factored forms representing the argument BDDs. The format of the
factored form is the one used in the genlib files for technology mapping in
sis. It returns 1 in case of success; 0 otherwise (e.g., file system full).
Cudd_DumpFactoredForm does not close the file: This is the caller
responsibility. Caution must be exercised because a factored form may be
exponentially larger than the argument BDD. If the argument inames is non-
null, it is assumed to hold the pointers to the names of the inputs.
Similarly for onames.
Side Effects: None
DdNode *
Cudd_Dxygtdxz(
DdManager * dd, DD manager
int N, number of x, y, and z variables
DdNode ** x, array of x variables
DdNode ** y, array of y variables
DdNode ** z array of z variables
)
This function generates a BDD for the function d(x,y) > d(x,z); x, y, and
z are N-bit numbers, x[0] x[1] ... x[N-1], y[0] y[1] ... y[N-1], and z[0]
z[1] ... z[N-1], with 0 the most significant bit. The distance d(x,y) is
defined as: sum_{i=0}^{N-1}(|x_i - y_i| cdot 2^{N-i-1}). The BDD is built
bottom-up. It has 7*N-3 internal nodes, if the variables are ordered as
follows: x[0] y[0] z[0] x[1] y[1] z[1] ... x[N-1] y[N-1] z[N-1].
Side Effects: None
DdNode *
Cudd_Dxygtdyz(
DdManager * dd, DD manager
int N, number of x, y, and z variables
DdNode ** x, array of x variables
DdNode ** y, array of y variables
DdNode ** z array of z variables
)
This function generates a BDD for the function d(x,y) > d(y,z); x, y, and
z are N-bit numbers, x[0] x[1] ... x[N-1], y[0] y[1] ... y[N-1], and z[0]
z[1] ... z[N-1], with 0 the most significant bit. The distance d(x,y) is
defined as: sum_{i=0}^{N-1}(|x_i - y_i| cdot 2^{N-i-1}). The BDD is built
bottom-up. It has 7*N-3 internal nodes, if the variables are ordered as
follows: x[0] y[0] z[0] x[1] y[1] z[1] ... x[N-1] y[N-1] z[N-1].
Side Effects: None
void
Cudd_EnableGarbageCollection(
DdManager * dd
)
Enables garbage collection. Garbage collection is initially enabled.
Therefore it is necessary to call this function only if garbage collection
has been explicitly disabled.
Side Effects: None
int
Cudd_EnableReorderingReporting(
DdManager * dd
)
Enables reporting of reordering stats. Returns 1 if successful; 0 otherwise.
Side Effects: Installs functions in the pre-reordering and post-reordering
hooks.
int
Cudd_EpdCountMinterm(
DdManager * manager,
DdNode * node,
int nvars,
EpDouble * epd
)
Counts the number of minterms of a DD with extended precision. The function
is assumed to depend on nvars variables. The minterm count is represented as
an EpDouble, to allow any number of variables. Returns 0 if successful;
CUDD_OUT_OF_MEM otherwise.
Side Effects: None
int
Cudd_EqualSupNorm(
DdManager * dd, manager
DdNode * f, first ADD
DdNode * g, second ADD
CUDD_VALUE_TYPE tolerance, maximum allowed difference
int pr verbosity level
)
Compares two ADDs for equality within tolerance. Two ADDs are reported to be
equal if the maximum difference between them (the sup norm of their
difference) is less than or equal to the tolerance parameter. Returns 1 if
the two ADDs are equal (within tolerance); 0 otherwise. If parameter
pr is positive the first failure is reported to the standard
output.
Side Effects: None
int
Cudd_EquivDC(
DdManager * dd,
DdNode * F,
DdNode * G,
DdNode * D
)
Tells whether F and G are identical wherever D is 0. F and G are either two
ADDs or two BDDs. D is either a 0-1 ADD or a BDD. The function returns 1 if
F and G are equivalent, and 0 otherwise. No new nodes are created.
Side Effects: None
int
Cudd_EstimateCofactorSimple(
DdNode * node,
int i
)
Estimates the number of nodes in a cofactor of a DD. Returns an estimate of
the number of nodes in the positive cofactor of the graph rooted at node
with respect to the variable whose index is i. This procedure implements
with minor changes the algorithm of Cabodi et al. (ICCAD96). It does not
allocate any memory, it does not change the state of the manager, and it is
fast. However, it has been observed to overestimate the size of the cofactor
by as much as a factor of 2.
Side Effects: None
int
Cudd_EstimateCofactor(
DdManager * dd, manager
DdNode * f, function
int i, index of variable
int phase 1: positive; 0: negative
)
Estimates the number of nodes in a cofactor of a DD. Returns an estimate of
the number of nodes in a cofactor of the graph rooted at node with respect
to the variable whose index is i. In case of failure, returns
CUDD_OUT_OF_MEM. This function uses a refinement of the algorithm of Cabodi
et al. (ICCAD96). The refinement allows the procedure to account for part of
the recombination that may occur in the part of the cofactor above the
cofactoring variable. This procedure does no create any new node. It does
keep a small table of results; therefore it may run out of memory. If this
is a concern, one should use Cudd_EstimateCofactorSimple, which is faster,
does not allocate any memory, but is less accurate.
Side Effects: None
DdNode *
Cudd_Eval(
DdManager * dd,
DdNode * f,
int * inputs
)
Finds the value of a DD for a given variable assignment. The variable
assignment is passed in an array of int's, that should specify a zero or a
one for each variable in the support of the function. Returns a pointer to a
constant node. No new nodes are produced.
Side Effects: None
double
Cudd_ExpectedUsedSlots(
DdManager * dd
)
Computes the fraction of slots in the unique table that should be in use.
This expected value is based on the assumption that the hash function
distributes the keys randomly; it can be compared with the result of
Cudd_ReadUsedSlots to monitor the performance of the unique table hash
function.
Side Effects: None
Cudd_E(
node
)
Returns the else child of an internal node. If node is a
constant node, the result is unpredictable.
Side Effects: none
DdNode *
Cudd_FindEssential(
DdManager * dd,
DdNode * f
)
Returns the cube of the essential variables. A positive literal means that
the variable must be set to 1 for the function to be 1. A negative literal
means that the variable must be set to 0 for the function to be 1. Returns a
pointer to the cube BDD if successful; NULL otherwise.
Side Effects: None
DdTlcInfo *
Cudd_FindTwoLiteralClauses(
DdManager * dd,
DdNode * f
)
Returns the one- and two-literal clauses of a DD. Returns a pointer to the
structure holding the clauses if successful; NULL otherwise. For a constant
DD, the empty set of clauses is returned. This is obviously correct for a
non-zero constant. For the constant zero, it is based on the assumption that
only those clauses containing variables in the support of the function are
considered. Since the support of a constant function is empty, no clauses
are returned.
Side Effects: None
DdGen *
Cudd_FirstCube(
DdManager * dd,
DdNode * f,
int ** cube,
CUDD_VALUE_TYPE * value
)
Defines an iterator on the onset of a decision diagram and finds its first
cube. Returns a generator that contains the information necessary to
continue the enumeration if successful; NULL otherwise. A cube is
represented as an array of literals, which are integers in {0, 1, 2}; 0
represents a complemented literal, 1 represents an uncomplemented literal,
and 2 stands for don't care. The enumeration produces a disjoint cover of
the function associated with the diagram. The size of the array equals the
number of variables in the manager at the time Cudd_FirstCube is called.
For each cube, a value is also returned. This value is always 1 for a BDD,
while it may be different from 1 for an ADD. For BDDs, the offset is the set
of cubes whose value is the logical zero. For ADDs, the offset is the set of
cubes whose value is the background value. The cubes of the offset are not
enumerated.
Side Effects: The first cube and its value are returned as side effects.
DdGen *
Cudd_FirstNode(
DdManager * dd,
DdNode * f,
DdNode ** node
)
Defines an iterator on the nodes of a decision diagram and finds its first
node. Returns a generator that contains the information necessary to
continue the enumeration if successful; NULL otherwise. The nodes are
enumerated in a reverse topological order, so that a node is always preceded
in the enumeration by its descendants.
Side Effects: The first node is returned as a side effect.
DdGen *
Cudd_FirstPrime(
DdManager * dd,
DdNode * l,
DdNode * u,
int ** cube
)
Defines an iterator on a pair of BDDs describing a (possibly incompletely
specified) Boolean functions and finds the first cube of a cover of the
function. Returns a generator that contains the information necessary to
continue the enumeration if successful; NULL otherwise. The two argument
BDDs are the lower and upper bounds of an interval. It is a mistake to call
this function with a lower bound that is not less than or equal to the upper
bound. A cube is represented as an array of literals, which are integers
in {0, 1, 2}; 0 represents a complemented literal, 1 represents an
uncomplemented literal, and 2 stands for don't care. The enumeration
produces a prime and irredundant cover of the function associated with the
two BDDs. The size of the array equals the number of variables in the
manager at the time Cudd_FirstCube is called. This iterator can only be
used on BDDs.
Side Effects: The first cube is returned as side effect.
Cudd_ForeachCube(
manager,
f,
gen,
cube,
value
)
Iterates over the cubes of a decision diagram f. DdManager
*manager; DdNode *f; DdGen *gen; int *cube;
CUDD_VALUE_TYPE value; Cudd_ForeachCube allocates and frees the
generator. Therefore the application should not try to do that. Also, the
cube is freed at the end of Cudd_ForeachCube and hence is not available
outside of the loop. CAUTION: It is assumed that dynamic reordering will
not occur while there are open generators. It is the user's responsibility
to make sure that dynamic reordering does not occur. As long as new nodes
are not created during generation, and dynamic reordering is not called
explicitly, dynamic reordering will not occur. Alternatively, it is
sufficient to disable dynamic reordering. It is a mistake to dispose of a
diagram on which generation is ongoing.
Side Effects: none
Cudd_ForeachNode(
manager,
f,
gen,
node
)
Iterates over the nodes of a decision diagram f. DdManager
*manager; DdNode *f; DdGen *gen; DdNode *node; The
nodes are returned in a seemingly random order. Cudd_ForeachNode allocates
and frees the generator. Therefore the application should not try to do
that. CAUTION: It is assumed that dynamic reordering will not occur while
there are open generators. It is the user's responsibility to make sure that
dynamic reordering does not occur. As long as new nodes are not created
during generation, and dynamic reordering is not called explicitly, dynamic
reordering will not occur. Alternatively, it is sufficient to disable
dynamic reordering. It is a mistake to dispose of a diagram on which
generation is ongoing.
Side Effects: none
Cudd_ForeachPrime(
manager,
l,
u,
gen,
cube
)
Iterates over the primes of a Boolean function producing a prime and
irredundant cover. DdManager *manager; DdNode *l; DdNode
*u; DdGen *gen; int *cube; The Boolean function is described
by an upper bound and a lower bound. If the function is completely
specified, the two bounds coincide. Cudd_ForeachPrime allocates and frees
the generator. Therefore the application should not try to do that. Also,
the cube is freed at the end of Cudd_ForeachPrime and hence is not available
outside of the loop. CAUTION: It is a mistake to change a diagram on
which generation is ongoing.
Side Effects: none
void
Cudd_FreeTree(
DdManager * dd
)
Frees the variable group tree of the manager.
Side Effects: None
void
Cudd_FreeZddTree(
DdManager * dd
)
Frees the variable group tree of the manager.
Side Effects: None
int
Cudd_GarbageCollectionEnabled(
DdManager * dd
)
Returns 1 if garbage collection is enabled; 0 otherwise.
Side Effects: None
int
Cudd_GenFree(
DdGen * gen
)
Frees a CUDD generator. Always returns 0, so that it can be used in mis-like
foreach constructs.
Side Effects: None
DdNode *
Cudd_Increasing(
DdManager * dd,
DdNode * f,
int i
)
Determines whether the function represented by BDD f is positive unate
(monotonic increasing) in variable i. It is based on Cudd_Decreasing and the
fact that f is monotonic increasing in i if and only if its complement is
monotonic decreasing in i.
Side Effects: None
DdNode *
Cudd_IndicesToCube(
DdManager * dd,
int * array,
int n
)
Builds a cube of BDD variables from an array of indices. Returns a pointer
to the result if successful; NULL otherwise.
Side Effects: None
DdManager *
Cudd_Init(
unsigned int numVars, initial number of BDD variables (i.e.,
subtables)
unsigned int numVarsZ, initial number of ZDD variables (i.e.,
subtables)
unsigned int numSlots, initial size of the unique tables
unsigned int cacheSize, initial size of the cache
unsigned long maxMemory target maximum memory occupation
)
Creates a new DD manager, initializes the table, the basic constants and the
projection functions. If maxMemory is 0, Cudd_Init decides suitable values
for the maximum size of the cache and for the limit for fast unique table
growth based on the available memory. Returns a pointer to the manager if
successful; NULL otherwise.
Side Effects: None
Cudd_IsComplement(
node
)
Returns 1 if a pointer is complemented.
Side Effects: none
Cudd_IsConstant(
node
)
Returns 1 if the node is a constant node (rather than an internal node). All
constant nodes have the same index (CUDD_CONST_INDEX). The pointer passed to
Cudd_IsConstant may be either regular or complemented.
Side Effects: none
int
Cudd_IsGenEmpty(
DdGen * gen
)
Queries the status of a generator. Returns 1 if the generator is empty or
NULL; 0 otherswise.
Side Effects: None
int
Cudd_IsInHook(
DdManager * dd,
DD_HFP f,
Cudd_HookType where
)
Checks whether a function is in a hook. A hook is a list of application-
provided functions called on certain occasions by the package. Returns 1 if
the function is found; 0 otherwise.
Side Effects: None
int
Cudd_IsNonConstant(
DdNode * f
)
Returns 1 if a DD node is not constant. This function is useful to test the
results of Cudd_bddIteConstant, Cudd_addIteConstant, Cudd_addEvalConst.
These results may be a special value signifying non-constant. In the other
cases the macro Cudd_IsConstant can be used.
Side Effects: None
void
Cudd_IterDerefBdd(
DdManager * table,
DdNode * n
)
Decreases the reference count of node n. If n dies, recursively decreases
the reference counts of its children. It is used to dispose of a BDD that is
no longer needed. It is more efficient than Cudd_RecursiveDeref, but it
cannot be used on ADDs. The greater efficiency comes from being able to
assume that no constant node will ever die as a result of a call to this
procedure.
Side Effects: None
DdNode *
Cudd_LargestCube(
DdManager * manager,
DdNode * f,
int * length
)
Finds a largest cube in a DD. f is the DD we want to get the largest cube
for. The problem is translated into the one of finding a shortest path in f,
when both THEN and ELSE arcs are assumed to have unit length. This yields a
largest cube in the disjoint cover corresponding to the DD. Therefore, it is
not necessarily the largest implicant of f. Returns the largest cube as a
BDD.
Side Effects: The number of literals of the cube is returned in length.
DdNode *
Cudd_MakeBddFromZddCover(
DdManager * dd,
DdNode * node
)
Converts a ZDD cover to a BDD graph. If successful, it returns a BDD node,
otherwise it returns NULL.
MtrNode *
Cudd_MakeTreeNode(
DdManager * dd, manager
unsigned int low, index of the first group variable
unsigned int size, number of variables in the group
unsigned int type MTR_DEFAULT or MTR_FIXED
)
Creates a new variable group. The group starts at variable and contains size
variables. The parameter low is the index of the first variable. If the
variable already exists, its current position in the order is known to the
manager. If the variable does not exist yet, the position is assumed to be
the same as the index. The group tree is created if it does not exist yet.
Returns a pointer to the group if successful; NULL otherwise.
Side Effects: The variable tree is changed.
