Global Guidance for Local Generalization in Model Checking

SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of SPACER solver in Z3. Our empirical results show that GSPACER, SPACER extended with global guidance, is significantly more effective than both SPACER and sole global reasoning, and, furthermore, is insensitive to interpolation.Comment: Published in CAV 202

Global Guidance for Local Generalization in Model Checking

SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMT-based procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of Spacer solver in Z3. Our empirical results show that GSpacer, Spacer extended with global guidance, is significantly more effective than both Spacer and sole global reasoning, and, furthermore, is insensitive to interpolation

Syntax-Guided Synthesis for Lemma Generation in Hardware Model Checking

In this work we propose to use Syntax-Guided Synthesis (SyGuS) for lemma generation in a word-level IC3/PDR framework for bit-vector problems. Hardware model checking is moving from bit-level to word-level problems, and it is expected that model checkers can benefit when such high-level information is available. However, for bit-vectors, it is challenging to find a good word-level interpolation strategy for lemma generation, which hinders the use of word-level IC3/PDR algorithms. Our SyGuS-based procedure, SyGuS- , is tightly integrated with an existing word-level IC3/PDR framework . It includes a predefined grammar template and term production rules for generating candidate lemmas, and does not rely on any extra human inputs. Our experiments on benchmarks from the hardware model checking competition show that SyGuS- can outperform state-of-the-art Constrained Horn Clause (CHC) solvers, including those that implement bit-level IC3/PDR. We also show that SyGuS- and these CHC solvers can solve many instances faster than other leading word-level hardware model checkers that are not CHC-based. As a by-product of our work, we provide a translator Btor2CHC that enables the use of CHC solvers for general hardware model checking problems, and contribute representative bit-vector benchmarks to the CHC-solver community