What’s Decidable About Arrays?

In this paper, we present the logic of Counter Arithmetic with Lambda Expressions and Uninterpreted Functions (CLU). CLU generalizes the logic of equality with uninterpreted functions (EUF) with constrained lambda expressions, ordering, and successor and predecessor functions. In addition to modeling pipelined processors that EUF has proved useful for, CLU can be used to model many infinite-state systems including those with infinite memories, finite and infinite queues including lossy channels, and networks of identical processes. Even with this richer expressive power, the validity of a CLU formula can be efficiently decided by translating it to a propositional formula, and then using Boolean methods to check validity. We give theoretical and empirical evidence for the efficiency of our decision procedure. We also describe verification techniques that we have used on a variety of systems, including an out-of-order execution unit and the load-store unit of an industrial microprocessor.

Lower bounds are established on the computational complexity of the decision problem and on the inherent lengths of proofs for two classical decidable theories of logic: the first-order theory of the real numbers under addition, and Presburger arithmetic — the first-order theory of addition on the natural numbers. There is a fixed constant c > 0 such that for every (nondeterministic) decision procedure for determining the truth of sentences of real addition and for all sufficiently large n, there is a sentence of length n for which the decision procedure runs for more than 2cn steps. In the case of Presburger arithmetic, the corresponding bound is \({2^{{2^{cn}}}}\). These bounds apply also to the minimal lengths of proofs for any complete axiomatization in which the axioms are easily recognized.KeywordsDecision ProcedureFinite Abelian GroupScanning HeadBinary WordReal AdditionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We describe a simplifier for use in program manipulation and verification. The simplifier finds a normal form for any expression over the language consisting of individual variables, the usual boolean connectives, the conditional function cond (denoting if-then-else), the integers (numerals), the arithmetic functions and predicates +, - and ≤, the LISP constants, functions and predicates nil, car, cdr, cons and atom, the functions store and select for storing into and selecting from arrays, and uninterpreted function symbols. Individual variables range over the union of the rationals, the set of arrays, the LISP s-expressions and the booleans true and false. The constant, function and predicate symbols take their natural interpretations.The simplifier is complete; that is, it simplifies every valid formula to true. Thus it is also a decision procedure for the quantifier-free theory of rationals, arrays and s-expressions under the above functions and predicates.The organization of the simplifier is based on a method for combining decision algorithms for several theories into a single decision algorithm for a larger theory containing the original theories. More precisely, given a set S of functions and predicates over a fixed domain, a satisfiability program for S is a program which determines the satisfiability of conjunctions of literals (signed atomic formulas) whose predicates and function signs are in S. We give a general procedure for combining satisfiability programs for sets S and T into a single satisfiability program for S ∪ T, given certain conditions on S and T. We show how a satisfiability program for a set S can be used to write a complete simplifier for expressions containing functions and predicates of S as well as uninterpreted function symbols.The simplifier described in this paper is currently used in the Stanford Pascal Verifier.

Inspired by Boyer and Moore''s approach for generating induction schemes based on terminating function definitions, Zhang, Kapur and Krishnamoorthy introduced a cover set method for designing induction schemes for automating proofs by induction from specifications expressed as equations and conditional equations. This method has been implemented in the theorem prover Rewrite Rule Laboratory (RRL) and a proof management system Tecton built on top of em RRL, and it has been used to prove many nontrivial theorems and reason about sequential as well as parallel programs. The cover set method is based on the assumption that a function symbol is defined using a finite set of terminating (conditional or unconditional) rewrite rules. The left side of the rules are then used to design different cases of an induction scheme, and recursive calls to the function made in the right side can be used to design appropriate instantiations for generating induction hypotheses. A weakness of this method is that it relies on syntactic unification for generating an induction scheme for a conjecture. This paper goes a step further by proposing semantic analysis for generating an induction scheme for a conjecture from a cover set. We discuss the use of a decision procedure for Presburger arithmetic (quantifier-free theory of numbers with the addition operation and relational predicates , , =, ) for performing semantic analysis about numbers. The decision procedure is used to generate appropriate induction schemes for a conjecture using cover sets of function taking numbers as arguments. This extension of the cover set method automates proofs of many theorems which otherwise, require human guidance and hints. The effectiveness of the method is demonstrated using some examples which commonly arise in reasoning about specifications and programs. It is also shown how semantic analysis using a Presburger arithmetic decision procedure can be used for checking the completeness of a cover set of a function defined using operations such as check, many function definitions used in a proof of the prime factorization theorem stating that every number can be factored uniquely into prime factors, which had to be checked manually, can now be checked automatically in procedure for guiding generalization for generating conjectures and merging induction schemes is also illustrated.