MtrNode *
Cudd_MakeZddTreeNode(
DdManager * dd, manager
unsigned int low, index of the first group variable
unsigned int size, number of variables in the group
unsigned int type MTR_DEFAULT or MTR_FIXED
)
Creates a new ZDD variable group. The group starts at variable and contains
size variables. The parameter low is the index of the first variable. If the
variable already exists, its current position in the order is known to the
manager. If the variable does not exist yet, the position is assumed to be
the same as the index. The group tree is created if it does not exist yet.
Returns a pointer to the group if successful; NULL otherwise.
Side Effects: The ZDD variable tree is changed.
int
Cudd_MinHammingDist(
DdManager * dd, DD manager
DdNode * f, function to examine
int * minterm, reference minterm
int upperBound distance above which an approximate
answer is OK
)
Returns the minimum Hamming distance between the minterms of a function f
and a reference minterm. The function is given as a BDD; the minterm is
given as an array of integers, one for each variable in the manager. Returns
the minimum distance if it is less than the upper bound; the upper bound if
the minimum distance is at least as large; CUDD_OUT_OF_MEM in case of
failure.
Side Effects: None
DdApaNumber
Cudd_NewApaNumber(
int digits
)
Allocates memory for an arbitrary precision integer. Returns a pointer to
the allocated memory if successful; NULL otherwise.
Side Effects: None
int
Cudd_NextCube(
DdGen * gen,
int ** cube,
CUDD_VALUE_TYPE * value
)
Generates the next cube of a decision diagram onset, using generator gen.
Returns 0 if the enumeration is completed; 1 otherwise.
Side Effects: The cube and its value are returned as side effects. The
generator is modified.
int
Cudd_NextNode(
DdGen * gen,
DdNode ** node
)
Finds the node of a decision diagram, using generator gen. Returns 0 if the
enumeration is completed; 1 otherwise.
Side Effects: The next node is returned as a side effect.
int
Cudd_NextPrime(
DdGen * gen,
int ** cube
)
Generates the next cube of a Boolean function, using generator gen. Returns
0 if the enumeration is completed; 1 otherwise.
Side Effects: The cube and is returned as side effects. The generator is
modified.
unsigned int
Cudd_NodeReadIndex(
DdNode * node
)
Returns the index of the node. The node pointer can be either regular or
complemented.
Side Effects: None
Cudd_NotCond(
node,
c
)
Complements a DD if condition c is true; c should be either 0 or 1, because
it is used directly (for efficiency). If in doubt on the values c may take,
use "(c) ? Cudd_Not(node) : node".
Side Effects: none
Cudd_Not(
node
)
Complements a DD by flipping the complement attribute of the pointer (the
least significant bit).
Side Effects: none
void
Cudd_OutOfMem(
long size size of the allocation that failed
)
Warns that a memory allocation failed. This function can be used as
replacement of MMout_of_memory to prevent the safe_mem functions of the util
package from exiting when malloc returns NULL. One possible use is in case
of discretionary allocations; for instance, the allocation of memory to
enlarge the computed table.
Side Effects: None
DdNode *
Cudd_OverApprox(
DdManager * dd, manager
DdNode * f, function to be superset
int numVars, number of variables in the support of f
int threshold, when to stop approximation
int safe, enforce safe approximation
double quality minimum improvement for accepted changes
)
Extracts a dense superset from a BDD. The procedure is identical to the
underapproximation procedure except for the fact that it works on the
complement of the given function. Extracting the subset of the complement
function is equivalent to extracting the superset of the function. Returns a
pointer to the BDD of the superset if successful. NULL if intermediate
result causes the procedure to run out of memory. The parameter numVars is
the maximum number of variables to be used in minterm calculation. The
optimal number should be as close as possible to the size of the support of
f. However, it is safe to pass the value returned by Cudd_ReadSize for
numVars when the number of variables is under 1023. If numVars is larger
than 1023, it will overflow. If a 0 parameter is passed then the procedure
will compute a value which will avoid overflow but will cause underflow with
2046 variables or more.
Side Effects: None
unsigned int
Cudd_Prime(
unsigned int p
)
Returns the next prime >= p.
Side Effects: None
int
Cudd_PrintDebug(
DdManager * dd,
DdNode * f,
int n,
int pr
)
Prints to the standard output a DD and its statistics. The statistics
include the number of nodes, the number of leaves, and the number of
minterms. (The number of minterms is the number of assignments to the
variables that cause the function to be different from the logical zero (for
BDDs) and from the background value (for ADDs.) The statistics are printed
if pr > 0. Specifically: pr = 0 : prints nothing pr = 1 :
prints counts of nodes and minterms pr = 2 : prints counts + disjoint
sum of product pr = 3 : prints counts + list of nodes pr > 3 :
prints counts + disjoint sum of product + list of nodes For the
purpose of counting the number of minterms, the function is supposed to
depend on n variables. Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_PrintInfo(
DdManager * dd,
FILE * fp
)
Prints out statistics and settings for a CUDD manager. Returns 1 if
successful; 0 otherwise.
Side Effects: None
int
Cudd_PrintLinear(
DdManager * table
)
Prints the linear transform matrix. Returns 1 in case of success; 0
otherwise.
Side Effects: none
int
Cudd_PrintMinterm(
DdManager * manager,
DdNode * node
)
Prints a disjoint sum of product cover for the function rooted at node. Each
product corresponds to a path from node to a leaf node different from the
logical zero, and different from the background value. Uses the package
default output file. Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_PrintTwoLiteralClauses(
DdManager * dd,
DdNode * f,
char ** names,
FILE * fp
)
Prints the one- and two-literal clauses. Returns 1 if successful; 0
otherwise. The argument "names" can be NULL, in which case the variable
indices are printed.
Side Effects: None
void
Cudd_PrintVersion(
FILE * fp
)
Prints the package version number.
Side Effects: None
DdNode *
Cudd_PrioritySelect(
DdManager * dd, manager
DdNode * R, BDD of the relation
DdNode ** x, array of x variables
DdNode ** y, array of y variables
DdNode ** z, array of z variables (optional: may be
NULL)
DdNode * Pi, BDD of the priority function (optional:
may be NULL)
int n, size of x, y, and z
DD_PRFP Pifunc function used to build Pi if it is NULL
)
Selects pairs from a relation R(x,y) (given as a BDD) in such a way that a
given x appears in one pair only. Uses a priority function to determine
which y should be paired to a given x. Cudd_PrioritySelect returns a pointer
to the selected function if successful; NULL otherwise. Three of the
arguments--x, y, and z--are vectors of BDD variables. The first two are the
variables on which R depends. The third vectore is a vector of auxiliary
variables, used during the computation. This vector is optional. If a NULL
value is passed instead, Cudd_PrioritySelect will create the working
variables on the fly. The sizes of x and y (and z if it is not NULL) should
equal n. The priority function Pi can be passed as a BDD, or can be built by
Cudd_PrioritySelect. If NULL is passed instead of a DdNode *, parameter
Pifunc is used by Cudd_PrioritySelect to build a BDD for the priority
function. (Pifunc is a pointer to a C function.) If Pi is not NULL, then
Pifunc is ignored. Pifunc should have the same interface as the standard
priority functions (e.g., Cudd_Dxygtdxz). Cudd_PrioritySelect and
Cudd_CProjection can sometimes be used interchangeably. Specifically,
calling Cudd_PrioritySelect with Cudd_Xgty as Pifunc produces the same
result as calling Cudd_CProjection with the all-zero minterm as reference
minterm. However, depending on the application, one or the other may be
preferable: When extracting representatives from an equivalence
relation, Cudd_CProjection has the advantage of nor requiring the auxiliary
variables. When computing matchings in general bipartite graphs,
Cudd_PrioritySelect normally obtains better results because it can use more
powerful matching schemes (e.g., Cudd_Dxygtdxz).
Side Effects: If called with z == NULL, will create new variables in the
manager.
void
Cudd_Quit(
DdManager * unique
)
Deletes resources associated with a DD manager and resets the global
statistical counters. (Otherwise, another manaqger subsequently created
would inherit the stats of this one.)
Side Effects: None
long
Cudd_Random(
)
Portable number generator based on ran2 from "Numerical Recipes in C." It is
a long period (> 2 * 10^18) random number generator of L'Ecuyer with Bays-
Durham shuffle. Returns a long integer uniformly distributed between 0 and
2147483561 (inclusive of the endpoint values). The random generator can be
explicitly initialized by calling Cudd_Srandom. If no explicit
initialization is performed, then the seed 1 is assumed.
Side Effects: None
int
Cudd_ReadArcviolation(
DdManager * dd
)
Returns the current value of the arcviolation parameter. This parameter is
used in group sifting to decide how many arcs into y not coming
from x are tolerable when checking for aggregation due to
extended symmetry. The value should be between 0 and 100. A small value
causes fewer variables to be aggregated. The default value is 0.
Side Effects: None
DdNode *
Cudd_ReadBackground(
DdManager * dd
)
Reads the background constant of the manager.
Side Effects: None
double
Cudd_ReadCacheHits(
DdManager * dd
)
Returns the number of cache hits.
Side Effects: None
double
Cudd_ReadCacheLookUps(
DdManager * dd
)
Returns the number of cache look-ups.
Side Effects: None
unsigned int
Cudd_ReadCacheSlots(
DdManager * dd
)
Reads the number of slots in the cache.
Side Effects: None
double
Cudd_ReadCacheUsedSlots(
DdManager * dd
)
Reads the fraction of used slots in the cache. The unused slots are those in
which no valid data is stored. Garbage collection, variable reordering, and
cache resizing may cause used slots to become unused.
Side Effects: None
unsigned int
Cudd_ReadDead(
DdManager * dd
)
Returns the number of dead nodes in the unique table.
Side Effects: None
CUDD_VALUE_TYPE
Cudd_ReadEpsilon(
DdManager * dd
)
Reads the epsilon parameter of the manager. The epsilon parameter control
the comparison between floating point numbers.
Side Effects: None
Cudd_ErrorType
Cudd_ReadErrorCode(
DdManager * dd
)
Returns the code of the last error. The error codes are defined in cudd.h.
Side Effects: None
long
Cudd_ReadGarbageCollectionTime(
DdManager * dd
)
Returns the number of milliseconds spent doing garbage collection since the
manager was initialized.
Side Effects: None
int
Cudd_ReadGarbageCollections(
DdManager * dd
)
Returns the number of times garbage collection has occurred in the manager.
The number includes both the calls from reordering procedures and those
caused by requests to create new nodes.
Side Effects: None
Cudd_AggregationType
Cudd_ReadGroupcheck(
DdManager * dd
)
Reads the groupcheck parameter of the manager. The groupcheck parameter
determines the aggregation criterion in group sifting.
Side Effects: None
Cudd_ReadIndex(
dd,
index
)
Returns the current position in the order of variable index. This macro is
obsolete and is kept for compatibility. New applications should use
Cudd_ReadPerm instead.
Side Effects: none
int
Cudd_ReadInvPermZdd(
DdManager * dd,
int i
)
Returns the index of the ZDD variable currently in the i-th position of the
order. If the index is CUDD_CONST_INDEX, returns CUDD_CONST_INDEX;
otherwise, if the index is out of bounds returns -1.
Side Effects: None
int
Cudd_ReadInvPerm(
DdManager * dd,
int i
)
Returns the index of the variable currently in the i-th position of the
order. If the index is CUDD_CONST_INDEX, returns CUDD_CONST_INDEX;
otherwise, if the index is out of bounds returns -1.
Side Effects: None
int
Cudd_ReadIthClause(
DdTlcInfo * tlc,
int i,
DdHalfWord * var1,
DdHalfWord * var2,
int * phase1,
int * phase2
)
Accesses the i-th clause of a DD given the clause set which must be already
computed. Returns 1 if successful; 0 if i is out of range, or in case of
error.
Side Effects: the four components of a clause are returned as side effects.
unsigned int
Cudd_ReadKeys(
DdManager * dd
)
Returns the total number of nodes currently in the unique table, including
the dead nodes.
Side Effects: None
int
Cudd_ReadLinear(
DdManager * table, CUDD manager
int x, row index
int y column index
)
Reads an entry of the linear transform matrix.
Side Effects: none
DdNode *
Cudd_ReadLogicZero(
DdManager * dd
)
Returns the zero constant of the manager. The logic zero constant is the
complement of the one constant, and is distinct from the arithmetic zero.
Side Effects: None
unsigned int
Cudd_ReadLooseUpTo(
DdManager * dd
)
Reads the looseUpTo parameter of the manager.
Side Effects: None
unsigned int
Cudd_ReadMaxCacheHard(
DdManager * dd
)
Reads the maxCacheHard parameter of the manager.
Side Effects: None
unsigned int
Cudd_ReadMaxCache(
DdManager * dd
)
Returns the soft limit for the cache size. The soft limit
Side Effects: None
double
Cudd_ReadMaxGrowthAlternate(
DdManager * dd
)
Reads the maxGrowthAlt parameter of the manager. This parameter is analogous
to the maxGrowth paramter, and is used every given number of reorderings
instead of maxGrowth. The number of reorderings is set with
Cudd_SetReorderingCycle. If the number of reorderings is 0 (default)
maxGrowthAlt is never used.
Side Effects: None
double
Cudd_ReadMaxGrowth(
DdManager * dd
)
Reads the maxGrowth parameter of the manager. This parameter determines how
much the number of nodes can grow during sifting of a variable. Overall,
sifting never increases the size of the decision diagrams. This parameter
only refers to intermediate results. A lower value will speed up sifting,
possibly at the expense of quality.
Side Effects: None
unsigned int
Cudd_ReadMaxLive(
DdManager * dd
)
Reads the maximum allowed number of live nodes. When this number is
exceeded, the package returns NULL.
Side Effects: none
unsigned long
Cudd_ReadMaxMemory(
DdManager * dd
)
Reads the maximum allowed memory. When this number is exceeded, the package
returns NULL.
Side Effects: none
unsigned long
Cudd_ReadMemoryInUse(
DdManager * dd
)
Returns the memory in use by the manager measured in bytes.
Side Effects: None
unsigned int
Cudd_ReadMinDead(
DdManager * dd
)
Reads the minDead parameter of the manager. The minDead parameter is used by
the package to decide whether to collect garbage or resize a subtable of the
unique table when the subtable becomes too full. The application can
indirectly control the value of minDead by setting the looseUpTo parameter.
Side Effects: None
unsigned int
Cudd_ReadMinHit(
DdManager * dd
)
Reads the hit rate that causes resizinig of the computed table.
Side Effects: None
DdNode *
Cudd_ReadMinusInfinity(
DdManager * dd
)
Reads the minus-infinity constant from the manager.
Side Effects: None
unsigned int
Cudd_ReadNextReordering(
DdManager * dd
)
Returns the threshold for the next dynamic reordering. The threshold is in
terms of number of nodes and is in effect only if reordering is enabled. The
count does not include the dead nodes, unless the countDead parameter of the
manager has been changed from its default setting.
Side Effects: None
long
Cudd_ReadNodeCount(
DdManager * dd
)
Reports the number of live nodes in BDDs and ADDs. This number does not
include the isolated projection functions and the unused constants. These
nodes that are not counted are not part of the DDs manipulated by the
application.
Side Effects: None
double
Cudd_ReadNodesDropped(
DdManager * dd
)
Returns the number of nodes killed by dereferencing if the keeping of this
statistic is enabled; -1 otherwise. This statistic is enabled only if the
package is compiled with DD_STATS defined.
Side Effects: None
double
Cudd_ReadNodesFreed(
DdManager * dd
)
Returns the number of nodes returned to the free list if the keeping of this
statistic is enabled; -1 otherwise. This statistic is enabled only if the
package is compiled with DD_STATS defined.
Side Effects: None
int
Cudd_ReadNumberXovers(
DdManager * dd
)
Reads the current number of crossovers used by the genetic algorithm for
variable reordering. A larger number of crossovers will cause the genetic
algorithm to take more time, but will generally produce better results. The
default value is 0, in which case the package uses three times the number of
variables as number of crossovers, with a maximum of 60.
