Legion: Best-First Concolic Testing

02/15/2020
by   Dongge Liu, et al.
0

Legion is a grey-box concolic tool that aims to balance the complementary nature of fuzzing and symbolic execution to achieve the best of both worlds. It proposes a variation of Monte Carlo tree search (MCTS) that formulates program exploration as sequential decisionmaking under uncertainty guided by the best-first search strategy. It relies on approximate path-preserving fuzzing, a novel instance of constrained random testing, which quickly generates many diverse inputs that likely target program parts of interest. In Test-Comp 2020, the prototype performed within 90

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