SEMANTIC PROGRAM REPAIR

Abstract

Debugging consumes significant amount of resources in software development projects. Automated program repair is a promising technology that can reduce the cost of debugging by automatically eliminating program defects. Early test-driven program repair techniques that scaled to large real-world programs utilized syntactic search without comprehending the meaning of the program and the defect. Although such techniques demonstrated encouraging results, they suffer from several limitations. First, since a test suite is an incomplete specification, automatically generated patches may not correspond to user intentions but merely overfit the tests. Secondly, syntactic techniques scale to relatively small search spaces and therefore can address only a small number of defects. This work introduces a series of techniques to address the aforementioned challenges of automated program repair. These techniques are united by the idea of revealing the underlying program structure by means of semantic analysis. Our experiments showed that the proposed techniques advance the state of the art of program repair. Semantic analysis helps to increase the quality of automatically generated patches. Apart from that, it enables program repair to scale to larger search spaces and consequently address more defect.