Testing satisfiability of CNF formulas by computing a stable set of points

We show that a conjunctive normal form (CNF) formula F is unsatisfiable if and only if there is a set of points of the Boolean space that is stable with respect to F. So testing the satisfiability of a CNF formula reduces to looking for a stable set of points (SSP). We give some properties of SSPs and describe a simple algorithm for constructing an SSP for a CNF formula. Building an SSP can be viewed as a natural way of search space traversal. This naturalness of search space examination allows one to make use of the regularity of CNF formulas to be checked for satisfiability. We illustrate this point by showing that if a CNF F formula is symmetric with respect to a group of permutations, it is very easy to make use of this symmetry when constructing an SSP. As an example, we show that the unsatisfiability of pigeon-hole CNF formulas can be proven by examining only a set of points whose size is quadratic in the number of holes. Finally, we introduce the notion of an SSP with excluded directions and sketch a procedure of satisfiability testing based on the construction of such SSPs.     

Generalizations of matched CNF formulas

A CNF formula is called matched if its associated bipartite graph (whose vertices are clauses and variables) has a matching that covers all clauses. Matched CNF formulas are satisfiable and can be recognized efficiently by matching algorithms. We generalize this concept and cover clauses by collections of bicliques (complete bipartite graphs). It turns out that such generalization indeed gives rise to larger classes of satisfiable CNF formulas which we term biclique satisfiable. We show, however, that the recognition of biclique satisfiable CNF formulas is NP-complete, and remains NP-hard if the size of bicliques is bounded. A satisfiable CNF formula is called var-satisfiable if it remains satisfiable under arbitrary replacement of literals by their complements. Var-satisfiable CNF formulas can be viewed as the best possible generalization of matched CNF formulas as every matched CNF formula and every biclique satisfiable CNF formula is var-satisfiable. We show that recognition of var-satisfiable CNF formulas is ₂ ^P-complete, answering a question posed by Kleine Büning and Zhao.     

Generalizations of matched CNF formulas

A CNF formula is called matched if its associated bipartite graph (whose vertices are clauses and variables) has a matching that covers all clauses. Matched CNF formulas are satisfiable and can be recognized efficiently by matching algorithms. We generalize this concept and cover clauses by collections of bicliques (complete bipartite graphs). It turns out that such generalization indeed gives rise to larger classes of satisfiable CNF formulas which we term biclique satisfiable. We show, however, that the recognition of biclique satisfiable CNF formulas is NP-complete, and remains NP-hard if the size of bicliques is bounded. A satisfiable CNF formula is called var-satisfiable if it remains satisfiable under arbitrary replacement of literals by their complements. Var-satisfiable CNF formulas can be viewed as the best possible generalization of matched CNF formulas as every matched CNF formula and every biclique satisfiable CNF formula is var-satisfiable. We show that recognition of var-satisfiable CNF formulas is _P ² P-complete, answering a question posed by Kleine Büning and Zhao.     

Minimal unsatisfiable formulas with bounded clause-variable difference are fixed-parameter tractable

Recognition of minimal unsatisfiable CNF formulas (unsatisfiable CNF formulas which become satisfiable if any clause is removed) is a classical D^P-complete problem. It was shown recently that minimal unsatisfiable formulas with n variables and n+k clauses can be recognized in time . We improve this result and present an algorithm with time complexity ; hence the problem turns out to be fixed-parameter tractable (FTP) in the sense of Downey and Fellows (Parameterized Complexity, 1999).Our algorithm gives rise to a fixed-parameter tractable parameterization of the satisfiability problem: If for a given set of clauses F, the number of clauses in each of its subsets exceeds the number of variables occurring in the subset at most by k, then we can decide in time whether F is satisfiable; k is called the maximum deficiency of F and can be efficiently computed by means of graph matching algorithms. Known parameters for fixed-parameter tractable satisfiability decision are tree-width or related to tree-width. Tree-width and maximum deficiency are incomparable in the sense that we can find formulas with constant maximum deficiency and arbitrarily high tree-width, and formulas where the converse prevails.     

On Skolemization in constrained logics

Quantification in first-order logic always involves all elements of the universe. However, it is often more natural to just quantify over those elements of the universe which satisfy a certain condition. Constrained logics therefore provide restricted quantifiers _X:R F and _X:R F whereX is a set of variables, and which can be read as F holds for all elements satisfying the restrictionR and F holds if there exists an element which satisfiesR. In order to test satisfiability of a set of such formulas by means of an appropriately extended resolution principle, one needs a procedure which transforms them into a set of clauses with constraints. Such a procedure essentially differs from the classical transformation of first-oder formulas into a set of clauses, in particular since quantification over the empty set may occur and since the needed Skolemization procedure has to take the restrictions of restricted quantifiers into account. In the first part of this article we present a procedure that transforms formulas with restricted quantifiers into a set of clauses with constraints while preserving satisfiability. The thus obtained clauses are of the formC R whereC is an ordinary clause andR is a restriction, and can be read as C holds ifR holds. These clauses can now be tested on unsatisfiability via the existingconstrained resolution principle. In the second part we generalize the constrained resolution principle in such a way that it allows for further optimization, and we introduce a combination of unification and constraint solving that can be employed to instantiate this kind of optimization.     

