Contract-Based Program Repair Without The Contracts: An Extended Study
Liushan Chen, Yu Pei, Carlo A. Furia · IEEE Transactions on Software Engineering · 2020
Most techniques for automated program repair (APR) use tests to drive the repair process; this makes them prone to generating spurious repairs that overfit the available tests unless additional information about expected program behavior is available. Our previous work onJaid, an APR technique for Java programs, showed that constructing detailed state abstractions—similar to those employed by techniques for programs with contracts—from plain Java code without any special annotations provides valuable additional information, and hence helps mitigate the overfitting problem. This paper extends the work onJaidwith a comprehensive experimental evaluation involving 693 bugs in three different benchmark suites. The evaluation shows, among other things, that: 1)Jaidis effective: it produced correct fixes for over 15 percent of all bugs, with a precision of nearly 60 percent; 2)Jaidis reasonably efficient: on average, it took less than 30 minutes to output a correct fix; 3)Jaidis competitive with the state of the art, as it fixed more bugs than any other technique, and 11 bugs that no other tool can fix; 4)Jaidis robust: its heuristics are complementary and their effectiveness does not depend on the fine-tuning of parameters. The experimental results also indicate the main trade-offs involved in designing an APR technique based on tests, as well as possible directions for further progress in this line of work.