Pending Constraints in Symbolic Execution for Better Exploration and Seeding

Abstract

Symbolic execution is a well established technique for software testing and analysis. However, scalability continues to be a challenge, both in terms of constraint solving cost and path explosion. In this work, we present a novel approach for symbolic execution, which can enhance its scalability by aggressively prioritising execution paths that are already known to be feasible, and deferring all other paths. We evaluate our technique on nine applications, including SQLite3, make and tcpdump and show it can achieve higher coverage for both seeded and non-seeded exploration.