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In mathematical logic,
proof compression In proof theory, an area of mathematical logic, proof compression is the problem of algorithmically compressing formal proofs. The developed algorithms can be used to improve the proofs generated by automated theorem proving tools such as SAT solver ...
by RecycleUnitsBar-Ilan, O.; Fuhrmann, O.; Hoory, S.; Shacham, O.; Strichman, O. ''Linear-time Reductions of Resolution Proofs''. Hardware and Software: Verification and Testing, p. 114–128, Springer, 2011. is a method for compressing propositional logic resolution proofs. Its main idea is to make use of intermediate (e.g. non input) proof results being unit
clauses In language, a clause is a constituent that comprises a semantic predicand (expressed or not) and a semantic predicate. A typical clause consists of a subject and a syntactic predicate, the latter typically a verb phrase composed of a verb with ...
, i.e. clauses containing only one literal. Certain proof nodes can be replaced with the nodes representing these unit clauses. After this operation the obtained graph is transformed into a valid proof. The output proof is shorter than the original while being equivalent or stronger.


Algorithms

The algorithms treat resolution proofs as directed acyclic graphs, where each node is labeled by a clause and each node has either one or two predecessors called parents. If a node has two parents it is also labeled with a propositional variable called the pivot, which was used to compute the nodes clause using resolution.
The following algorithm describes the replacement of nodes.
It is assumed that in the resolution proof for all non leaf nodes with two parent nodes, the left parent node contains the positive and the right parent node the negative pivot variable. The algorithm first iterates over all non leaf unit clauses and then over all non ancestor nodes of the proof. If the node's pivot element is the variable of the present unit clause's literal, one of the parent nodes can be replaced by the node corresponding to the unit clause. Because of the above assumption, if the literal is equal to the pivot, the left parent contains the literal and can be replaced by the unit clause node. If the literal is equal to the negation of the pivot the right parent is replaced. 1 function RecycleUnits(Proof P): 2 Let U be the set of non leaf nodes representing unit clauses 3 for each u \in U do 4 Mark the ancestors of u 5 for each unmarked n \in P do 6 let p be the pivot variable of n 7 let l be the literal contained in the clause of u 8 if p

l
then 9 replace the left parent of n with u 10 else if \neg p

l
then 11 replace the right parent of n with u In general after execution of this function the proof won't be a legal proof anymore. The following algorithm takes the root node of a proof and constructs a legal proof out of it. The computation begins with recursively calls to the children nodes. In order to minimize the algorithm calls, it is beingt kept track of which nodes were already visited. Note that a resolution proof can be seen as a general directed acyclic graph as opposed to a tree. After the recursive call the clause of the present node is updated. While doing so four different cases can occur. The present pivot variable can occur in both, the left, the right or in none of the parent nodes. If it occurs in both parent nodes the clause is calculated as resolvent of the parent clauses. If it is not present in one of the parent nodes the clause of this parent can be copied. If it misses in both parents one has to choose heuristically. 1 function ReconstructProof(Node n): 3 if n is visited return 4 mark n as visited 5 if n has no parents return 6 else if n has only one parent x then 7 ReconstructProof(x) 8 n.Clause = x.Clause 9 else 10 let l be the left and r the right parent node 11 let p be the pivot variable used to compute n 12 ReconstructProof(l) 13 ReconstructProof(r) 14 if p \in l.Clause and p \in r.Clause 15 n.Clause = Resolve(l,r,p) 16 else if p \in l.Clause and p \notin r.Clause 17 n.Clause = r.Clause 18 delete reference to l 19 else if p \in r.Clause and p \notin l.Clause 20 n.Clause = l.Clause 21 delete reference to r 22 else 23 let x \in \ and y \in \ \setminus \ //choose x heuristically 24 n.Clause = x.Clause 25 delete reference to y


Example

Consider the following resolution proof.
One intermediate result is C_8 which is representing the unit clause (-1). (1)\cfrac There is one non-ancestor node using the variable 1 as a pivot element: C_3. (1)\cfrac The literal -1 is contained in the right parent of this node and therefore this parent is replaced by C_8. The string ^* denotes a reference to the clause C_8 (the structure is now a directed acyclic graph rather than a tree). (1)\cfrac This structure is not a legal proof anymore, because C_3 is not the resolvent of C_1 and C_8. Therefore it has to be transformed into one again.
The first step is to update C_3. As the pivot variable 1 appears in both parent nodes, C_3 is computed as the resolvent of them. (1)\cfrac The left parent node of C_7 does not contain the pivot variable and therefore the clause of this parent is copied into the clause of C_7. The link between C_7 and C_4 is removed and since there are no other links to C_4 this node can be deleted. (1)\cfrac Again the left parent of C_9 does not contain the pivot variable and the same operation is performed as before. \cfrac Note: the reference ^* was replaced by the actual proof node C_8.
The result of this proof is the unit clause (3) which is a stronger result than the clause (3,5) of the original proof.


Notes

{{reflist Methods of proof