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arXiv · 1701.08466

Predicting SMT Solver Performance for Software Verification

Andrew Healy·Rosemary Monahan·James F. Power
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Abstract

The Why3 IDE and verification system facilitates the use of a wide range of Satisfiability Modulo Theories (SMT) solvers through a driver-based architecture. We present Where4: a portfolio-based approach to discharge Why3 proof obligations. We use data analysis and machine learning techniques on static metrics derived from program source code. Our approach benefits software engineers by providing a single utility to delegate proof obligations to the solvers most likely to return a useful result. It does this in a time-efficient way using existing Why3 and solver installations - without requiring low-level knowledge about SMT solver operation from the user.

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Andrew Healy, Rosemary Monahan, James F. Power. 2017-01-30. Predicting SMT Solver Performance for Software Verification. https://doi.org/10.4204/eptcs.240.2

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