Side Effects: None
DdNode *
Cudd_ReadOne(
DdManager * dd
)
Returns the one constant of the manager. The one constant is common to ADDs
and BDDs.
Side Effects: None
int
Cudd_ReadPeakLiveNodeCount(
DdManager * dd
)
Reports the peak number of live nodes. This count is kept only if CUDD is
compiled with DD_STATS defined. If DD_STATS is not defined, this function
returns -1.
Side Effects: None
long
Cudd_ReadPeakNodeCount(
DdManager * dd
)
Reports the peak number of nodes. This number includes node on the free
list. At the peak, the number of nodes on the free list is guaranteed to be
less than DD_MEM_CHUNK.
Side Effects: None
int
Cudd_ReadPermZdd(
DdManager * dd,
int i
)
Returns the current position of the i-th ZDD variable in the order. If the
index is CUDD_CONST_INDEX, returns CUDD_CONST_INDEX; otherwise, if the index
is out of bounds returns -1.
Side Effects: None
int
Cudd_ReadPerm(
DdManager * dd,
int i
)
Returns the current position of the i-th variable in the order. If the index
is CUDD_CONST_INDEX, returns CUDD_CONST_INDEX; otherwise, if the index is
out of bounds returns -1.
Side Effects: None
DdNode *
Cudd_ReadPlusInfinity(
DdManager * dd
)
Reads the plus-infinity constant from the manager.
Side Effects: None
int
Cudd_ReadPopulationSize(
DdManager * dd
)
Reads the current size of the population used by the genetic algorithm for
variable reordering. A larger population size will cause the genetic
algorithm to take more time, but will generally produce better results. The
default value is 0, in which case the package uses three times the number of
variables as population size, with a maximum of 120.
Side Effects: None
int
Cudd_ReadRecomb(
DdManager * dd
)
Returns the current value of the recombination parameter used in group
sifting. A larger (positive) value makes the aggregation of variables due to
the second difference criterion more likely. A smaller (negative) value
makes aggregation less likely.
Side Effects: None
double
Cudd_ReadRecursiveCalls(
DdManager * dd
)
Returns the number of recursive calls if the package is compiled with
DD_COUNT defined.
Side Effects: None
int
Cudd_ReadReorderingCycle(
DdManager * dd
)
Reads the reordCycle parameter of the manager. This parameter determines how
often the alternate threshold on maximum growth is used in reordering.
Side Effects: None
long
Cudd_ReadReorderingTime(
DdManager * dd
)
Returns the number of milliseconds spent reordering variables since the
manager was initialized. The time spent in collecting garbage before
reordering is included.
Side Effects: None
int
Cudd_ReadReorderings(
DdManager * dd
)
Returns the number of times reordering has occurred in the manager. The
number includes both the calls to Cudd_ReduceHeap from the application
program and those automatically performed by the package. However, calls
that do not even initiate reordering are not counted. A call may not
initiate reordering if there are fewer than minsize live nodes in the
manager, or if CUDD_REORDER_NONE is specified as reordering method. The
calls to Cudd_ShuffleHeap are not counted.
Side Effects: None
int
Cudd_ReadSiftMaxSwap(
DdManager * dd
)
Reads the siftMaxSwap parameter of the manager. This parameter gives the
maximum number of swaps that will be attempted for each invocation of
sifting. The real number of swaps may exceed the set limit because the
package will always complete the sifting of the variable that causes the
limit to be reached.
Side Effects: None
int
Cudd_ReadSiftMaxVar(
DdManager * dd
)
Reads the siftMaxVar parameter of the manager. This parameter gives the
maximum number of variables that will be sifted for each invocation of
sifting.
Side Effects: None
int
Cudd_ReadSize(
DdManager * dd
)
Returns the number of BDD variables in existance.
Side Effects: None
unsigned int
Cudd_ReadSlots(
DdManager * dd
)
Returns the total number of slots of the unique table. This number ismainly
for diagnostic purposes.
Side Effects: None
FILE *
Cudd_ReadStderr(
DdManager * dd
)
Reads the stderr of a manager. This is the file pointer to which messages
normally going to stderr are written. It is initialized to stderr.
Cudd_SetStderr allows the application to redirect it.
Side Effects: None
FILE *
Cudd_ReadStdout(
DdManager * dd
)
Reads the stdout of a manager. This is the file pointer to which messages
normally going to stdout are written. It is initialized to stdout.
Cudd_SetStdout allows the application to redirect it.
Side Effects: None
double
Cudd_ReadSwapSteps(
DdManager * dd
)
Reads the number of elementary reordering steps.
Side Effects: none
int
Cudd_ReadSymmviolation(
DdManager * dd
)
Returns the current value of the symmviolation parameter. This parameter is
used in group sifting to decide how many violations to the symmetry
conditions f10 = f01 or f11 = f00 are tolerable
when checking for aggregation due to extended symmetry. The value should be
between 0 and 100. A small value causes fewer variables to be aggregated.
The default value is 0.
Side Effects: None
MtrNode *
Cudd_ReadTree(
DdManager * dd
)
Returns the variable group tree of the manager.
Side Effects: None
double
Cudd_ReadUniqueLinks(
DdManager * dd
)
Returns the number of links followed during look-ups in the unique table if
the keeping of this statistic is enabled; -1 otherwise. If an item is found
in the first position of its collision list, the number of links followed is
taken to be 0. If it is in second position, the number of links is 1, and so
on. This statistic is enabled only if the package is compiled with
DD_UNIQUE_PROFILE defined.
Side Effects: None
double
Cudd_ReadUniqueLookUps(
DdManager * dd
)
Returns the number of look-ups in the unique table if the keeping of this
statistic is enabled; -1 otherwise. This statistic is enabled only if the
package is compiled with DD_UNIQUE_PROFILE defined.
Side Effects: None
double
Cudd_ReadUsedSlots(
DdManager * dd
)
Reads the fraction of used slots in the unique table. The unused slots are
those in which no valid data is stored. Garbage collection, variable
reordering, and subtable resizing may cause used slots to become unused.
Side Effects: None
DdNode *
Cudd_ReadVars(
DdManager * dd,
int i
)
Returns the i-th element of the vars array if it falls within the array
bounds; NULL otherwise. If i is the index of an existing variable, this
function produces the same result as Cudd_bddIthVar. However, if the i-th
var does not exist yet, Cudd_bddIthVar will create it, whereas Cudd_ReadVars
will not.
Side Effects: None
DdNode *
Cudd_ReadZddOne(
DdManager * dd,
int i
)
Returns the ZDD for the constant 1 function. The representation of the
constant 1 function as a ZDD depends on how many variables it (nominally)
depends on. The index of the topmost variable in the support is given as
argument i.
Side Effects: None
int
Cudd_ReadZddSize(
DdManager * dd
)
Returns the number of ZDD variables in existance.
Side Effects: None
MtrNode *
Cudd_ReadZddTree(
DdManager * dd
)
Returns the variable group tree of the manager.
Side Effects: None
DdNode *
Cudd_ReadZero(
DdManager * dd
)
Returns the zero constant of the manager. The zero constant is the
arithmetic zero, rather than the logic zero. The latter is the complement of
the one constant.
Side Effects: None
void
Cudd_RecursiveDerefZdd(
DdManager * table,
DdNode * n
)
Decreases the reference count of ZDD node n. If n dies, recursively
decreases the reference counts of its children. It is used to dispose of a
ZDD that is no longer needed.
Side Effects: None
void
Cudd_RecursiveDeref(
DdManager * table,
DdNode * n
)
Decreases the reference count of node n. If n dies, recursively decreases
the reference counts of its children. It is used to dispose of a DD that is
no longer needed.
Side Effects: None
int
Cudd_ReduceHeap(
DdManager * table, DD manager
Cudd_ReorderingTy heuristic, method used for reordering
int minsize bound below which no reordering occurs
)
Main dynamic reordering routine. Calls one of the possible reordering
procedures: Swapping Sifting Symmetric Sifting Group
Sifting Window Permutation Simulated Annealing Genetic Algorithm
Dynamic Programming (exact) For sifting, symmetric sifting, group
sifting, and window permutation it is possible to request reordering to
convergence. The core of all methods is the reordering procedure
cuddSwapInPlace() which swaps two adjacent variables and is based on
Rudell's paper. Returns 1 in case of success; 0 otherwise. In the case of
symmetric sifting (with and without convergence) returns 1 plus the number
of symmetric variables, in case of success.
Side Effects: Changes the variable order for all diagrams and clears the
cache.
void
Cudd_Ref(
DdNode * n
)
Increases the reference count of a node, if it is not saturated.
Side Effects: None
Cudd_Regular(
node
)
Returns the regular version of a pointer.
Side Effects: none
DdNode *
Cudd_RemapOverApprox(
DdManager * dd, manager
DdNode * f, function to be superset
int numVars, number of variables in the support of f
int threshold, when to stop approximation
double quality minimum improvement for accepted changes
)
Extracts a dense superset from a BDD. The procedure is identical to the
underapproximation procedure except for the fact that it works on the
complement of the given function. Extracting the subset of the complement
function is equivalent to extracting the superset of the function. Returns a
pointer to the BDD of the superset if successful. NULL if intermediate
result causes the procedure to run out of memory. The parameter numVars is
the maximum number of variables to be used in minterm calculation. The
optimal number should be as close as possible to the size of the support of
f. However, it is safe to pass the value returned by Cudd_ReadSize for
numVars when the number of variables is under 1023. If numVars is larger
than 1023, it will overflow. If a 0 parameter is passed then the procedure
will compute a value which will avoid overflow but will cause underflow with
2046 variables or more.
Side Effects: None
DdNode *
Cudd_RemapUnderApprox(
DdManager * dd, manager
DdNode * f, function to be subset
int numVars, number of variables in the support of f
int threshold, when to stop approximation
double quality minimum improvement for accepted changes
)
Extracts a dense subset from a BDD. This procedure uses a remapping
technique and density as the cost function. Returns a pointer to the BDD of
the subset if successful. NULL if the procedure runs out of memory. The
parameter numVars is the maximum number of variables to be used in minterm
calculation. The optimal number should be as close as possible to the size
of the support of f. However, it is safe to pass the value returned by
Cudd_ReadSize for numVars when the number of variables is under 1023. If
numVars is larger than 1023, it will cause overflow. If a 0 parameter is
passed then the procedure will compute a value which will avoid overflow but
will cause underflow with 2046 variables or more.
Side Effects: None
int
Cudd_RemoveHook(
DdManager * dd,
DD_HFP f,
Cudd_HookType where
)
Removes a function from a hook. A hook is a list of application-provided
functions called on certain occasions by the package. Returns 1 if
successful; 0 the function was not in the list.
Side Effects: None
int
Cudd_ReorderingReporting(
DdManager * dd
)
Returns 1 if reporting of reordering stats is enabled; 0 otherwise.
Side Effects: none
int
Cudd_ReorderingStatusZdd(
DdManager * unique,
Cudd_ReorderingTy method
)
Reports the status of automatic dynamic reordering of ZDDs. Parameter method
is set to the ZDD reordering method currently selected. Returns 1 if
automatic reordering is enabled; 0 otherwise.
Side Effects: Parameter method is set to the ZDD reordering method currently
selected.
int
Cudd_ReorderingStatus(
DdManager * unique,
Cudd_ReorderingTy method
)
Reports the status of automatic dynamic reordering of BDDs and ADDs.
Parameter method is set to the reordering method currently selected. Returns
1 if automatic reordering is enabled; 0 otherwise.
Side Effects: Parameter method is set to the reordering method currently
selected.
void
Cudd_SetArcviolation(
DdManager * dd,
int arcviolation
)
Sets the value of the arcviolation parameter. This parameter is used in
group sifting to decide how many arcs into y not coming from
x are tolerable when checking for aggregation due to extended
symmetry. The value should be between 0 and 100. A small value causes fewer
variables to be aggregated. The default value is 0.
Side Effects: None
void
Cudd_SetBackground(
DdManager * dd,
DdNode * bck
)
Sets the background constant of the manager. It assumes that the DdNode
pointer bck is already referenced.
Side Effects: None
void
Cudd_SetEpsilon(
DdManager * dd,
CUDD_VALUE_TYPE ep
)
Sets the epsilon parameter of the manager to ep. The epsilon parameter
control the comparison between floating point numbers.
Side Effects: None
void
Cudd_SetGroupcheck(
DdManager * dd,
Cudd_AggregationT gc
)
Sets the parameter groupcheck of the manager to gc. The groupcheck parameter
determines the aggregation criterion in group sifting.
Side Effects: None
void
Cudd_SetLooseUpTo(
DdManager * dd,
unsigned int lut
)
Sets the looseUpTo parameter of the manager. This parameter of the manager
controls the threshold beyond which no fast growth of the unique table is
allowed. The threshold is given as a number of slots. If the value passed to
this function is 0, the function determines a suitable value based on the
available memory.
Side Effects: None
void
Cudd_SetMaxCacheHard(
DdManager * dd,
unsigned int mc
)
Sets the maxCacheHard parameter of the manager. The cache cannot grow larger
than maxCacheHard entries. This parameter allows an application to control
the trade-off of memory versus speed. If the value passed to this function
is 0, the function determines a suitable maximum cache size based on the
available memory.
Side Effects: None
void
Cudd_SetMaxGrowthAlternate(
DdManager * dd,
double mg
)
Sets the maxGrowthAlt parameter of the manager. This parameter is analogous
to the maxGrowth paramter, and is used every given number of reorderings
instead of maxGrowth. The number of reorderings is set with
Cudd_SetReorderingCycle. If the number of reorderings is 0 (default)
maxGrowthAlt is never used.
Side Effects: None
void
Cudd_SetMaxGrowth(
DdManager * dd,
double mg
)
Sets the maxGrowth parameter of the manager. This parameter determines how
much the number of nodes can grow during sifting of a variable. Overall,
sifting never increases the size of the decision diagrams. This parameter
only refers to intermediate results. A lower value will speed up sifting,
possibly at the expense of quality.
Side Effects: None
void
Cudd_SetMaxLive(
DdManager * dd,
unsigned int maxLive
)
Sets the maximum allowed number of live nodes. When this number is exceeded,
the package returns NULL.
Side Effects: none
void
Cudd_SetMaxMemory(
DdManager * dd,
unsigned long maxMemory
)
Sets the maximum allowed memory. When this number is exceeded, the package
returns NULL.
Side Effects: none
void
Cudd_SetMinHit(
DdManager * dd,
unsigned int hr
)
Sets the minHit parameter of the manager. This parameter controls the
resizing of the computed table. If the hit rate is larger than the specified
value, and the cache is not already too large, then its size is doubled.
Side Effects: None
void
Cudd_SetNextReordering(
DdManager * dd,
unsigned int next
)
Sets the threshold for the next dynamic reordering. The threshold is in
terms of number of nodes and is in effect only if reordering is enabled. The
count does not include the dead nodes, unless the countDead parameter of the
manager has been changed from its default setting.
Side Effects: None
void
Cudd_SetNumberXovers(
DdManager * dd,
int numberXovers
)
Sets the number of crossovers used by the genetic algorithm for variable
reordering. A larger number of crossovers will cause the genetic algorithm
to take more time, but will generally produce better results. The default
value is 0, in which case the package uses three times the number of
variables as number of crossovers, with a maximum of 60.
Side Effects: None
void
Cudd_SetPopulationSize(
DdManager * dd,
int populationSize
)
Sets the size of the population used by the genetic algorithm for variable
reordering. A larger population size will cause the genetic algorithm to
take more time, but will generally produce better results. The default value
is 0, in which case the package uses three times the number of variables as
population size, with a maximum of 120.
Side Effects: Changes the manager.
void
Cudd_SetRecomb(
DdManager * dd,
int recomb
)
Sets the value of the recombination parameter used in group sifting. A
larger (positive) value makes the aggregation of variables due to the second
difference criterion more likely. A smaller (negative) value makes
aggregation less likely. The default value is 0.