A hypergraph model for constraint logic programming and applications to bus drivers' scheduling

In a previous paper, a hypergraph model for the satisfiability of Datalog formulas was proposed. Here, we extend that approach in order to deal with a class ofconstraint logic programming (CLP) formulas, that is, Datalog formulas in the presence of constraints. A CLP formula is represented by means of a weighted hypergraph and the problem of evaluating this formula is reduced to a sequence of shortest path computations on hypergraphs. To evaluate the performance of this approach, the bus drivers' scheduling problem is formulated as the problem of checking the satisfiability of a CLP formula and it is solved by means of the hypergraph-based algorithm embedded within a local search procedure. Preliminary experimental results are quite encouraging and suggest that the proposed approach may provide an efficient way to tackle hard real-life combinatorial problems.This research was partially supported by the Progetto Finalizzato Trasporti 2 of the Italian National Research Council, under Contract No. 91.02479.PF74.     

Complexity of computing with extended propositional logic programs

In this paper we introduce the notion of anF-program, whereF is a collection of formulas. We then study the complexity of computing withF-programs.F-programs can be regarded as a generalization of standard logic programs. Clauses (or rules) ofF-programs are built of formulas fromF. In particular, formulas other than atoms are allowed as building blocks ofF-program rules. Typical examples ofF are the set of all atoms (in which case the class of ordinary logic programs is obtained), the set of all literals (in this case, we get the class of logic programs with classical negation [9]), the set of all Horn clauses, the set of all clauses, the set of all clauses with at most two literals, the set of all clauses with at least three literals, etc. The notions of minimal and stable models [16, 1, 7] of a logic program have natural generalizations to the case ofF-programs. The resulting notions are called in this paperminimal andstable answer sets. We study the complexity of reasoning involving these notions. In particular, we establish the complexity of determining the existence of a stable answer set, and the complexity of determining the membership of a formula in some (or all) stable answer sets. We study the complexity of the existence of minimal answer sets, and that of determining the membership of a formula in all minimal answer sets. We also list several open problems.This work was partially supported by National Science Foundation under grant IRI-9012902.This work was partially supported by National Science Foundation under grant CCR-9110721.     

A New Lower Bound on the Maximum Number of Satisfied Clauses in Max-SAT and Its Algorithmic Applications

A pair of unit clauses is called conflicting if it is of the form (x), $(\bar{x})$ . A CNF formula is unit-conflict free (UCF) if it contains no pair of conflicting unit clauses. Lieberherr and Specker (J. ACM 28:411?C421, 1981) showed that for each UCF CNF formula with m clauses we can simultaneously satisfy at least $\hat{ \varphi } m$ clauses, where $\hat{ \varphi }=(\sqrt{5}-1)/2$ . We improve the Lieberherr-Specker bound by showing that for each UCF CNF formula F with m clauses we can find, in polynomial time, a?subformula F?? with m?? clauses such that we can simultaneously satisfy at least $\hat{ \varphi } m+(1-\hat{ \varphi })m'+(2-3\hat {\varphi })n''/2$ clauses (in F), where n?? is the number of variables in F which are not in F??. We consider two parameterized versions of MAX-SAT, where the parameter is the number of satisfied clauses above the bounds m/2 and $m(\sqrt{5}-1)/2$ . The former bound is tight for general formulas, and the later is tight for UCF formulas. Mahajan and Raman (J. Algorithms 31:335?C354, 1999) showed that every instance of the first parameterized problem can be transformed, in polynomial time, into an equivalent one with at most 6k+3 variables and 10k clauses. We improve this to 4k variables and $(2\sqrt{5}+4)k$ clauses. Mahajan and Raman conjectured that the second parameterized problem is fixed-parameter tractable (FPT). We show that the problem is indeed FPT by describing a polynomial-time algorithm that transforms any problem instance into an equivalent one with at most $(7+3\sqrt{5})k$ variables. Our results are obtained using our improvement of the Lieberherr-Specker bound above.     

