Enhancing B Language Reasoners with SAT and SMT Techniques – BLaSST
The BLaSST project targets bridging combinatorial and symbolic techniques in automatic theorem proving, in particular for proof obligations generated from B models. It focuses on advancing the state of the art in automated reasoning, in particular SAT and SMT techniques, and on making these techniques available to software verification. More specifically, encoding techniques, optimized resolution techniques, model generation, and lemma suggestion will be considered. The expected scientific impact is a substantially higher degree of automation of solvers for expressive input languages by leveraging higher-order reasoning and enumerative instantiations over finite domains, as well as useful feedback for verification conditions that cannot be proved. The effectiveness of the techniques developed in the project will be quantified by applying them to benchmark sets provided by the industrial partner. The industrial impact of BLaSST will be a higher productivity of proof engineers. The collections of benchmarks and the reasoning engines will be made openly available under permissive open-source licenses.
Project coordination
Stephan Merz (Centre de Recherche Inria Nancy - Grand Est)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partner
UMR 8188 CRIL - Centre de Recherche en Informatique de Lens
Inria Nancy Grand Est Centre de Recherche Inria Nancy - Grand Est
CLEARSY CLEARSY
ULiège Université de Liège / Institut Montefiore
Help of the ANR 479,585 euros
Beginning and duration of the scientific project:
February 2022
- 48 Months