Recent improvements in propositional satisfiability techniques (SAT) made it possible to tackle successfully some hard real-world problems (e.g., model-checking, circuit testing, propositional planning) by encoding into SAT. However, a purely Boolean representation is not expressive enough for many other real-world applications, including the verification of timed and hybrid systems, of proof obligations in software, and of circuit design at RTL level. These problems can be naturally modeled as satisfiability in linear arithmetic logic (LAL), that is, the Boolean combination of propositional variables and linear constraints over numerical variables. In this paper we present MathSAT, a new, SAT-based decision procedure for LAL, based on the (known approach) of integrating a state-of-the-art SAT solver with a dedicated mathematical solver for LAL. We improve MathSAT in two different directions. First, the top?level line procedure is enhanced and now features a tighter integration between the Boolean search and the mathematical solver. In particular, we allow for theory-driven backjumping and learning, and theory-driven deduction; we use static learning in order to reduce the number of Boolean models that are mathematically inconsistent; we exploit problem clustering in order to partition mathematical reasoning; and we define a stack-based interface that allows us to implement mathematical reasoning in an incremental and backtrackable way. Second, the mathematical solver is based on layering; that is, the consistency of (partial) assignments is checked in theories of increasing strength (equality and uninterpreted functions, linear arithmetic over the reals, linear arithmetic over the integers). For each of these layers, a dedicated (sub)solver is used. Cheaper solvers are called first, and detection of inconsistency makes call of the subsequent solvers superfluous. We provide a through experimental evaluation of our approach, by taking into account a large set of previously proposed benchmarks. We first investigate the relative benefits and drawbacks of each proposed technique by comparison with respect to a reference option setting. We then demonstrate the global effectiveness of our approach by a comparison with several state-of-the-art decision procedures. We show that the behavior of MathSAT is often superior to its competitors, both on LAL and in the subclass of difference logic.

We consider the first-order theory whose language has as nonlogical symbols the constant symbols 0 and 1, the binary relation symbols = and This theory of integers under addition is commonly called the 'Presburger Arithmetic' and is known to be decidable for truth [Presburger (1929), Hilbert and Bernays (1968)]. We prove here that there exists a decision procedure for this theory, involving quantifier elimination, for which there is a superexponential upper bound on the size of formula produced when all variables have been eliminated.

This paper considers the satisfiability problem of symbolic heaps in separation logic with Presburger arithmetic and inductive definitions. First the system without any restrictions is proved to be undecidable. Secondly this paper proposes some syntactic restrictions for decidability. These restrictions are identified based on a new decidable subsystem of Presburger arithmetic with inductive definitions. In the subsystem of arithmetic, every inductively defined predicate represents an eventually periodic set and can be eliminated. The proposed system is quite general as it can handle the satisfiability of the arithmetical parts of fairly complex predicates such as sorted lists and AVL trees. Finally, we prove the decidability by presenting a decision procedure for symbolic heaps with the restricted inductive definitions and arithmetic.

Decision procedures can be either theory-specific, e.g., Presburger arithmetic, or theory-generic, applying to an infinite number of user-definable theories. Variant satisfiability is a theory-generic procedure for quantifier-free satisfiability in the initial algebra of an order-sorted equational theory \((\varSigma ,E \cup B)\) under two conditions: (i) \(E \cup B\) has the finite variant property and B has a finitary unification algorithm; and (ii) \((\varSigma ,E \cup B)\) protects a constructor subtheory \((\varOmega ,E_{\varOmega } \cup B_{\varOmega })\) that is OS-compact. These conditions apply to many user-definable theories, but have a main limitation: they apply well to data structures, but often do not hold for user-definable predicates on such data structures. We present a theory-generic satisfiability decision procedure, and a prototype implementation, extending variant-based satisfiability to initial algebras with user-definable predicates under fairly general conditions.

Coq is a proof assistant featuring a tactic-based interactive theorem prover. The latest incarnation comes with over 150 tactics that assist the user in developing a formal proof. These tactics range from the simple and mundane to the ‘allpowerful’. Some examples from the latter category are the omega tactic that solves a goal in Presburger arithmetic and the ring and field tactics that solve identities modulo associativity and commutativity in ring and field structures. This paper presents a new proof tactic that decides equalities and inequalities between terms over lattices. It uses a decision procedure that is a variation on Whitman’s algorithm and is implemented using a technique known as proof by reflection. We will paint the essence of the approach in broad strokes and discuss the use of certified functional programs to aid the automation of formal reasoning. This paper makes three contributions. Firstly it serves an an introduction to using proof by reflection approach Coq. This utilizes the Ltac language and two recent extensions to the Coq system: type classes and the PROGRAM extension. Secondly it gives a certified implementation of Whitman’s algorithm in Coq, with proofs of correctness and termination. Thirdly, the final product of this work is a useable proof tactic that can be applied to proof goals involving equalities and inequalities in lattice theory. The rest of the paper is organized as follows: Section 2 will give a short introduction to Coq, highlighting the concept of a proof term, and will refresh the necessary details of lattice theory. We will give a motivation for the problem in Section 3, and a Coq-based introduction to free lattices along with the decision

