Proceedings paper

CHC Model Validation with Proof Guarantees
R. Otoni, M. Blicha, P. Eugster, N. Sharygina
iFM 2023

Formal verification tooling increasingly relies on logic solvers as automated reasoning engines. A point of commonality among these solvers is the high complexity of their codebases, which makes bug occurrence disturbingly frequent. Tool competitions have showcased many examples of state-of-the-art solvers disagreeing on the satisfiability of logic formulas, be them solvers for Boolean satisfiability (SAT), satisfiability modulo theories (SMT), or constrained Horn clauses (CHC). The validation of solvers’ results is thus of paramount importance, in order to increase the confidence not only in the solvers themselves, but also in the tooling which they underpin. Among the formalisms commonly used by modern verification tools, CHC is one that has seen, at the same time, extensive practical usage and very little efforts in result validation. As one of the initial steps in addressing this issue, we propose and evaluate a two-layered validation approach for witnesses of CHC satisfiability. Our approach relies, first, on a proof producing SMT solver to validate a CHC model via a series of SMT queries, and, second, on a proof checker to validate the SMT solver’ s results. We developed a modular evaluation framework and assessed the approach’ s viability via large scale experimentation, comparing three CHC solvers, five SMT solvers, and four proof checkers. Our results indicate that the approach is feasible, with potential to be incorporated into CHC-based tooling, and also confirm the need for validation, with nine bugs being found in the tools used.

    title = {{CHC Model Validation with  Proof Guarantees}},
    author = {Otoni, Rodrigo and Blicha, Martin and Eugster, Patrick and Sharygina, Natasha},
    year = {2024},
    booktitle = {{iFM 2023}},
    editor = {Herber, Paula and Wijs, Anton},
    publisher = {Springer Nature Switzerland},
    series = {{Lecture Notes in Computer Science}},
    location = {Cham},
    doi = {10.1007/978-3-031-47705-8_4},
    isbn = {978-3-031-47705-8},
    pages = {62--81},