正则(3,4)-CNF公式的社区结构

通过构造适当的极小不可满足公式以实现在多项式时间内将3-CNF公式归约转换为一个正则(3,4)-CNF公式,转换后的公式与原公式具有相同的可满足性,同时公式的结构也发生相应的变化。图的社区结构反映了图的模块特性,文中将CNF公式转化为相应的图,研究公式图的模块特性与公式某些性质之间的关系。将归约前后的两类公式转换为相应的图并研究其模块特性,发现转换后得到的正则(3,4)-CNF公式具有较高的模块度。此外,在使用DPLL(Davis Putnam Logemann Loveland)算法求解CNF公式的过程中,发生冲突时利用冲突驱动子句学习策略,得到一个学习子句并将其添加到原公式中,使得原公式的模块度降低。研究发现:将DPLL算法与冲突驱动子句学习策略结合应用到正则(3,4)-CNF公式时,其学习子句所包含的绝大部分变元位于不同的社区中。     

A decomposition based algorithm for maximal contractions

This paper proposes a decomposition based algorithm for revision problems in classical propositional logic. A set of decomposing rules are presented to analyze the satisfiability of formulas. The satisfiability of a formula is equivalent to the satisfiability of a set of literal sets. A decomposing function is constructed to calculate all satisfiable literal sets of a given formula. When expressing the satisfiability of a formula, these literal sets are equivalent to all satisfied models of such formula. A revision algorithm based on this decomposing function is proposed, which can calculate maximal contractions of a given problem. In order to reduce the memory requirement, a filter function is introduced. The improved algorithm has a good performance in both time and space perspectives.     

Homogenization and the polynomial calculus

In standard implementations of the Gröbner basis algorithm, the original polynomials are homogenized so that each term in a given polynomial has the same degree. In this paper, we study the effect of homogenization on the proof complexity of refutations of polynomials derived from Boolean formulas in both the Polynomial Calculus (PC) and Nullstellensatz systems. We show that the PC refutations of homogenized formulas give crucial information about the complexity of the original formulas. The minimum PC refutation degree of homogenized formulas is equal to the Nullstellensatz refutation degree of the original formulas, whereas the size of the homogenized PC refutation is equal to the size of the PC refutation for the originals. Using this relationship, we prove nearly linear ((n/log n) vs. O(1)) separations between Nullstellensatz and PC degree, for a family of explicitly constructed contradictory 3CNF formulas. Previously, an (n ^1/2) separation had been proved for equations that did not correspond to any CNF formulas, and a log n separation for equations derived from kCNF formulas.     

The Complexity of Symmetry-Breaking Formulas

Symmetry-breaking formulas for a constraint-satisfaction problem are satisfied by exactly one member (e.g., the lexicographic leader) from each set of symmetrical points in the search space. Thus, the incorporation of such formulas can accelerate the search for a solution without sacrificing satisfiability. We study the computational complexity of generating lex-leader formulas. We show, even for abelian symmetry groups, that the number of essential clauses in the natural lex-leader formula could be exponential. Furthermore, we show the intractability (NP-hardness) of finding any expression of lex-leadership without reordering the variables, even for elementary abelian groups with orbits of size 3. Nevertheless, using techniques of computational group theory, we describe a reordering relative to which we construct small lex-leader formulas for abelian groups.     

Formal Verification Techniques Based on Boolean Satisfiability Problem

This paper exploits Boolean satisfiability problem in equivalence checking and model checking respectively. A combinational equivalence checking method based on incremental satisfiability is presented. This method chooses the candidate equivalent pairs with some new techniques, and uses incremental satisfiability algorithm to improve its performance.By substituting the internal equivalent pairs and converting the equivalence relations into conjunctive normal form (CNF)formulas, this approach can avoid the false negatives, and reduce the search space of SAT procedure. Experimental results on ISCAS‘85 benchmark circuits show that, the presented approach is faster and more robust than those existed in literature.This paper also presents an algorithm for extracting of unsatisfiable core, which has an important application in abstraction and refinement for model checking to alleviate the state space explosion bottleneck. The error of approximate extraction is analyzed by means of simulation. An analysis reveals that an interesting phenomenon occurs, with the increasing density of the formula, the average error of the extraction is decreasing. An exact extraction approach for MU subformula, referred to as pre-assignment algorithm, is proposed. Both theoretical analysis and experimental results show that it is more efficient.     

不可满足公式的同态证明系统

合取范式(CNF)公式H到F的同态φ是一个从H的文字集合到F的文字集合的映射,并保持补运算和子句映到子句.同态映射保持一个公式的不可满足性.一个公式是极小不可满足的是指该公式本身不可满足,而且从中删去任意一个子句后得到的公式可满足.MU(1)是子句数与变元数的差等于1的极小不可满足公式类.一个三元组(H,φ,F)称为的一个来自H的同态证明,如果φ是一个从H到F的同态.利用基础矩阵的方法证明了:一个不可满足公式F的树消解证明,可以在多项式时间内转换成一个来自MU(1)中公式的同态证明.从而,由MU(1)中的公式构成的同态证明系统是完备的,并且由MU(1)中的公式构成的同态证明系统与树消解证明系统之间是多项式等价的.     