According to the theory of yin-yang, everything in this universe is conflictingly and inter relatedly united, deep connected, exchangeable with two opposite dynamics i.e. yang and yin. Traditional Chinese medicine (TCM) makes heavy use of the five elements principle. The idea of elements, the rule of transmission, and the law of similarity—all of which were common at the time—are said to have served as the foundation for the development of this five elements theory. Most likely, based on the principle of contagiousness the coupling of the internal organs was done. The internally linked organs were divided into five components according to the similarity rule, and theory of five elements was contrasted with a variety of objects, including seasons, colors, tastes, sentiments, and so forth. In this review we have complied this concept also dealing with the types of Qi, the vital energy associated with Yin-Yang in regulating various body functions.

Recursive algebraic data types (term algebras, ADTs) are one of the most well-studied theories in logic, and find application in contexts including functional programming, modelling languages, proof assistants, and verification. At this point, several state-of-the-art theorem provers and SMT solvers include tailor-made decision procedures for ADTs, and version~2.6 of the SMT-LIB standard includes support for ADTs. We study an extremely simple approach to decide satisfiability of ADT constraints, the reduction of ADT constraints to equisatisfiable constraints over uninterpreted functions (EUF) and linear integer arithmetic (LIA). We show that the reduction approach gives rise to both decision and Craig interpolation procedures in (extensions of) ADTs.

The design of decision procedures for first-order theories and their combinations has been a very active research subject for thirty years; it has gained practical importance through the development of SMT (satisfiability modulo theories) solvers. Most results concentrate on combining decision procedures for data structures such as theories for arrays, bitvectors, fragments of arithmetic, and uninterpreted functions. In particular, the well-known Nelson-Oppen scheme for the combination of decision procedures requires the signatures to be disjoint and each theory to be stably infinite; every satisfiable set of literals in a stably infinite theory has an infinite model.In this paper we consider some of the best-known decidable fragments of first-order logic with equality, including the Löwenheim class (monadic FOL with equality, but without functions), Bernays-Schönfinkel-Ramsey theories (finite sets of formulas of the form ∃ * ∀ * ϕ, where ϕ is a function-free and quantifier-free FOL formula), and the two-variable fragment of FOL. In general, these are not stably infinite, and the Nelson-Oppen scheme cannot be used to integrate them into SMT solvers. Noticing some elementary results about the cardinalities of the models of these theories, we show that they can nevertheless be combined with almost any other decidable theory.

We present a new approach for performing predicate abstraction based on symbolic decision procedures. A symbolic decision procedure for a theory T (SDPT) takes sets of predicates G and E and symbolically executes a decision procedure for T on G′ ∪ {– e | e ∈ E}, for all the subsets G′ of G. The result of SDPT is a shared expression (represented by a directed acyclic graph) that implicitly represents the answer to a predicate abstraction query. We present symbolic decision procedures for the logic of Equality and Uninterpreted Functions(EUF) and Difference logic (DIF) and show that these procedures run in pseudo-polynomial (rather than exponential) time. We then provide a method to construct SDP's for simple mixed theories (including EUF + DIF) using an extension of the Nelson-Oppen combination method. We present preliminary evaluation of our procedure on predicate abstraction benchmarks from device driver verification in SLAM.

This paper presents two decidability results on the validity checking problem for entailments of symbolic heaps in separation logic with Presburger arithmetic and arrays. The first result is for a system with arrays and existential quantifiers. The correctness of the decision procedure is proved under the condition that sizes of arrays in the succedent are not existentially quantified. This condition is different from that proposed by Brotherston et al. in 2017 and one of them does not imply the other. The main idea is a novel translation from an entailment of symbolic heaps into a formula in Presburger arithmetic. The second result is the decidability for a system with both arrays and lists. The key idea is to extend the unroll collapse technique proposed by Berdine et al. in 2005 to arrays and arithmetic as well as double-linked lists.Comment: arXiv admin note: text overlap with arXiv:1708.06696

Complexity, convexity and combinations of theories