Emergent Mind

Abstract

Modern automated program repair (APR) is well-tuned to finding and repairing bugs that introduce observable erroneous behavior to a program. However, a significant class of bugs does not lead to such observable behavior (e.g., liveness/termination bugs, non-functional bugs, and information flow bugs). Such bugs can generally not be handled with current APR approaches, so, as a community, we need to develop complementary techniques. To stimulate the systematic study of alternative APR approaches and hybrid APR combinations, we devise a novel bug classification system that enables methodical analysis of their bug detection power and bug repair capabilities. To demonstrate the benefits, we analyze the repair of termination bugs in sequential and concurrent programs. The study shows that integrating dynamic APR with formal analysis techniques, such as termination provers and software model checkers, reduces complexity and improves the overall reliability of these repairs.

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