Side Effects: Changes the manager.
void
Cudd_SetReorderingCycle(
DdManager * dd,
int cycle
)
Sets the reordCycle parameter of the manager. This parameter determines how
often the alternate threshold on maximum growth is used in reordering.
Side Effects: None
void
Cudd_SetSiftMaxSwap(
DdManager * dd,
int sms
)
Sets the siftMaxSwap parameter of the manager. This parameter gives the
maximum number of swaps that will be attempted for each invocation of
sifting. The real number of swaps may exceed the set limit because the
package will always complete the sifting of the variable that causes the
limit to be reached.
Side Effects: None
void
Cudd_SetSiftMaxVar(
DdManager * dd,
int smv
)
Sets the siftMaxVar parameter of the manager. This parameter gives the
maximum number of variables that will be sifted for each invocation of
sifting.
Side Effects: None
void
Cudd_SetStderr(
DdManager * dd,
FILE * fp
)
Sets the stderr of a manager.
Side Effects: None
void
Cudd_SetStdout(
DdManager * dd,
FILE * fp
)
Sets the stdout of a manager.
Side Effects: None
void
Cudd_SetSymmviolation(
DdManager * dd,
int symmviolation
)
Sets the value of the symmviolation parameter. This parameter is used in
group sifting to decide how many violations to the symmetry conditions
f10 = f01 or f11 = f00 are tolerable when checking
for aggregation due to extended symmetry. The value should be between 0 and
100. A small value causes fewer variables to be aggregated. The default
value is 0.
Side Effects: Changes the manager.
void
Cudd_SetTree(
DdManager * dd,
MtrNode * tree
)
Sets the variable group tree of the manager.
Side Effects: None
int
Cudd_SetVarMap(
DdManager * manager, DD manager
DdNode ** x, first array of variables
DdNode ** y, second array of variables
int n length of both arrays
)
Registers with the manager a variable mapping described by two sets of
variables. This variable mapping is then used by functions like
Cudd_bddVarMap. This function is convenient for those applications that
perform the same mapping several times. However, if several different
permutations are used, it may be more efficient not to rely on the
registered mapping, because changing mapping causes the cache to be cleared.
(The initial setting, however, does not clear the cache.) The two sets of
variables (x and y) must have the same size (x and y). The size is given by
n. The two sets of variables are normally disjoint, but this restriction is
not imposeded by the function. When new variables are created, the map is
automatically extended (each new variable maps to itself). The typical use,
however, is to wait until all variables are created, and then create the
map. Returns 1 if the mapping is successfully registered with the manager; 0
otherwise.
Side Effects: Modifies the manager. May clear the cache.
void
Cudd_SetZddTree(
DdManager * dd,
MtrNode * tree
)
Sets the ZDD variable group tree of the manager.
Side Effects: None
int
Cudd_SharingSize(
DdNode ** nodeArray,
int n
)
Counts the number of nodes in an array of DDs. Shared nodes are counted only
once. Returns the total number of nodes.
Side Effects: None
int
Cudd_ShortestLength(
DdManager * manager,
DdNode * f,
int * weight
)
Find the length of the shortest path(s) in a DD. f is the DD we want to get
the shortest path for; weight[i] is the weight of the THEN edge coming from
the node whose index is i. All ELSE edges have 0 weight. Returns the length
of the shortest path(s) if successful; CUDD_OUT_OF_MEM otherwise.
Side Effects: None
DdNode *
Cudd_ShortestPath(
DdManager * manager,
DdNode * f,
int * weight,
int * support,
int * length
)
Finds a shortest path in a DD. f is the DD we want to get the shortest path
for; weight[i] is the weight of the THEN arc coming from the node whose
index is i. If weight is NULL, then unit weights are assumed for all THEN
arcs. All ELSE arcs have 0 weight. If non-NULL, both weight and support
should point to arrays with at least as many entries as there are variables
in the manager. Returns the shortest path as the BDD of a cube.
Side Effects: support contains on return the true support of f. If support
is NULL on entry, then Cudd_ShortestPath does not compute the true support
info. length contains the length of the path.
int
Cudd_ShuffleHeap(
DdManager * table, DD manager
int * permutation required variable permutation
)
Reorders variables according to given permutation. The i-th entry of the
permutation array contains the index of the variable that should be brought
to the i-th level. The size of the array should be equal or greater to the
number of variables currently in use. Returns 1 in case of success; 0
otherwise.
Side Effects: Changes the variable order for all diagrams and clears the
cache.
DdNode *
Cudd_SolveEqn(
DdManager * bdd,
DdNode * F, the left-hand side of the equation
DdNode * Y, the cube of the y variables
DdNode ** G, the array of solutions (return parameter)
int ** yIndex, index of y variables
int n numbers of unknowns
)
Implements the solution for F(x,y) = 0. The return value is the consistency
condition. The y variables are the unknowns and the remaining variables are
the parameters. Returns the consistency condition if successful; NULL
otherwise. Cudd_SolveEqn allocates an array and fills it with the indices of
the unknowns. This array is used by Cudd_VerifySol.
Side Effects: The solution is returned in G; the indices of the y variables
are returned in yIndex.
DdNode *
Cudd_SplitSet(
DdManager * manager,
DdNode * S,
DdNode ** xVars,
int n,
double m
)
Returns m minterms from a BDD whose support has n
variables at most. The procedure tries to create as few extra nodes as
possible. The function represented by S depends on at most
n of the variables in xVars. Returns a BDD with
m minterms of the on-set of S if successful; NULL otherwise.
Side Effects: None
void
Cudd_Srandom(
long seed
)
Initializer for the portable number generator based on ran2 in "Numerical
Recipes in C." The input is the seed for the generator. If it is negative,
its absolute value is taken as seed. If it is 0, then 1 is taken as seed.
The initialized sets up the two recurrences used to generate a long-period
stream, and sets up the shuffle table.
Side Effects: None
int
Cudd_StdPostReordHook(
DdManager * dd,
const char * str,
void * data
)
Sample hook function to call after reordering. Prints on the manager's
stdout final size and reordering time. Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_StdPreReordHook(
DdManager * dd,
const char * str,
void * data
)
Sample hook function to call before reordering. Prints on the manager's
stdout reordering method and initial size. Returns 1 if successful; 0
otherwise.
Side Effects: None
DdNode *
Cudd_SubsetCompress(
DdManager * dd, manager
DdNode * f, BDD whose subset is sought
int nvars, number of variables in the support of f
int threshold maximum number of nodes in the subset
)
Finds a dense subset of BDD f. Density is the ratio of number
of minterms to number of nodes. Uses several techniques in series. It is
more expensive than other subsetting procedures, but often produces better
results. See Cudd_SubsetShortPaths for a description of the threshold and
nvars parameters. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_SubsetHeavyBranch(
DdManager * dd, manager
DdNode * f, function to be subset
int numVars, number of variables in the support of f
int threshold maximum number of nodes in the subset
)
Extracts a dense subset from a BDD. This procedure builds a subset by
throwing away one of the children of each node, starting from the root,
until the result is small enough. The child that is eliminated from the
result is the one that contributes the fewer minterms. Returns a pointer to
the BDD of the subset if successful. NULL if the procedure runs out of
memory. The parameter numVars is the maximum number of variables to be used
in minterm calculation and node count calculation. The optimal number should
be as close as possible to the size of the support of f. However, it is safe
to pass the value returned by Cudd_ReadSize for numVars when the number of
variables is under 1023. If numVars is larger than 1023, it will overflow.
If a 0 parameter is passed then the procedure will compute a value which
will avoid overflow but will cause underflow with 2046 variables or more.
Side Effects: None
DdNode *
Cudd_SubsetShortPaths(
DdManager * dd, manager
DdNode * f, function to be subset
int numVars, number of variables in the support of f
int threshold, maximum number of nodes in the subset
int hardlimit flag: 1 if threshold is a hard limit
)
Extracts a dense subset from a BDD. This procedure tries to preserve the
shortest paths of the input BDD, because they give many minterms and
contribute few nodes. This procedure may increase the number of nodes in
trying to create the subset or reduce the number of nodes due to
recombination as compared to the original BDD. Hence the threshold may not
be strictly adhered to. In practice, recombination overshadows the increase
in the number of nodes and results in small BDDs as compared to the
threshold. The hardlimit specifies whether threshold needs to be strictly
adhered to. If it is set to 1, the procedure ensures that result is never
larger than the specified limit but may be considerably less than the
threshold. Returns a pointer to the BDD for the subset if successful; NULL
otherwise. The value for numVars should be as close as possible to the size
of the support of f for better efficiency. However, it is safe to pass the
value returned by Cudd_ReadSize for numVars. If 0 is passed, then the value
returned by Cudd_ReadSize is used.
Side Effects: None
DdNode *
Cudd_SubsetWithMaskVars(
DdManager * dd, manager
DdNode * f, function from which to pick a cube
DdNode ** vars, array of variables
int nvars, size of vars
DdNode ** maskVars, array of variables
int mvars size of maskVars
)
Extracts a subset from a BDD in the following procedure. 1. Compute the
weight for each mask variable by counting the number of minterms for both
positive and negative cofactors of the BDD with respect to each mask
variable. (weight = #positive - #negative) 2. Find a representative cube of
the BDD by using the weight. From the top variable of the BDD, for each
variable, if the weight is greater than 0.0, choose THEN branch, othereise
ELSE branch, until meeting the constant 1. 3. Quantify out the variables not
in maskVars from the representative cube and if a variable in maskVars is
don't care, replace the variable with a constant(1 or 0) depending on the
weight. 4. Make a subset of the BDD by multiplying with the modified cube.
Side Effects: None
DdNode *
Cudd_SupersetCompress(
DdManager * dd, manager
DdNode * f, BDD whose superset is sought
int nvars, number of variables in the support of f
int threshold maximum number of nodes in the superset
)
Finds a dense superset of BDD f. Density is the ratio of number
of minterms to number of nodes. Uses several techniques in series. It is
more expensive than other supersetting procedures, but often produces better
results. See Cudd_SupersetShortPaths for a description of the threshold and
nvars parameters. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_SupersetHeavyBranch(
DdManager * dd, manager
DdNode * f, function to be superset
int numVars, number of variables in the support of f
int threshold maximum number of nodes in the superset
)
Extracts a dense superset from a BDD. The procedure is identical to the
subset procedure except for the fact that it receives the complement of the
given function. Extracting the subset of the complement function is
equivalent to extracting the superset of the function. This procedure builds
a superset by throwing away one of the children of each node starting from
the root of the complement function, until the result is small enough. The
child that is eliminated from the result is the one that contributes the
fewer minterms. Returns a pointer to the BDD of the superset if successful.
NULL if intermediate result causes the procedure to run out of memory. The
parameter numVars is the maximum number of variables to be used in minterm
calculation and node count calculation. The optimal number should be as
close as possible to the size of the support of f. However, it is safe to
pass the value returned by Cudd_ReadSize for numVars when the number of
variables is under 1023. If numVars is larger than 1023, it will overflow.
If a 0 parameter is passed then the procedure will compute a value which
will avoid overflow but will cause underflow with 2046 variables or more.
Side Effects: None
DdNode *
Cudd_SupersetShortPaths(
DdManager * dd, manager
DdNode * f, function to be superset
int numVars, number of variables in the support of f
int threshold, maximum number of nodes in the subset
int hardlimit flag: 1 if threshold is a hard limit
)
Extracts a dense superset from a BDD. The procedure is identical to the
subset procedure except for the fact that it receives the complement of the
given function. Extracting the subset of the complement function is
equivalent to extracting the superset of the function. This procedure tries
to preserve the shortest paths of the complement BDD, because they give many
minterms and contribute few nodes. This procedure may increase the number of
nodes in trying to create the superset or reduce the number of nodes due to
recombination as compared to the original BDD. Hence the threshold may not
be strictly adhered to. In practice, recombination overshadows the increase
in the number of nodes and results in small BDDs as compared to the
threshold. The hardlimit specifies whether threshold needs to be strictly
adhered to. If it is set to 1, the procedure ensures that result is never
larger than the specified limit but may be considerably less than the
threshold. Returns a pointer to the BDD for the superset if successful; NULL
otherwise. The value for numVars should be as close as possible to the size
of the support of f for better efficiency. However, it is safe to pass the
value returned by Cudd_ReadSize for numVar. If 0 is passed, then the value
returned by Cudd_ReadSize is used.
Side Effects: None
int *
Cudd_SupportIndex(
DdManager * dd, manager
DdNode * f DD whose support is sought
)
Finds the variables on which a DD depends. Returns an index array of the
variables if successful; NULL otherwise. The size of the array equals the
number of variables in the manager. Each entry of the array is 1 if the
corresponding variable is in the support of the DD and 0 otherwise.
Side Effects: None
int
Cudd_SupportSize(
DdManager * dd, manager
DdNode * f DD whose support size is sought
)
Counts the variables on which a DD depends. Returns the number of the
variables if successful; CUDD_OUT_OF_MEM otherwise.
Side Effects: None
DdNode *
Cudd_Support(
DdManager * dd, manager
DdNode * f DD whose support is sought
)
Finds the variables on which a DD depends. Returns a BDD consisting of the
product of the variables if successful; NULL otherwise.
Side Effects: None
void
Cudd_SymmProfile(
DdManager * table,
int lower,
int upper
)
Prints statistics on symmetric variables.
Side Effects: None
void
Cudd_TurnOffCountDead(
DdManager * dd
)
Causes the dead nodes not to be counted towards triggering reordering. This
causes less frequent reorderings. By default dead nodes are not counted.
Therefore there is no need to call this function unless Cudd_TurnOnCountDead
has been previously called.
Side Effects: Changes the manager.
void
Cudd_TurnOnCountDead(
DdManager * dd
)
Causes the dead nodes to be counted towards triggering reordering. This
causes more frequent reorderings. By default dead nodes are not counted.
Side Effects: Changes the manager.
Cudd_T(
node
)
Returns the then child of an internal node. If node is a
constant node, the result is unpredictable.
Side Effects: none
DdNode *
Cudd_UnderApprox(
DdManager * dd, manager
DdNode * f, function to be subset
int numVars, number of variables in the support of f
int threshold, when to stop approximation
int safe, enforce safe approximation
double quality minimum improvement for accepted changes
)
Extracts a dense subset from a BDD. This procedure uses a variant of Tom
Shiple's underapproximation method. The main difference from the original
method is that density is used as cost function. Returns a pointer to the
BDD of the subset if successful. NULL if the procedure runs out of memory.
The parameter numVars is the maximum number of variables to be used in
minterm calculation. The optimal number should be as close as possible to
the size of the support of f. However, it is safe to pass the value returned
by Cudd_ReadSize for numVars when the number of variables is under 1023. If
numVars is larger than 1023, it will cause overflow. If a 0 parameter is
passed then the procedure will compute a value which will avoid overflow but
will cause underflow with 2046 variables or more.
Side Effects: None
int *
Cudd_VectorSupportIndex(
DdManager * dd, manager
DdNode ** F, array of DDs whose support is sought
int n size of the array
)
Finds the variables on which a set of DDs depends. The set must contain
either BDDs and ADDs, or ZDDs. Returns an index array of the variables if
successful; NULL otherwise.
Side Effects: None
int
Cudd_VectorSupportSize(
DdManager * dd, manager
DdNode ** F, array of DDs whose support is sought
int n size of the array
)
Counts the variables on which a set of DDs depends. The set must contain
either BDDs and ADDs, or ZDDs. Returns the number of the variables if
successful; CUDD_OUT_OF_MEM otherwise.
Side Effects: None
DdNode *
Cudd_VectorSupport(
DdManager * dd, manager
DdNode ** F, array of DDs whose support is sought
int n size of the array
)
Finds the variables on which a set of DDs depends. The set must contain
either BDDs and ADDs, or ZDDs. Returns a BDD consisting of the product of
the variables if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_VerifySol(
DdManager * bdd,
DdNode * F, the left-hand side of the equation
DdNode ** G, the array of solutions
int * yIndex, index of y variables
int n numbers of unknowns
)
Checks the solution of F(x,y) = 0. This procedure substitutes the solution
components for the unknowns of F and returns the resulting BDD for F.
