Interval counterexamples for loop invariant learning
Rongchen Xu, Fei He, Bow-Yaw Wang · 2020
Loop invariant generation has long been a challenging problem. Black-box learning has recently emerged as a promising method for inferring loop invariants. However, the performance depends heavily on the quality of collected examples. In many cases, only after tens or even hundreds of constraint queries, can a feasible invariant be successfully inferred.