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Sepideh Asadi

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LPAR Conference 2018 Conference Paper

Function Summarization Modulo Theories

  • Sepideh Asadi
  • Martin Blicha
  • Grigory Fedyukovich
  • Antti E. J. Hyvärinen
  • Karine Even-Mendoza
  • Natasha Sharygina
  • Hana Chockler

SMT-based program verification can achieve high precision using bit-precise models or combinations of different theories. Often such approaches suffer from problems related to scalability due to the complexity of the underlying decision procedures. Precision is traded for performance by increasing the abstraction level of the model. As the level of abstraction increases, missing important details of the program model becomes problematic. In this paper we address this problem with an incremental verification approach that alternates precision of the program modules on demand. The idea is to model a program using the lightest possible (i. e. , less expensive) theories that suffice to verify the desired property. To this end, we employ safe over-approximations for the program based on both function summaries and light-weight SMT theories. If during verification it turns out that the precision is too low, our approach lazily strengthens all affected summaries or the theory through an iterative refinement procedure. The resulting summarization framework provides a natural and light-weight approach for carrying information between different theories. An experimental evaluation with a bounded model checker for C on a wide range of benchmarks demonstrates that our approach scales well, often effortlessly solving instances where the state-of-the-art model checker CBMC runs out of time or memory.

SAT Conference 2017 Conference Paper

Theory Refinement for Program Verification

  • Antti E. J. Hyvärinen
  • Sepideh Asadi
  • Karine Even-Mendoza
  • Grigory Fedyukovich
  • Hana Chockler
  • Natasha Sharygina

Abstract Recent progress in automated formal verification is to a large degree due to the development of constraint languages that are sufficiently light-weight for reasoning but still expressive enough to prove properties of programs. Satisfiability modulo theories (SMT) solvers implement efficient decision procedures, but offer little direct support for adapting the constraint language to the task at hand. Theory refinement is a new approach that modularly adjusts the modeling precision based on the properties being verified through the use of combination of theories. We implement the approach using an augmented version of the theory of bit-vectors and uninterpreted functions capable of directly injecting non-clausal refinements to the inherent Boolean structure of SMT. In our comparison to a state-of-the-art model checker, our prototype implementation is in general competitive, being several orders of magnitudes faster on some instances that are challenging for flattening, while computing models that are significantly more succinct.

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