SLS算法求解平衡正则(k,2r)-CNF公式

可满足性问题的求解算法和结构性质研究是计算机科学中重要问题之一，为寻求某些CNF公式子类问题有效算法或算法改进途径，对公式的结构加以某些限制，其中限定子句长度为恒定常数和变元出现次数是常见的处理方式。研究具有正则结构且每个变元正负出现均衡的结构化公式的可满足性问题求解，其随机生成模型的构建及随机实验测试有助于观察解分布状况。并且，随机局部搜索算法在求解具有一定规则结构CNF公式实例中具有良好效率。本文集中研究平衡正则(k, 2r)-CNF公式的求解问题，即限制每个子句的长度为k，每个变元出现的次数为偶数2r,并且每个变元正负出现的次数在相等情况下的可满足性问题求解。给出BR(n,  k, 2r)模型，以此模型来生成具有特殊结构的平衡正则(k, 2r)-CNF公式实例，利用随机局部搜索算法求解问题。通过限制初始指派的0文字和1文字各占一半且均匀生成，以WalkSAT算法和NSAT算法做实验对比，发现对于平衡正则(k, 2r)-CNF公式，实例具有明显效率。     

On exact selection of minimally unsatisfiable subformulae

A minimally unsatisfiable subformula (MUS) is a subset of clauses of a given CNF formula which is unsatisfiable but becomes satisfiable as soon as any of its clauses is removed. The selection of a MUS is of great relevance in many practical applications. This expecially holds when the propositional formula encoding the application is required to have a well-defined satisfiability property (either to be satisfiable or to be unsatisfiable). While selection of a MUS is a hard problem in general, we show classes of formulae where this problem can be solved efficiently. This is done by using a variant of Farkas lemma and solving a linear programming problem. Successful results on real-world contradiction detection problems are presented.     

Solution Validation and Extraction for QBF Preprocessing

In the context of reasoning on quantified Boolean formulas (QBFs), the extension of propositional logic with existential and universal quantifiers, it is beneficial to use preprocessing for solving QBF encodings of real-world problems. Preprocessing applies rewriting techniques that preserve (satisfiability) equivalence and that do not destroy the formula’s CNF structure. In many cases, preprocessing either solves a formula directly or modifies it such that information helpful to solvers becomes better visible and irrelevant information is hidden. The application of a preprocessor, however, prevented the extraction of proofs for the original formula in the past. Such proofs are required to independently validate the correctness of the preprocessor’s rewritings and the solver’s result as well as for the extraction of solutions in terms of Skolem functions. In particular for the important technique of universal expansion efficient proof checking and solution generation was not possible so far. This article presents a unified proof system with three simple rules based on quantified resolution asymmetric tautology (\(\mathsf {QRAT}\)). In combination with an extended version of universal reduction, we use this proof system to efficiently express current preprocessing techniques including universal expansion. Further, we develop an approach for extracting Skolem functions. We equip the preprocessor bloqqer with \(\mathsf {QRAT}\) proof logging and provide a proof checker for \(\mathsf {QRAT}\) proofs which is also able to extract Skolem functions.     

Modified ant colony algorithm for constructing finite state machines from execution scenarios and temporal formulas

We solve the problem of constructing extended finite state machines with execution scenarios and temporal formulas. We propose a new algorithm pstMuACO that combines a scenario filtering procedure, an exact algorithm efsmSAT for constructing finite state machines from execution scenarios based on a reduction to the Boolean satisfiability problem, and a parallel ant colony algorithm pMuACO. Experiments show that constructing several initial solutions for the ant colony algorithm with reduced sets of scenarios significantly reduces the total time needed to find optimal solutions. The proposed algorithm can be used for automated construction of reliable control systems.     

APTL公式的可满足性检查工具

交替投影时序逻辑（Alternating Projection Temporal Logic,简称APTL）公式简单易懂,表达能力强;不仅可以描述经典时序逻辑LTL可以描述的性质,而且可以描述与区间相关的顺序和循环性质以及开放系统和多智能体系统中与博弈相关的性质.在验证系统是否满足所给的APTL公式所描述的性质之前需要检查公式的可满足性.本文根据检查APTL公式的可满足性的方法^[1],开发实现了工具APTL2BCG.具体细节如下：首先,利用公式P的范式构造P的标记范式图（Labeled Normal Form Graph,简称LNFG）;然后,将LNFG转化为广义的基于并发博弈结构的交替Büchi自动机（Generalized alternating Büchi automaton over Concurrent Game structure,简称GBCG）;最后,将GBCG转化为基于并发博弈结构的交替Büchi自动机（alternating Büchi automaton over Concurrent Game structure,简称BCG）并且化为最简形式并检查公式P的可满足性.