Side Effects: Frees the memory pointed by yIndex.
Cudd_V(
node
)
Returns the value of a constant node. If node is an internal
node, the result is unpredictable.
Side Effects: none
DdNode *
Cudd_Xeqy(
DdManager * dd, DD manager
int N, number of x and y variables
DdNode ** x, array of x variables
DdNode ** y array of y variables
)
This function generates a BDD for the function x==y. Both x and y are N-bit
numbers, x[0] x[1] ... x[N-1] and y[0] y[1] ... y[N-1], with 0 the most
significant bit. The BDD is built bottom-up. It has 3*N-1 internal nodes, if
the variables are ordered as follows: x[0] y[0] x[1] y[1] ... x[N-1] y[N-1].
Side Effects: None
DdNode *
Cudd_Xgty(
DdManager * dd, DD manager
int N, number of x and y variables
DdNode ** z, array of z variables: unused
DdNode ** x, array of x variables
DdNode ** y array of y variables
)
This function generates a BDD for the function x > y. Both x and y are N-
bit numbers, x[0] x[1] ... x[N-1] and y[0] y[1] ... y[N-1], with 0 the most
significant bit. The BDD is built bottom-up. It has 3*N-1 internal nodes, if
the variables are ordered as follows: x[0] y[0] x[1] y[1] ... x[N-1] y[N-1].
Argument z is not used by Cudd_Xgty: it is included to make it call-
compatible to Cudd_Dxygtdxz and Cudd_Dxygtdyz.
Side Effects: None
DdNode *
Cudd_addAgreement(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Returns NULL if not a terminal case; f op g otherwise, where f op g is f if
f==g; background if f!=g.
Side Effects: None
DdNode *
Cudd_addApply(
DdManager * dd,
DD_AOP op,
DdNode * f,
DdNode * g
)
Applies op to the corresponding discriminants of f and g. Returns a pointer
to the result if succssful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addBddInterval(
DdManager * dd,
DdNode * f,
CUDD_VALUE_TYPE lower,
CUDD_VALUE_TYPE upper
)
Converts an ADD to a BDD by replacing all discriminants greater than or
equal to lower and less than or equal to upper with 1, and all other
discriminants with 0. Returns a pointer to the resulting BDD if successful;
NULL otherwise.
Side Effects: None
DdNode *
Cudd_addBddIthBit(
DdManager * dd,
DdNode * f,
int bit
)
Converts an ADD to a BDD by replacing all discriminants whose i-th bit is
equal to 1 with 1, and all other discriminants with 0. The i-th bit refers
to the integer representation of the leaf value. If the value is has a
fractional part, it is ignored. Repeated calls to this procedure allow one
to transform an integer-valued ADD into an array of BDDs, one for each bit
of the leaf values. Returns a pointer to the resulting BDD if successful;
NULL otherwise.
Side Effects: None
DdNode *
Cudd_addBddPattern(
DdManager * dd,
DdNode * f
)
Converts an ADD to a BDD by replacing all discriminants different from 0
with 1. Returns a pointer to the resulting BDD if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_addBddStrictThreshold(
DdManager * dd,
DdNode * f,
CUDD_VALUE_TYPE value
)
Converts an ADD to a BDD by replacing all discriminants STRICTLY greater
than value with 1, and all other discriminants with 0. Returns a pointer to
the resulting BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addBddThreshold(
DdManager * dd,
DdNode * f,
CUDD_VALUE_TYPE value
)
Converts an ADD to a BDD by replacing all discriminants greater than or
equal to value with 1, and all other discriminants with 0. Returns a pointer
to the resulting BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addCmpl(
DdManager * dd,
DdNode * f
)
Computes the complement of an ADD a la C language: The complement of 0 is 1
and the complement of everything else is 0. Returns a pointer to the
resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addCompose(
DdManager * dd,
DdNode * f,
DdNode * g,
int v
)
Substitutes g for x_v in the ADD for f. v is the index of the variable to be
substituted. g must be a 0-1 ADD. Cudd_bddCompose passes the corresponding
projection function to the recursive procedure, so that the cache may be
used. Returns the composed ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addComputeCube(
DdManager * dd,
DdNode ** vars,
int * phase,
int n
)
Computes the cube of an array of ADD variables. If non-null, the phase
argument indicates which literal of each variable should appear in the cube.
If phase[i] is nonzero, then the positive literal is used. If phase is NULL,
the cube is positive unate. Returns a pointer to the result if successful;
NULL otherwise.
Side Effects: none
DdNode *
Cudd_addConstrain(
DdManager * dd,
DdNode * f,
DdNode * c
)
Computes f constrain c (f @ c), for f an ADD and c a 0-1 ADD. List of
special cases: F @ 0 = 0 F @ 1 = F 0 @ c = 0 1 @ c
= 1 F @ F = 1 Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_addConst(
DdManager * dd,
CUDD_VALUE_TYPE c
)
Retrieves the ADD for constant c if it already exists, or creates a new ADD.
Returns a pointer to the ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addDiff(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Returns NULL if not a terminal case; f op g otherwise, where f op g is
plusinfinity if f=g; min(f,g) if f!=g.
Side Effects: None
DdNode *
Cudd_addDivide(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point division. Returns NULL if not a terminal case; f
/ g otherwise.
Side Effects: None
DdNode *
Cudd_addEvalConst(
DdManager * dd,
DdNode * f,
DdNode * g
)
Checks whether ADD g is constant whenever ADD f is 1. f must be a 0-1 ADD.
Returns a pointer to the resulting ADD (which may or may not be constant) or
DD_NON_CONSTANT. If f is identically 0, the check is assumed to be
successful, and the background value is returned. No new nodes are created.
Side Effects: None
DdNode *
Cudd_addExistAbstract(
DdManager * manager,
DdNode * f,
DdNode * cube
)
Abstracts all the variables in cube from f by summing over all possible
values taken by the variables. Returns the abstracted ADD.
Side Effects: None
DdNode *
Cudd_addFindMax(
DdManager * dd,
DdNode * f
)
Returns a pointer to a constant ADD.
Side Effects: None
DdNode *
Cudd_addFindMin(
DdManager * dd,
DdNode * f
)
Returns a pointer to a constant ADD.
Side Effects: None
DdNode *
Cudd_addGeneralVectorCompose(
DdManager * dd,
DdNode * f,
DdNode ** vectorOn,
DdNode ** vectorOff
)
Given a vector of ADDs, creates a new ADD by substituting the ADDs for the
variables of the ADD f. vectorOn contains ADDs to be substituted for the x_v
and vectorOff the ADDs to be substituted for x_v'. There should be an entry
in vector for each variable in the manager. If no substitution is sought for
a given variable, the corresponding projection function should be specified
in the vector. This function implements simultaneous composition. Returns a
pointer to the resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addHamming(
DdManager * dd,
DdNode ** xVars,
DdNode ** yVars,
int nVars
)
Computes the Hamming distance ADD. Returns an ADD that gives the Hamming
distance between its two arguments if successful; NULL otherwise. The two
vectors xVars and yVars identify the variables that form the two arguments.
Side Effects: None
int
Cudd_addHarwell(
FILE * fp, pointer to the input file
DdManager * dd, DD manager
DdNode ** E, characteristic function of the graph
DdNode *** x, array of row variables
DdNode *** y, array of column variables
DdNode *** xn, array of complemented row variables
DdNode *** yn_, array of complemented column variables
int * nx, number or row variables
int * ny, number or column variables
int * m, number of rows
int * n, number of columns
int bx, first index of row variables
int sx, step of row variables
int by, first index of column variables
int sy, step of column variables
int pr verbosity level
)
Reads in a matrix in the format of the Harwell-Boeing benchmark suite. The
variables are ordered as follows: x[0] y[0] x[1] y[1] ...
0 is the most significant bit. On input, nx and ny hold the
numbers of row and column variables already in existence. On output, they
hold the numbers of row and column variables actually used by the matrix. m
and n are set to the numbers of rows and columns of the matrix. Their values
on input are immaterial. Returns 1 on success; 0 otherwise. The ADD for the
sparse matrix is returned in E, and its reference count is > 0.
Side Effects: None
DdNode *
Cudd_addIteConstant(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * h
)
Implements ITEconstant for ADDs. f must be a 0-1 ADD. Returns a pointer to
the resulting ADD (which may or may not be constant) or DD_NON_CONSTANT. No
new nodes are created. This function can be used, for instance, to check
that g has a constant value (specified by h) whenever f is 1. If the
constant value is unknown, then one should use Cudd_addEvalConst.
Side Effects: None
DdNode *
Cudd_addIte(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * h
)
Implements ITE(f,g,h). This procedure assumes that f is a 0-1 ADD. Returns a
pointer to the resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addIthBit(
DdManager * dd,
DdNode * f,
int bit
)
Produces an ADD from another ADD by replacing all discriminants whose i-th
bit is equal to 1 with 1, and all other discriminants with 0. The i-th bit
refers to the integer representation of the leaf value. If the value is has
a fractional part, it is ignored. Repeated calls to this procedure allow one
to transform an integer-valued ADD into an array of ADDs, one for each bit
of the leaf values. Returns a pointer to the resulting ADD if successful;
NULL otherwise.
Side Effects: None
DdNode *
Cudd_addIthVar(
DdManager * dd,
int i
)
Retrieves the ADD variable with index i if it already exists, or creates a
new ADD variable. Returns a pointer to the variable if successful; NULL
otherwise. An ADD variable differs from a BDD variable because it points to
the arithmetic zero, instead of having a complement pointer to 1.
Side Effects: None
int
Cudd_addLeq(
DdManager * dd,
DdNode * f,
DdNode * g
)
Returns 1 if f is less than or equal to g; 0 otherwise. No new nodes are
created. This procedure works for arbitrary ADDs. For 0-1 ADDs
Cudd_addEvalConst is more efficient.
Side Effects: None
DdNode *
Cudd_addLog(
DdManager * dd,
DdNode * f
)
Natural logarithm of an ADDs. Returns NULL if not a terminal case; log(f)
otherwise. The discriminants of f must be positive double's.
Side Effects: None
DdNode *
Cudd_addMatrixMultiply(
DdManager * dd,
DdNode * A,
DdNode * B,
DdNode ** z,
int nz
)
Calculates the product of two matrices, A and B, represented as ADDs. This
procedure implements the quasiring multiplication algorithm. A is assumed to
depend on variables x (rows) and z (columns). B is assumed to depend on
variables z (rows) and y (columns). The product of A and B then depends on x
(rows) and y (columns). Only the z variables have to be explicitly
identified; they are the "summation" variables. Returns a pointer to the
result if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addMaximum(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point max for Cudd_addApply. Returns NULL if not a
terminal case; max(f,g) otherwise.
Side Effects: None
DdNode *
Cudd_addMinimum(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point min for Cudd_addApply. Returns NULL if not a
terminal case; min(f,g) otherwise.
Side Effects: None
DdNode *
Cudd_addMinus(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point subtraction. Returns NULL if not a terminal case;
f - g otherwise.
Side Effects: None
DdNode *
Cudd_addMonadicApply(
DdManager * dd,
DD_MAOP op,
DdNode * f
)
Applies op to the discriminants of f. Returns a pointer to the result if
succssful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addNand(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
NAND of two 0-1 ADDs. Returns NULL if not a terminal case; f NAND g
otherwise.
Side Effects: None
DdNode *
Cudd_addNegate(
DdManager * dd,
DdNode * f
)
Computes the additive inverse of an ADD. Returns a pointer to the result if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addNewVarAtLevel(
DdManager * dd,
int level
)
Creates a new ADD variable. The new variable has an index equal to the
largest previous index plus 1 and is positioned at the specified level in
the order. Returns a pointer to the new variable if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_addNewVar(
DdManager * dd
)
Creates a new ADD variable. The new variable has an index equal to the
largest previous index plus 1. Returns a pointer to the new variable if
successful; NULL otherwise. An ADD variable differs from a BDD variable
because it points to the arithmetic zero, instead of having a complement
pointer to 1.
Side Effects: None
DdNode *
Cudd_addNonSimCompose(
DdManager * dd,
DdNode * f,
DdNode ** vector
)
Given a vector of 0-1 ADDs, creates a new ADD by substituting the 0-1 ADDs
for the variables of the ADD f. There should be an entry in vector for each
variable in the manager. This function implements non-simultaneous
composition. If any of the functions being composed depends on any of the
variables being substituted, then the result depends on the order of
composition, which in turn depends on the variable order: The variables
farther from the roots in the order are substituted first. Returns a pointer
to the resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addNor(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
NOR of two 0-1 ADDs. Returns NULL if not a terminal case; f NOR g otherwise.
Side Effects: None
DdNode *
Cudd_addOneZeroMaximum(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Returns 1 if f > g and 0 otherwise. Used in conjunction with
Cudd_addApply. Returns NULL if not a terminal case.
Side Effects: None
DdNode *
Cudd_addOrAbstract(
DdManager * manager,
DdNode * f,
DdNode * cube
)
Abstracts all the variables in cube from the 0-1 ADD f by taking the
disjunction over all possible values taken by the variables. Returns the
abstracted ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addOr(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Disjunction of two 0-1 ADDs. Returns NULL if not a terminal case; f OR g
otherwise.
Side Effects: None
DdNode *
Cudd_addOuterSum(
DdManager * dd,
DdNode * M,
DdNode * r,
DdNode * c
)
Takes the pointwise minimum of a matrix and the outer sum of two vectors.
This procedure is used in the Floyd-Warshall all-pair shortest path
algorithm. Returns a pointer to the result if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addPermute(
DdManager * manager,
DdNode * node,
int * permut
)
Given a permutation in array permut, creates a new ADD with permuted
variables. There should be an entry in array permut for each variable in the
manager. The i-th entry of permut holds the index of the variable that is to
substitute the i-th variable. Returns a pointer to the resulting ADD if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addPlus(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point addition. Returns NULL if not a terminal case;
f+g otherwise.
Side Effects: None
int
Cudd_addRead(
FILE * fp, input file pointer
DdManager * dd, DD manager
DdNode ** E, characteristic function of the graph
DdNode *** x, array of row variables
DdNode *** y, array of column variables
DdNode *** xn, array of complemented row variables
DdNode *** yn_, array of complemented column variables
int * nx, number or row variables
int * ny, number or column variables
int * m, number of rows
int * n, number of columns
int bx, first index of row variables
int sx, step of row variables
int by, first index of column variables
int sy step of column variables
)
Reads in a sparse matrix specified in a simple format. The first line of the
input contains the numbers of rows and columns. The remaining lines contain
the elements of the matrix, one per line. Given a background value
(specified by the background field of the manager), only the values
different from it are explicitly listed. Each foreground element is
described by two integers, i.e., the row and column number, and a real
number, i.e., the value. Cudd_addRead produces an ADD that depends on two
sets of variables: x and y. The x variables (x[0] ... x[nx-1]) encode the
row index and the y variables (y[0] ... y[ny-1]) encode the column index.
x[0] and y[0] are the most significant bits in the indices. The variables
may already exist or may be created by the function. The index of x[i] is
bx+i*sx, and the index of y[i] is by+i*sy. On input, nx and ny hold the
numbers of row and column variables already in existence. On output, they
hold the numbers of row and column variables actually used by the matrix.
When Cudd_addRead creates the variable arrays, the index of x[i] is bx+i*sx,
and the index of y[i] is by+i*sy. When some variables already exist
Cudd_addRead expects the indices of the existing x variables to be bx+i*sx,
and the indices of the existing y variables to be by+i*sy. m and n are
set to the numbers of rows and columns of the matrix. Their values on input
are immaterial. The ADD for the sparse matrix is returned in E, and its
reference count is > 0. Cudd_addRead returns 1 in case of success; 0
otherwise.
