Fault localization by abstract interpretation and its applications

Fault localization aims to automatically identify the cause of an error in a program by localizing the error to a relatively small part of the program. In this paper, we present a novel technique for automated fault localization via error invariants inferred by abstract interpretation. An error invariant for a location in an error program over-approximates the reachable states at the given location that may produce the error, if the execution of the program is continued from that location. Error invariants can be used for statement-wise semantic slicing of error programs and for obtaining concise error explanations. We use an iterative refinement sequence of backward–forward static analyses by abstract interpretation to compute error invariants, which are designed to explain why an error program violates a particular assertion.

Furthermore, we present a practical application of the fault localization technique for automatic repair of programs. Given an erroneous program, we first use the fault localization to automatically identify statements relevant for the error, and then repeatedly mutate the expressions in those relevant statements until a correct program that satisfies all assertions is found. All other statements classified by the fault localization as irrelevant for the error are not mutated in the program repair process. This way, we significantly reduce the search space of mutated programs without losing any potentially correct program, and so locate a repaired program much faster than a program repair without fault localization.

We have developed a prototype tool for automatic fault localization and repair of C programs. We demonstrate the effectiveness of our approach to localize errors in realistic C programs, and to subsequently repair them. Moreover, we show that our approach based on combining fault localization and code mutations is significantly faster that the previous program repair approach without fault localization.