Key points are not available for this paper at this time.
LTL solvers check the satisfiability of Linear-time Temporal Logic (LTL) formulas and are widely used for verifying and testing critical software systems. Thus, potential bugs in the solvers' implementations can have a significant impact. We present SpecBCFuzz, a fuzzing method for finding bugs in LTL solvers, that is guided by boundary conditions (BCs), corner cases whose (un)satisfiability depends on rare traces. SpecBCFuzz implements a search-based algorithm that fuzzes LTL formulas giving relevance to BCs. It integrates syntactic and semantic similarity metrics to explore the vicinity of the seeded formulas with BCs. We evaluate SpecBCFuzz on 21 different configurations (including the latest and past releases) of four mature and state-of-the-art LTL solvers (NuSMV, Black, Aalta, and PLTL) that implement a diverse set of satisfiability algorithms. SpecBCFuzz produces 368,716 bug-triggering formulas, detecting bugs in 18 out of the 21 solvers' configurations we study. Overall, SpecBCFuzz reveals: soundness issues (wrong answers given by a solver) in Aalta and PLTL; crashes, e.g., segmentation faults, in NuSMV, Black and Aalta; flaky behaviors (different responses across re-runs of the solver on the same formula) in NuSMV and Aalta; performance bugs (large time performance degradation between successive versions of the solver on the same formula) in Black, Aalta and PLTL; and no bug in NuSMV BDD (all versions), suggesting that the latter is currently the most robust solver.
Carvalho et al. (Fri,) studied this question.