Side Effects: nx and ny are set to the numbers of row and column variables.
m and n are set to the numbers of rows and columns. x and y are possibly
extended to represent the array of row and column variables. Similarly for
xn and yn_, which hold on return from Cudd_addRead the complements of the
row and column variables.
DdNode *
Cudd_addResidue(
DdManager * dd, manager
int n, number of bits
int m, modulus
int options, options
int top index of top variable
)
Builds an ADD for the residue modulo m of an n-bit number. The modulus must
be at least 2, and the number of bits at least 1. Parameter options
specifies whether the MSB should be on top or the LSB; and whther the number
whose residue is computed is in two's complement notation or not. The macro
CUDD_RESIDUE_DEFAULT specifies LSB on top and unsigned number. The macro
CUDD_RESIDUE_MSB specifies MSB on top, and the macro CUDD_RESIDUE_TC
specifies two's complement residue. To request MSB on top and two's
complement residue simultaneously, one can OR the two macros:
CUDD_RESIDUE_MSB | CUDD_RESIDUE_TC. Cudd_addResidue returns a pointer to the
resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addRestrict(
DdManager * dd,
DdNode * f,
DdNode * c
)
ADD restrict according to Coudert and Madre's algorithm (ICCAD90). Returns
the restricted ADD if successful; otherwise NULL. If application of restrict
results in an ADD larger than the input ADD, the input ADD is returned.
Side Effects: None
DdNode *
Cudd_addRoundOff(
DdManager * dd,
DdNode * f,
int N
)
Rounds off the discriminants of an ADD. The discriminants are rounded off to
N digits after the decimal. Returns a pointer to the result ADD if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addScalarInverse(
DdManager * dd,
DdNode * f,
DdNode * epsilon
)
Computes an n ADD where the discriminants are the multiplicative inverses of
the corresponding discriminants of the argument ADD. Returns a pointer to
the resulting ADD in case of success. Returns NULL if any discriminants
smaller than epsilon is encountered.
Side Effects: None
DdNode *
Cudd_addSetNZ(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
This operator sets f to the value of g wherever g != 0. Returns NULL if not
a terminal case; f op g otherwise.
Side Effects: None
DdNode *
Cudd_addSwapVariables(
DdManager * dd,
DdNode * f,
DdNode ** x,
DdNode ** y,
int n
)
Swaps two sets of variables of the same size (x and y) in the ADD f. The
size is given by n. The two sets of variables are assumed to be disjoint.
Returns a pointer to the resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addThreshold(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Threshold operator for Apply (f if f >=g; 0 if f<g). Returns NULL if
not a terminal case; f op g otherwise.
Side Effects: None
DdNode *
Cudd_addTimesPlus(
DdManager * dd,
DdNode * A,
DdNode * B,
DdNode ** z,
int nz
)
Calculates the product of two matrices, A and B, represented as ADDs, using
the CMU matrix by matrix multiplication procedure by Clarke et al.. Matrix A
has x's as row variables and z's as column variables, while matrix B has z's
as row variables and y's as column variables. Returns the pointer to the
result if successful; NULL otherwise. The resulting matrix has x's as row
variables and y's as column variables.
Side Effects: None
DdNode *
Cudd_addTimes(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
Integer and floating point multiplication. Returns NULL if not a terminal
case; f * g otherwise. This function can be used also to take the AND of two
0-1 ADDs.
Side Effects: None
DdNode *
Cudd_addTriangle(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode ** z,
int nz
)
Implements the semiring multiplication algorithm used in the triangulation
step for the shortest path computation. f is assumed to depend on variables
x (rows) and z (columns). g is assumed to depend on variables z (rows) and y
(columns). The product of f and g then depends on x (rows) and y (columns).
Only the z variables have to be explicitly identified; they are the
"abstraction" variables. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_addUnivAbstract(
DdManager * manager,
DdNode * f,
DdNode * cube
)
Abstracts all the variables in cube from f by taking the product over all
possible values taken by the variable. Returns the abstracted ADD if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addVectorCompose(
DdManager * dd,
DdNode * f,
DdNode ** vector
)
Given a vector of 0-1 ADDs, creates a new ADD by substituting the 0-1 ADDs
for the variables of the ADD f. There should be an entry in vector for each
variable in the manager. If no substitution is sought for a given variable,
the corresponding projection function should be specified in the vector.
This function implements simultaneous composition. Returns a pointer to the
resulting ADD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addWalsh(
DdManager * dd,
DdNode ** x,
DdNode ** y,
int n
)
Generates a Walsh matrix in ADD form. Returns a pointer to the matrixi if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_addXeqy(
DdManager * dd, DD manager
int N, number of x and y variables
DdNode ** x, array of x variables
DdNode ** y array of y variables
)
This function generates an ADD for the function x==y. Both x and y are N-bit
numbers, x[0] x[1] ... x[N-1] and y[0] y[1] ... y[N-1], with 0 the most
significant bit. The ADD is built bottom-up. It has 3*N-1 internal nodes, if
the variables are ordered as follows: x[0] y[0] x[1] y[1] ... x[N-1] y[N-1].
Side Effects: None
DdNode *
Cudd_addXnor(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
XNOR of two 0-1 ADDs. Returns NULL if not a terminal case; f XNOR g
otherwise.
Side Effects: None
DdNode *
Cudd_addXor(
DdManager * dd,
DdNode ** f,
DdNode ** g
)
XOR of two 0-1 ADDs. Returns NULL if not a terminal case; f XOR g otherwise.
Side Effects: None
DdNode *
Cudd_bddAdjPermuteX(
DdManager * dd,
DdNode * B,
DdNode ** x,
int n
)
Rearranges a set of variables in the BDD B. The size of the set is given by
n. This procedure is intended for the `randomization' of the priority
functions. Returns a pointer to the BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddAndAbstractLimit(
DdManager * manager,
DdNode * f,
DdNode * g,
DdNode * cube,
unsigned int limit
)
Takes the AND of two BDDs and simultaneously abstracts the variables in
cube. The variables are existentially abstracted. Returns a pointer to the
result is successful; NULL otherwise. In particular, if the number of new
nodes created exceeds limit, this function returns NULL.
Side Effects: None
DdNode *
Cudd_bddAndAbstract(
DdManager * manager,
DdNode * f,
DdNode * g,
DdNode * cube
)
Takes the AND of two BDDs and simultaneously abstracts the variables in
cube. The variables are existentially abstracted. Returns a pointer to the
result is successful; NULL otherwise. Cudd_bddAndAbstract implements the
semiring matrix multiplication algorithm for the boolean semiring.
Side Effects: None
DdNode *
Cudd_bddAndLimit(
DdManager * dd,
DdNode * f,
DdNode * g,
unsigned int limit
)
Computes the conjunction of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up or
more new nodes than limit are required.
Side Effects: None
DdNode *
Cudd_bddAnd(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the conjunction of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
int
Cudd_bddApproxConjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** conjuncts address of the first factor
)
Performs two-way conjunctive decomposition of a BDD. This procedure owes its
name to the use of supersetting to obtain an initial factor of the given
function. Returns the number of conjuncts produced, that is, 2 if
successful; 1 if no meaningful decomposition was found; 0 otherwise. The
conjuncts produced by this procedure tend to be imbalanced.
Side Effects: The factors are returned in an array as side effects. The
array is allocated by this function. It is the caller's responsibility to
free it. On successful completion, the conjuncts are already referenced. If
the function returns 0, the array for the conjuncts is not allocated. If the
function returns 1, the only factor equals the function to be decomposed.
int
Cudd_bddApproxDisjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** disjuncts address of the array of the disjuncts
)
Performs two-way disjunctive decomposition of a BDD. Returns the number of
disjuncts produced, that is, 2 if successful; 1 if no meaningful
decomposition was found; 0 otherwise. The disjuncts produced by this
procedure tend to be imbalanced.
Side Effects: The two disjuncts are returned in an array as side effects.
The array is allocated by this function. It is the caller's responsibility
to free it. On successful completion, the disjuncts are already referenced.
If the function returns 0, the array for the disjuncts is not allocated. If
the function returns 1, the only factor equals the function to be
decomposed.
int
Cudd_bddBindVar(
DdManager * dd, manager
int index variable index
)
This function sets a flag to prevent sifting of a variable. Returns 1 if
successful; 0 otherwise (i.e., invalid variable index).
Side Effects: Changes the "bindVar" flag in DdSubtable.
DdNode *
Cudd_bddBooleanDiff(
DdManager * manager,
DdNode * f,
int x
)
Computes the boolean difference of f with respect to the variable with index
x. Returns the BDD of the boolean difference if successful; NULL otherwise.
Side Effects: None
DdNode **
Cudd_bddCharToVect(
DdManager * dd,
DdNode * f
)
Computes a vector of BDDs whose image equals a non-zero function. The result
depends on the variable order. The i-th component of the vector depends only
on the first i variables in the order. Each BDD in the vector is not larger
than the BDD of the given characteristic function. This function is based on
the description of char-to-vect in "Verification of Sequential Machines
Using Boolean Functional Vectors" by O. Coudert, C. Berthet and J. C. Madre.
Returns a pointer to an array containing the result if successful; NULL
otherwise. The size of the array equals the number of variables in the
manager. The components of the solution have their reference counts already
incremented (unlike the results of most other functions in the package).
Side Effects: None
DdNode *
Cudd_bddClippingAndAbstract(
DdManager * dd, manager
DdNode * f, first conjunct
DdNode * g, second conjunct
DdNode * cube, cube of variables to be abstracted
int maxDepth, maximum recursion depth
int direction under (0) or over (1) approximation
)
Approximates the conjunction of two BDDs f and g and simultaneously
abstracts the variables in cube. The variables are existentially abstracted.
Returns a pointer to the resulting BDD if successful; NULL if the
intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddClippingAnd(
DdManager * dd, manager
DdNode * f, first conjunct
DdNode * g, second conjunct
int maxDepth, maximum recursion depth
int direction under (0) or over (1) approximation
)
Approximates the conjunction of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddClosestCube(
DdManager * dd,
DdNode * f,
DdNode * g,
int * distance
)
Finds a cube of f at minimum Hamming distance from the minterms of g. All
the minterms of the cube are at the minimum distance. If the distance is 0,
the cube belongs to the intersection of f and g. Returns the cube if
successful; NULL otherwise.
Side Effects: The distance is returned as a side effect.
DdNode *
Cudd_bddCompose(
DdManager * dd,
DdNode * f,
DdNode * g,
int v
)
Substitutes g for x_v in the BDD for f. v is the index of the variable to be
substituted. Cudd_bddCompose passes the corresponding projection function to
the recursive procedure, so that the cache may be used. Returns the composed
BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddComputeCube(
DdManager * dd,
DdNode ** vars,
int * phase,
int n
)
Computes the cube of an array of BDD variables. If non-null, the phase
argument indicates which literal of each variable should appear in the cube.
If phase[i] is nonzero, then the positive literal is used. If phase is NULL,
the cube is positive unate. Returns a pointer to the result if successful;
NULL otherwise.
Side Effects: None
DdNode **
Cudd_bddConstrainDecomp(
DdManager * dd,
DdNode * f
)
BDD conjunctive decomposition as in McMillan's CAV96 paper. The
decomposition is canonical only for a given variable order. If canonicity is
required, variable ordering must be disabled after the decomposition has
been computed. Returns an array with one entry for each BDD variable in the
manager if successful; otherwise NULL. The components of the solution have
their reference counts already incremented (unlike the results of most other
functions in the package.
Side Effects: None
DdNode *
Cudd_bddConstrain(
DdManager * dd,
DdNode * f,
DdNode * c
)
Computes f constrain c (f @ c). Uses a canonical form: (f' @ c) = ( f @ c)'.
(Note: this is not true for c.) List of special cases: f @ 0 = 0
f @ 1 = f 0 @ c = 0 1 @ c = 1 f @ f = 1 f @ f'= 0
Returns a pointer to the result if successful; NULL otherwise. Note
that if F=(f1,...,fn) and reordering takes place while computing F @ c, then
the image restriction property (Img(F,c) = Img(F @ c)) is lost.
Side Effects: None
double
Cudd_bddCorrelationWeights(
DdManager * manager,
DdNode * f,
DdNode * g,
double * prob
)
Computes the correlation of f and g for given input probabilities. On input,
prob[i] is supposed to contain the probability of the i-th input variable to
be 1. If f == g, their correlation is 1. If f == g', their correlation is 0.
Returns the probability that f and g have the same value. If it runs out of
memory, returns (double)CUDD_OUT_OF_MEM. The correlation of f and the
constant one gives the probability of f.
Side Effects: None
double
Cudd_bddCorrelation(
DdManager * manager,
DdNode * f,
DdNode * g
)
Computes the correlation of f and g. If f == g, their correlation is 1. If f
== g', their correlation is 0. Returns the fraction of minterms in the ON-
set of the EXNOR of f and g. If it runs out of memory, returns
(double)CUDD_OUT_OF_MEM.
Side Effects: None
DdNode *
Cudd_bddExistAbstract(
DdManager * manager,
DdNode * f,
DdNode * cube
)
Existentially abstracts all the variables in cube from f. Returns the
abstracted BDD if successful; NULL otherwise.
Side Effects: None
int
Cudd_bddGenConjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** conjuncts address of the array of conjuncts
)
Performs two-way conjunctive decomposition of a BDD. This procedure owes its
name to the fact tht it generalizes the decomposition based on the cofactors
with respect to one variable. Returns the number of conjuncts produced, that
is, 2 if successful; 1 if no meaningful decomposition was found; 0
otherwise. The conjuncts produced by this procedure tend to be balanced.
Side Effects: The two factors are returned in an array as side effects. The
array is allocated by this function. It is the caller's responsibility to
free it. On successful completion, the conjuncts are already referenced. If
the function returns 0, the array for the conjuncts is not allocated. If the
function returns 1, the only factor equals the function to be decomposed.
int
Cudd_bddGenDisjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** disjuncts address of the array of the disjuncts
)
Performs two-way disjunctive decomposition of a BDD. Returns the number of
disjuncts produced, that is, 2 if successful; 1 if no meaningful
decomposition was found; 0 otherwise. The disjuncts produced by this
procedure tend to be balanced.
Side Effects: The two disjuncts are returned in an array as side effects.
The array is allocated by this function. It is the caller's responsibility
to free it. On successful completion, the disjuncts are already referenced.
If the function returns 0, the array for the disjuncts is not allocated. If
the function returns 1, the only factor equals the function to be
decomposed.
DdNode *
Cudd_bddIntersect(
DdManager * dd, manager
DdNode * f, first operand
DdNode * g second operand
)
Computes a function included in the intersection of f and g. (That is, a
witness that the intersection is not empty.) Cudd_bddIntersect tries to
build as few new nodes as possible. If the only result of interest is
whether f and g intersect, Cudd_bddLeq should be used instead.
Side Effects: None
int
Cudd_bddIsNsVar(
DdManager * dd,
int index
)
Checks whether a variable is next state. Returns 1 if the variable's type is
present state; 0 if the variable exists but is not a present state; -1 if
the variable does not exist.
Side Effects: none
int
Cudd_bddIsPiVar(
DdManager * dd, manager
int index variable index
)
Checks whether a variable is primary input. Returns 1 if the variable's type
is primary input; 0 if the variable exists but is not a primary input; -1 if
the variable does not exist.
Side Effects: none
int
Cudd_bddIsPsVar(
DdManager * dd,
int index
)
Checks whether a variable is present state. Returns 1 if the variable's type
is present state; 0 if the variable exists but is not a present state; -1 if
the variable does not exist.
Side Effects: none
int
Cudd_bddIsVarEssential(
DdManager * manager,
DdNode * f,
int id,
int phase
)
Determines whether a given variable is essential with a given phase in a
BDD. Uses Cudd_bddIteConstant. Returns 1 if phase == 1 and f-->x_id, or if
phase == 0 and f-->x_id'.
