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Register a new userSymbolic Automatic Relations and Their Applications to SMT and CHC Solving
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Added by
Ken Sakayori
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Despite the recent advance of automated program verification, reasoning about recursive data structures remains as a challenge for verification tools and their backends such as SMT and CHC solvers. To address the challenge, we introduce the notion of symbolic automatic relations (SARs), which combines symbolic automata and automatic relations, and inherits their good properties such as the closure under Boolean operations. We consider the satisfiability problem for SARs, and show that it is undecidable in general, but that we can construct a sound (but incomplete) and automated satisfiability checker by a reduction to CHC solving. We discuss applications to SMT and CHC solving on data structures, and show the effectiveness of our approach through experiments.
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A well-established approach to reasoning about loops during program analysis is to capture the effect of a loop by extracting recurrences from the loop; these express relationships between the values of variables, or program properties such as cost, on successive loop iterations. Recurrence solvers are capable of computing closed forms for some recurrences, thus deriving precise relationships capturing the complete loop execution. However, many recurrences extracted from loops cannot be solved, due to their having multiple recursive cases or multiple arguments. In the literature, several techniques for approximating the solution of unsolvable recurrences have been proposed. The approach presented in this paper is to define transformations based on regular path expressions and loop counters that (i) transform multi-path loops to single-path loops, giving rise to recurrences with a single recursive case, and (ii) transform multi-argument recurrences to single-argument recurrences, thus enabling the use of recurrence solvers on the transformed recurrences. Using this approach, precise solutions can sometimes be obtained that are not obtained by approximation methods.
CHC-COMP-21 is the fourth competition of solvers for Constrained Horn Clauses. In this year, 7 solvers participated at the competition, and were evaluated in 7 separate tracks on problems in linear integer arithmetic, linear real arithmetic, arrays, and algebraic data-types. The competition was run in March 2021 using the StarExec computing cluster. This report gives an overview of the competition design, explains the organisation of the competition, and presents the competition results.
We present Ultimate TreeAutomizer, a solver for satisfiability of sets of constrained Horn clauses. Constrained Horn clauses (CHC) are a fragment of first order logic with attractive properties in terms of expressiveness and accessibility to algorithmic solving. Ultimate TreeAutomizer is based on the techniques of trace abstraction, tree automata and tree interpolation. This paper serves as a tool description for TreeAutomizer in CHC-COMP 2019.
Satisfiability modulo theories (SMT) solvers have throughout the years been able to cope with increasingly expressive formulas, from ground logics to full first-order logic modulo theories. Nevertheless, higher-order logic within SMT is still little explored. One main goal of the Matryoshka project, which started in March 2017, is to extend the reasoning capabilities of SMT solvers and other automatic provers beyond first-order logic. In this preliminary report, we report on an extension of the SMT-LIB language, the standard input format of SMT solvers, to handle higher-order constructs. We also discuss how to augment the proof format of the SMT solver veriT to accommodate these new constructs and the solving techniques they require.
We introduce an approach that aims to combine the usage of satisfiability modulo theories (SMT) solvers with the Combinatory Logic Synthesizer (CL)S framework. (CL)S is a tool for the automatic composition of software components from a user-specified repository. The framework yields a tree grammar that contains all composed terms that comply with a target type. Type specifications for (CL)S are based on combinatory logic with intersection types. Our approach translates the tree grammar into SMT functions, which allows the consideration of additional domain-specific constraints. We demonstrate the usefulness of our approach in several experiments.
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