Leveraging syntax-related code for automated program repair

We present our automated program repair technique ssFix which leverages existing code (from a code database) that is syntax-related to the context of a bug to produce patches for its repair. Given a faulty program and a fault-exposing test suite, ssFix does fault localization to identify suspicious statements that are likely to be faulty. For each such statement, ssFix identifies a code chunk (or target chunk) including the statement and its local context. ssFix works on the target chunk to produce patches. To do so, it first performs syntactic code search to find candidate code chunks that are syntax-related, i.e., structurally similar and conceptually related, to the target chunk from a code database (or codebase) consisting of the local faulty program and an external code repository. ssFix assumes the correct fix to be contained in the candidate chunks, and it leverages each candidate chunk to produce patches for the target chunk. To do so, ssFix translates the candidate chunk by unifying the names used in the candidate chunk with those in the target chunk; matches the chunk components (expressions and statements) between the translated candidate chunk and the target chunk; and produces patches for the target chunk based on the syntactic differences that exist between the matched components and in the unmatched components. ssFix finally validates the patched programs generated against the test suite and reports the first one that passes the test suite. We evaluated ssFix on 357 bugs in the Defects4J bug dataset. Our results show that ssFix successfully repaired 20 bugs with valid patches generated and that it outperformed five other repair techniques for Java.