Side Effects: None
int
Cudd_bddIsVarHardGroup(
DdManager * dd,
int index
)
Checks whether a variable is set to be in a hard group. This function is
used for lazy sifting. Returns 1 if the variable is marked to be in a hard
group; 0 if the variable exists, but it is not marked to be in a hard group;
-1 if the variable does not exist.
Side Effects: none
int
Cudd_bddIsVarToBeGrouped(
DdManager * dd,
int index
)
Checks whether a variable is set to be grouped. This function is used for
lazy sifting.
Side Effects: none
int
Cudd_bddIsVarToBeUngrouped(
DdManager * dd,
int index
)
Checks whether a variable is set to be ungrouped. This function is used for
lazy sifting. Returns 1 if the variable is marked to be ungrouped; 0 if the
variable exists, but it is not marked to be ungrouped; -1 if the variable
does not exist.
Side Effects: none
DdNode *
Cudd_bddIsop(
DdManager * dd,
DdNode * L,
DdNode * U
)
Computes a BDD in the interval between L and U with a simple sum-of-produuct
cover. This procedure is similar to Cudd_zddIsop, but it does not return the
ZDD for the cover. Returns a pointer to the BDD if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_bddIteConstant(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * h
)
Implements ITEconstant(f,g,h). Returns a pointer to the resulting BDD (which
may or may not be constant) or DD_NON_CONSTANT. No new nodes are created.
Side Effects: None
int
Cudd_bddIterConjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** conjuncts address of the array of conjuncts
)
Performs two-way conjunctive decomposition of a BDD. This procedure owes its
name to the iterated use of supersetting to obtain a factor of the given
function. Returns the number of conjuncts produced, that is, 2 if
successful; 1 if no meaningful decomposition was found; 0 otherwise. The
conjuncts produced by this procedure tend to be imbalanced.
Side Effects: The factors are returned in an array as side effects. The
array is allocated by this function. It is the caller's responsibility to
free it. On successful completion, the conjuncts are already referenced. If
the function returns 0, the array for the conjuncts is not allocated. If the
function returns 1, the only factor equals the function to be decomposed.
int
Cudd_bddIterDisjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** disjuncts address of the array of the disjuncts
)
Performs two-way disjunctive decomposition of a BDD. Returns the number of
disjuncts produced, that is, 2 if successful; 1 if no meaningful
decomposition was found; 0 otherwise. The disjuncts produced by this
procedure tend to be imbalanced.
Side Effects: The two disjuncts are returned in an array as side effects.
The array is allocated by this function. It is the caller's responsibility
to free it. On successful completion, the disjuncts are already referenced.
If the function returns 0, the array for the disjuncts is not allocated. If
the function returns 1, the only factor equals the function to be
decomposed.
DdNode *
Cudd_bddIte(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * h
)
Implements ITE(f,g,h). Returns a pointer to the resulting BDD if successful;
NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddIthVar(
DdManager * dd,
int i
)
Retrieves the BDD variable with index i if it already exists, or creates a
new BDD variable. Returns a pointer to the variable if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_bddLICompaction(
DdManager * dd, manager
DdNode * f, function to be minimized
DdNode * c constraint (care set)
)
Performs safe minimization of a BDD. Given the BDD f of a
function to be minimized and a BDD c representing the care set,
Cudd_bddLICompaction produces the BDD of a function that agrees with
f wherever c is 1. Safe minimization means that
the size of the result is guaranteed not to exceed the size of
f. This function is based on the DAC97 paper by Hong et al..
Returns a pointer to the result if successful; NULL otherwise.
Side Effects: None
int
Cudd_bddLeqUnless(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * D
)
Tells whether f is less than of equal to G unless D is 1. f, g, and D are
BDDs. The function returns 1 if f is less than of equal to G, and 0
otherwise. No new nodes are created.
Side Effects: None
int
Cudd_bddLeq(
DdManager * dd,
DdNode * f,
DdNode * g
)
Returns 1 if f is less than or equal to g; 0 otherwise. No new nodes are
created.
Side Effects: None
DdNode *
Cudd_bddLiteralSetIntersection(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the intesection of two sets of literals represented as BDDs. Each
set is represented as a cube of the literals in the set. The empty set is
represented by the constant 1. No variable can be simultaneously present in
both phases in a set. Returns a pointer to the BDD representing the
intersected sets, if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddMakePrime(
DdManager * dd, manager
DdNode * cube, cube to be expanded
DdNode * f function of which the cube is to be made
a prime
)
Expands cube to a prime implicant of f. Returns the prime if successful;
NULL otherwise. In particular, NULL is returned if cube is not a real cube
or is not an implicant of f.
Side Effects: None
DdNode *
Cudd_bddMinimize(
DdManager * dd,
DdNode * f,
DdNode * c
)
Finds a small BDD that agrees with f over c.
Returns a pointer to the result if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddNPAnd(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes f non-polluting-and g. The non-polluting AND of f and g is a hybrid
of AND and Restrict. From Restrict, this operation takes the idea of
existentially quantifying the top variable of the second operand if it does
not appear in the first. Therefore, the variables that appear in the result
also appear in f. For the rest, the function behaves like AND. Since the two
operands play different roles, non-polluting AND is not commutative. Returns
a pointer to the result if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddNand(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the NAND of two BDDs f and g. Returns a pointer to the resulting
BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddNewVarAtLevel(
DdManager * dd,
int level
)
Creates a new BDD variable. The new variable has an index equal to the
largest previous index plus 1 and is positioned at the specified level in
the order. Returns a pointer to the new variable if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_bddNewVar(
DdManager * dd
)
Creates a new BDD variable. The new variable has an index equal to the
largest previous index plus 1. Returns a pointer to the new variable if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddNor(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the NOR of two BDDs f and g. Returns a pointer to the resulting BDD
if successful; NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddOr(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the disjunction of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddPermute(
DdManager * manager,
DdNode * node,
int * permut
)
Given a permutation in array permut, creates a new BDD with permuted
variables. There should be an entry in array permut for each variable in the
manager. The i-th entry of permut holds the index of the variable that is to
substitute the i-th variable. Returns a pointer to the resulting BDD if
successful; NULL otherwise.
Side Effects: None
DdNode **
Cudd_bddPickArbitraryMinterms(
DdManager * dd, manager
DdNode * f, function from which to pick k minterms
DdNode ** vars, array of variables
int n, size of vars
int k number of minterms to find
)
Picks k on-set minterms evenly distributed from given DD. The minterms are
in terms of vars. The array vars should contain at
least all variables in the support of f; if this condition is
not met the minterms built by this procedure may not be contained in
f. Builds an array of BDDs for the minterms and returns a
pointer to it if successful; NULL otherwise. There are three reasons why the
procedure may fail: It may run out of memory; the function
f may be the constant 0; the minterms may not be contained
in f.
Side Effects: None
int
Cudd_bddPickOneCube(
DdManager * ddm,
DdNode * node,
char * string
)
Picks one on-set cube randomly from the given DD. The cube is written into
an array of characters. The array must have at least as many entries as
there are variables. Returns 1 if successful; 0 otherwise.
Side Effects: None
DdNode *
Cudd_bddPickOneMinterm(
DdManager * dd, manager
DdNode * f, function from which to pick one minterm
DdNode ** vars, array of variables
int n size of vars
)
Picks one on-set minterm randomly from the given DD. The minterm is in terms
of vars. The array vars should contain at least
all variables in the support of f; if this condition is not met
the minterm built by this procedure may not be contained in f.
Builds a BDD for the minterm and returns a pointer to it if successful; NULL
otherwise. There are three reasons why the procedure may fail: It
may run out of memory; the function f may be the constant
0; the minterm may not be contained in f.
Side Effects: None
int
Cudd_bddPrintCover(
DdManager * dd,
DdNode * l,
DdNode * u
)
Prints a sum of product cover for an incompletely specified function given
by a lower bound and an upper bound. Each product is a prime implicant
obtained by expanding the product corresponding to a path from node to the
constant one. Uses the package default output file. Returns 1 if successful;
0 otherwise.
Side Effects: None
int
Cudd_bddReadPairIndex(
DdManager * dd,
int index
)
Reads a corresponding pair index for a given index. These pair indices are
present and next state variable. Returns the corresponding variable index if
the variable exists; -1 otherwise.
Side Effects: modifies the manager
int
Cudd_bddRead(
FILE * fp, input file pointer
DdManager * dd, DD manager
DdNode ** E, characteristic function of the graph
DdNode *** x, array of row variables
DdNode *** y, array of column variables
int * nx, number or row variables
int * ny, number or column variables
int * m, number of rows
int * n, number of columns
int bx, first index of row variables
int sx, step of row variables
int by, first index of column variables
int sy step of column variables
)
Reads in a graph (without labels) given as an adjacency matrix. The first
line of the input contains the numbers of rows and columns of the adjacency
matrix. The remaining lines contain the arcs of the graph, one per line.
Each arc is described by two integers, i.e., the row and column number, or
the indices of the two endpoints. Cudd_bddRead produces a BDD that depends
on two sets of variables: x and y. The x variables (x[0] ... x[nx-1]) encode
the row index and the y variables (y[0] ... y[ny-1]) encode the column
index. x[0] and y[0] are the most significant bits in the indices. The
variables may already exist or may be created by the function. The index of
x[i] is bx+i*sx, and the index of y[i] is by+i*sy. On input, nx and ny
hold the numbers of row and column variables already in existence. On
output, they hold the numbers of row and column variables actually used by
the matrix. When Cudd_bddRead creates the variable arrays, the index of x[i]
is bx+i*sx, and the index of y[i] is by+i*sy. When some variables already
exist, Cudd_bddRead expects the indices of the existing x variables to be
bx+i*sx, and the indices of the existing y variables to be by+i*sy. m and
n are set to the numbers of rows and columns of the matrix. Their values on
input are immaterial. The BDD for the graph is returned in E, and its
reference count is > 0. Cudd_bddRead returns 1 in case of success; 0
otherwise.
Side Effects: nx and ny are set to the numbers of row and column variables.
m and n are set to the numbers of rows and columns. x and y are possibly
extended to represent the array of row and column variables.
void
Cudd_bddRealignDisable(
DdManager * unique
)
Disables realignment of ZDD order to BDD order.
Side Effects: None
void
Cudd_bddRealignEnable(
DdManager * unique
)
Enables realignment of the BDD variable order to the ZDD variable order
after the ZDDs have been reordered. The number of ZDD variables must be a
multiple of the number of BDD variables for realignment to make sense. If
this condition is not met, Cudd_zddReduceHeap will return 0. Let
M be the ratio of the two numbers. For the purpose of
realignment, the ZDD variables from M*i to (M+1)*i-
1 are reagarded as corresponding to BDD variable i.
Realignment is initially disabled.
Side Effects: None
int
Cudd_bddRealignmentEnabled(
DdManager * unique
)
Returns 1 if the realignment of BDD order to ZDD order is enabled; 0
otherwise.
Side Effects: None
int
Cudd_bddResetVarToBeGrouped(
DdManager * dd,
int index
)
Resets a variable not to be grouped. This function is used for lazy sifting.
Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
DdNode *
Cudd_bddRestrict(
DdManager * dd,
DdNode * f,
DdNode * c
)
BDD restrict according to Coudert and Madre's algorithm (ICCAD90). Returns
the restricted BDD if successful; otherwise NULL. If application of restrict
results in a BDD larger than the input BDD, the input BDD is returned.
Side Effects: None
int
Cudd_bddSetNsVar(
DdManager * dd, manager
int index variable index
)
Sets a variable type to next state. The variable type is used by lazy
sifting. Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetPairIndex(
DdManager * dd, manager
int index, variable index
int pairIndex corresponding variable index
)
Sets a corresponding pair index for a given index. These pair indices are
present and next state variable. Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetPiVar(
DdManager * dd, manager
int index variable index
)
Sets a variable type to primary input. The variable type is used by lazy
sifting. Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetPsVar(
DdManager * dd, manager
int index variable index
)
Sets a variable type to present state. The variable type is used by lazy
sifting. Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetVarHardGroup(
DdManager * dd,
int index
)
Sets a variable to be a hard group. This function is used for lazy sifting.
Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetVarToBeGrouped(
DdManager * dd,
int index
)
Sets a variable to be grouped. This function is used for lazy sifting.
Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
int
Cudd_bddSetVarToBeUngrouped(
DdManager * dd,
int index
)
Sets a variable to be ungrouped. This function is used for lazy sifting.
Returns 1 if successful; 0 otherwise.
Side Effects: modifies the manager
DdNode *
Cudd_bddSqueeze(
DdManager * dd, manager
DdNode * l, lower bound
DdNode * u upper bound
)
Finds a small BDD in a function interval. Given BDDs l and
u, representing the lower bound and upper bound of a function
interval, Cudd_bddSqueeze produces the BDD of a function within the interval
with a small BDD. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_bddSwapVariables(
DdManager * dd,
DdNode * f,
DdNode ** x,
DdNode ** y,
int n
)
Swaps two sets of variables of the same size (x and y) in the BDD f. The
size is given by n. The two sets of variables are assumed to be disjoint.
Returns a pointer to the resulting BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddTransfer(
DdManager * ddSource,
DdManager * ddDestination,
DdNode * f
)
Convert a BDD from a manager to another one. The orders of the variables in
the two managers may be different. Returns a pointer to the BDD in the
destination manager if successful; NULL otherwise.
Side Effects: None
int
Cudd_bddUnbindVar(
DdManager * dd, manager
int index variable index
)
This function resets the flag that prevents the sifting of a variable. In
successive variable reorderings, the variable will NOT be skipped, that is,
sifted. Initially all variables can be sifted. It is necessary to call this
function only to re-enable sifting after a call to Cudd_bddBindVar. Returns
1 if successful; 0 otherwise (i.e., invalid variable index).
Side Effects: Changes the "bindVar" flag in DdSubtable.
DdNode *
Cudd_bddUnivAbstract(
DdManager * manager,
DdNode * f,
DdNode * cube
)
Universally abstracts all the variables in cube from f. Returns the
abstracted BDD if successful; NULL otherwise.
Side Effects: None
int
Cudd_bddVarConjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** conjuncts address of the array of conjuncts
)
Conjunctively decomposes one BDD according to a variable. If f
is the function of the BDD and x is the variable, the
decomposition is (f+x)(f+x'). The variable is chosen so as to
balance the sizes of the two conjuncts and to keep them small. Returns the
number of conjuncts produced, that is, 2 if successful; 1 if no meaningful
decomposition was found; 0 otherwise.
Side Effects: The two factors are returned in an array as side effects. The
array is allocated by this function. It is the caller's responsibility to
free it. On successful completion, the conjuncts are already referenced. If
the function returns 0, the array for the conjuncts is not allocated. If the
function returns 1, the only factor equals the function to be decomposed.
int
Cudd_bddVarDisjDecomp(
DdManager * dd, manager
DdNode * f, function to be decomposed
DdNode *** disjuncts address of the array of the disjuncts
)
Performs two-way disjunctive decomposition of a BDD according to a variable.
If f is the function of the BDD and x is the
variable, the decomposition is f*x + f*x'. The variable is
chosen so as to balance the sizes of the two disjuncts and to keep them
small. Returns the number of disjuncts produced, that is, 2 if successful; 1
if no meaningful decomposition was found; 0 otherwise.
Side Effects: The two disjuncts are returned in an array as side effects.
The array is allocated by this function. It is the caller's responsibility
to free it. On successful completion, the disjuncts are already referenced.
If the function returns 0, the array for the disjuncts is not allocated. If
the function returns 1, the only factor equals the function to be
decomposed.
int
Cudd_bddVarIsBound(
DdManager * dd, manager
int index variable index
)
This function returns 1 if a variable is enabled for sifting. Initially all
variables can be sifted. This function returns 0 only if there has been a
previous call to Cudd_bddBindVar for that variable not followed by a call to
Cudd_bddUnbindVar. The function returns 0 also in the case in which the
index of the variable is out of bounds.
Side Effects: none
int
Cudd_bddVarIsDependent(
DdManager * dd,
DdNode * f,
DdNode * var variable
)
Checks whether a variable is dependent on others in a function. Returns 1 if
the variable is dependent; 0 otherwise. No new nodes are created.
Side Effects: None
DdNode *
Cudd_bddVarMap(
DdManager * manager, DD manager
DdNode * f function in which to remap variables
)
Remaps the variables of a BDD using the default variable map. A typical use
of this function is to swap two sets of variables. The variable map must be
registered with Cudd_SetVarMap. Returns a pointer to the resulting BDD if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddVectorCompose(
DdManager * dd,
DdNode * f,
DdNode ** vector
)
Given a vector of BDDs, creates a new BDD by substituting the BDDs for the
variables of the BDD f. There should be an entry in vector for each variable
in the manager. If no substitution is sought for a given variable, the
corresponding projection function should be specified in the vector. This
function implements simultaneous composition. Returns a pointer to the
resulting BDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddXnor(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the exclusive NOR of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
DdNode *
Cudd_bddXorExistAbstract(
DdManager * manager,
DdNode * f,
DdNode * g,
DdNode * cube
)
Takes the exclusive OR of two BDDs and simultaneously abstracts the
variables in cube. The variables are existentially abstracted. Returns a
pointer to the result is successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_bddXor(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the exclusive OR of two BDDs f and g. Returns a pointer to the
resulting BDD if successful; NULL if the intermediate result blows up.
Side Effects: None
void
Cudd_tlcInfoFree(
DdTlcInfo * t
)
Frees a DdTlcInfo Structure as well as the memory pointed by it.
Side Effects: None
DdNode *
Cudd_zddChange(
DdManager * dd,
DdNode * P,
int var
)
Substitutes a variable with its complement in a ZDD. returns a pointer to
the result if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddComplement(
DdManager * dd,
DdNode * node
)
Computes a complement cover for a ZDD node. For lack of a better method, we
first extract the function BDD from the ZDD cover, then make the complement
of the ZDD cover from the complement of the BDD node by using ISOP. Returns
a pointer to the resulting cover if successful; NULL otherwise. The result
depends on current variable order.
Side Effects: The result depends on current variable order.
double
Cudd_zddCountDouble(
DdManager * zdd,
DdNode * P
)
Counts the number of minterms of a ZDD. The result is returned as a double.
If the procedure runs out of memory, it returns (double) CUDD_OUT_OF_MEM.
This procedure is used in Cudd_zddCountMinterm.
Side Effects: None
double
Cudd_zddCountMinterm(
DdManager * zdd,
DdNode * node,
int path
)
Counts the number of minterms of the ZDD rooted at node. This
procedure takes a parameter path that specifies how many
variables are in the support of the function. If the procedure runs out of
memory, it returns (double) CUDD_OUT_OF_MEM.
Side Effects: None
int
Cudd_zddCount(
DdManager * zdd,
DdNode * P
)
Returns an integer representing the number of minterms in a ZDD.
Side Effects: None
char *
Cudd_zddCoverPathToString(
DdManager * zdd, DD manager
int * path, path of ZDD representing a cover
char * str pointer to string to use if != NULL
)
Converts a path of a ZDD representing a cover to a string. The string
represents an implicant of the cover. The path is typically produced by
Cudd_zddForeachPath. Returns a pointer to the string if successful; NULL
otherwise. If the str input is NULL, it allocates a new string. The string
passed to this function must have enough room for all variables and for the
terminator.
Side Effects: None
int
Cudd_zddDagSize(
DdNode * p_node
)
Counts the number of nodes in a ZDD. This function duplicates Cudd_DagSize
and is only retained for compatibility.
Side Effects: None
DdNode *
Cudd_zddDiffConst(
DdManager * zdd,
DdNode * P,
DdNode * Q
)
Inclusion test for ZDDs (P implies Q). No new nodes are generated by this
procedure. Returns empty if true; a valid pointer different from empty or
DD_NON_CONSTANT otherwise.
Side Effects: None
DdNode *
Cudd_zddDiff(
DdManager * dd,
DdNode * P,
DdNode * Q
)
Computes the difference of two ZDDs. Returns a pointer to the result if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddDivideF(
DdManager * dd,
DdNode * f,
DdNode * g
)
Modified version of Cudd_zddDivide. This function may disappear in future
releases.
Side Effects: None
DdNode *
Cudd_zddDivide(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the quotient of two unate covers represented by ZDDs. Unate covers
use one ZDD variable for each BDD variable. Returns a pointer to the
resulting ZDD if successful; NULL otherwise.
Side Effects: None
int
Cudd_zddDumpDot(
DdManager * dd, manager
int n, number of output nodes to be dumped
DdNode ** f, array of output nodes to be dumped
char ** inames, array of input names (or NULL)
char ** onames, array of output names (or NULL)
FILE * fp pointer to the dump file
)
Writes a file representing the argument ZDDs in a format suitable for the
graph drawing program dot. It returns 1 in case of success; 0 otherwise
(e.g., out-of-memory, file system full). Cudd_zddDumpDot does not close the
file: This is the caller responsibility. Cudd_zddDumpDot uses a minimal
unique subset of the hexadecimal address of a node as name for it. If the
argument inames is non-null, it is assumed to hold the pointers to the names
of the inputs. Similarly for onames. Cudd_zddDumpDot uses the following
convention to draw arcs: solid line: THEN arcs; dashed line:
ELSE arcs. The dot options are chosen so that the drawing fits on a
letter-size sheet.
Side Effects: None
DdGen *
Cudd_zddFirstPath(
DdManager * zdd,
DdNode * f,
int ** path
)
Defines an iterator on the paths of a ZDD and finds its first path. Returns
a generator that contains the information necessary to continue the
enumeration if successful; NULL otherwise. A path is represented as an
array of literals, which are integers in {0, 1, 2}; 0 represents an else arc
out of a node, 1 represents a then arc out of a node, and 2 stands for the
absence of a node. The size of the array equals the number of variables in
the manager at the time Cudd_zddFirstCube is called. The paths that end
in the empty terminal are not enumerated.
Side Effects: The first path is returned as a side effect.
Cudd_zddForeachPath(
manager,
f,
gen,
path
)
Iterates over the paths of a ZDD f. DdManager *manager;
DdNode *f; DdGen *gen; int *path; Cudd_zddForeachPath
allocates and frees the generator. Therefore the application should not try
to do that. Also, the path is freed at the end of Cudd_zddForeachPath and
hence is not available outside of the loop. CAUTION: It is assumed that
dynamic reordering will not occur while there are open generators. It is the
user's responsibility to make sure that dynamic reordering does not occur.
As long as new nodes are not created during generation, and dynamic
reordering is not called explicitly, dynamic reordering will not occur.
Alternatively, it is sufficient to disable dynamic reordering. It is a
mistake to dispose of a diagram on which generation is ongoing.
Side Effects: none
DdNode *
Cudd_zddIntersect(
DdManager * dd,
DdNode * P,
DdNode * Q
)
Computes the intersection of two ZDDs. Returns a pointer to the result if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddIsop(
DdManager * dd,
DdNode * L,
DdNode * U,
DdNode ** zdd_I
)
Computes an irredundant sum of products (ISOP) in ZDD form from BDDs. The
two BDDs L and U represent the lower bound and the upper bound,
respectively, of the function. The ISOP uses two ZDD variables for each BDD
variable: One for the positive literal, and one for the negative literal.
These two variables should be adjacent in the ZDD order. The two ZDD
variables corresponding to BDD variable i should have indices
2i and 2i+1. The result of this procedure depends
on the variable order. If successful, Cudd_zddIsop returns the BDD for the
function chosen from the interval. The ZDD representing the irredundant
cover is returned as a side effect in zdd_I. In case of failure, NULL is
returned.
Side Effects: zdd_I holds the pointer to the ZDD for the ISOP on successful
return.
DdNode *
Cudd_zddIte(
DdManager * dd,
DdNode * f,
DdNode * g,
DdNode * h
)
Computes the ITE of three ZDDs. Returns a pointer to the result if
successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddIthVar(
DdManager * dd,
int i
)
Retrieves the ZDD variable with index i if it already exists, or creates a
new ZDD variable. Returns a pointer to the variable if successful; NULL
otherwise.
Side Effects: None
int
Cudd_zddNextPath(
DdGen * gen,
int ** path
)
Generates the next path of a ZDD onset, using generator gen. Returns 0 if
the enumeration is completed; 1 otherwise.
Side Effects: The path is returned as a side effect. The generator is
modified.
DdNode *
Cudd_zddPortFromBdd(
DdManager * dd,
DdNode * B
)
Converts a BDD into a ZDD. This function assumes that there is a one-to-one
correspondence between the BDD variables and the ZDD variables, and that the
variable order is the same for both types of variables. These conditions are
established if the ZDD variables are created by one call to
Cudd_zddVarsFromBddVars with multiplicity = 1. Returns a pointer to the
resulting ZDD if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddPortToBdd(
DdManager * dd,
DdNode * f
)
Converts a ZDD into a BDD. Returns a pointer to the resulting ZDD if
successful; NULL otherwise.
Side Effects: None
int
Cudd_zddPrintCover(
DdManager * zdd,
DdNode * node
)
Prints a sum of products from a ZDD representing a cover. Returns 1 if
successful; 0 otherwise.
Side Effects: None
int
Cudd_zddPrintDebug(
DdManager * zdd,
DdNode * f,
int n,
int pr
)
Prints to the standard output a DD and its statistics. The statistics
include the number of nodes and the number of minterms. (The number of
minterms is also the number of combinations in the set.) The statistics are
printed if pr > 0. Specifically: pr = 0 : prints nothing
pr = 1 : prints counts of nodes and minterms pr = 2 : prints counts +
disjoint sum of products pr = 3 : prints counts + list of nodes pr
> 3 : prints counts + disjoint sum of products + list of nodes
Returns 1 if successful; 0 otherwise.
Side Effects: None
int
Cudd_zddPrintMinterm(
DdManager * zdd,
DdNode * node
)
Prints a disjoint sum of product form for a ZDD. Returns 1 if successful; 0
otherwise.
Side Effects: None
void
Cudd_zddPrintSubtable(
DdManager * table
)
Prints the ZDD table for debugging purposes.
Side Effects: None
DdNode *
Cudd_zddProduct(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the product of two covers represented by ZDDs. The result is also a
ZDD. Returns a pointer to the result if successful; NULL otherwise. The
covers on which Cudd_zddProduct operates use two ZDD variables for each
function variable (one ZDD variable for each literal of the variable). Those
two ZDD variables should be adjacent in the order.
Side Effects: None
long
Cudd_zddReadNodeCount(
DdManager * dd
)
Reports the number of nodes in ZDDs. This number always includes the two
constants 1 and 0.
Side Effects: None
void
Cudd_zddRealignDisable(
DdManager * unique
)
Disables realignment of ZDD order to BDD order.
Side Effects: None
void
Cudd_zddRealignEnable(
DdManager * unique
)
Enables realignment of the ZDD variable order to the BDD variable order
after the BDDs and ADDs have been reordered. The number of ZDD variables
must be a multiple of the number of BDD variables for realignment to make
sense. If this condition is not met, Cudd_ReduceHeap will return 0. Let
M be the ratio of the two numbers. For the purpose of
realignment, the ZDD variables from M*i to (M+1)*i-
1 are reagarded as corresponding to BDD variable i.
Realignment is initially disabled.
Side Effects: None
int
Cudd_zddRealignmentEnabled(
DdManager * unique
)
Returns 1 if the realignment of ZDD order to BDD order is enabled; 0
otherwise.
Side Effects: None
int
Cudd_zddReduceHeap(
DdManager * table, DD manager
Cudd_ReorderingTy heuristic, method used for reordering
int minsize bound below which no reordering occurs
)
Main dynamic reordering routine for ZDDs. Calls one of the possible
reordering procedures: Swapping Sifting Symmetric Sifting
For sifting and symmetric sifting it is possible to request reordering
to convergence. The core of all methods is the reordering procedure
cuddZddSwapInPlace() which swaps two adjacent variables. Returns 1 in case
of success; 0 otherwise. In the case of symmetric sifting (with and without
convergence) returns 1 plus the number of symmetric variables, in case of
success.
Side Effects: Changes the variable order for all ZDDs and clears the cache.
int
Cudd_zddShuffleHeap(
DdManager * table, DD manager
int * permutation required variable permutation
)
Reorders ZDD variables according to given permutation. The i-th entry of the
permutation array contains the index of the variable that should be brought
to the i-th level. The size of the array should be equal or greater to the
number of variables currently in use. Returns 1 in case of success; 0
otherwise.
Side Effects: Changes the ZDD variable order for all diagrams and clears the
cache.
DdNode *
Cudd_zddSubset0(
DdManager * dd,
DdNode * P,
int var
)
Computes the negative cofactor of a ZDD w.r.t. a variable. In terms of
combinations, the result is the set of all combinations in which the
variable is negated. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
DdNode *
Cudd_zddSubset1(
DdManager * dd,
DdNode * P,
int var
)
Computes the positive cofactor of a ZDD w.r.t. a variable. In terms of
combinations, the result is the set of all combinations in which the
variable is asserted. Returns a pointer to the result if successful; NULL
otherwise.
Side Effects: None
void
Cudd_zddSymmProfile(
DdManager * table,
int lower,
int upper
)
Prints statistics on symmetric ZDD variables.
Side Effects: None
DdNode *
Cudd_zddUnateProduct(
DdManager * dd,
DdNode * f,
DdNode * g
)
Computes the product of two unate covers represented as ZDDs. Unate covers
use one ZDD variable for each BDD variable. Returns a pointer to the result
if successful; NULL otherwise.
Side Effects: None
DdNode *
Cudd_zddUnion(
DdManager * dd,
DdNode * P,
DdNode * Q
)
Computes the union of two ZDDs. Returns a pointer to the result if
successful; NULL otherwise.
Side Effects: None
int
Cudd_zddVarsFromBddVars(
DdManager * dd, DD manager
int multiplicity how many ZDD variables are created for
each BDD variable
)
Creates one or more ZDD variables for each BDD variable. If some ZDD
variables already exist, only the missing variables are created. Parameter
multiplicity allows the caller to control how many variables are created for
each BDD variable in existence. For instance, if ZDDs are used to represent
covers, two ZDD variables are required for each BDD variable. The order of
the BDD variables is transferred to the ZDD variables. If a variable group
tree exists for the BDD variables, a corresponding ZDD variable group tree
is created by expanding the BDD variable tree. In any case, the ZDD
variables derived from the same BDD variable are merged in a ZDD variable
group. If a ZDD variable group tree exists, it is freed. Returns 1 if
successful; 0 otherwise.
Side Effects: None
DdNode *
Cudd_zddWeakDivF(
DdManager * dd,
DdNode * f,
DdNode * g
)
Modified version of Cudd_zddWeakDiv. This function may disappear in future
releases.
Side Effects: None
DdNode *
Cudd_zddWeakDiv(
DdManager * dd,
DdNode * f,
DdNode * g
)
Applies weak division to two ZDDs representing two covers. Returns a pointer
to the ZDD representing the result if successful; NULL otherwise. The result
of weak division depends on the variable order. The covers on which
Cudd_zddWeakDiv operates use two ZDD variables for each function variable
(one ZDD variable for each literal of the variable). Those two ZDD variables
should be adjacent in the order.
Side Effects: None
distrib
>
Mandriva
>
2010.0
>
i586
>
media
>
contrib-release
>
by-pkgid
>
a24e1a39141f9b4ca49bd1e2e23a54ba
>
files
>
1027
