2013 35th International Conference on Software Engineering (ICSE) (2013)
San Francisco, CA, USA
May 18, 2013 to May 26, 2013
Dongsun Kim , The Hong Kong University of Science and Technology, China
Jaechang Nam , The Hong Kong University of Science and Technology, China
Jaewoo Song , The Hong Kong University of Science and Technology, China
Sunghun Kim , The Hong Kong University of Science and Technology, China
Patch generation is an essential software maintenance task because most software systems inevitably have bugs that need to be fixed. Unfortunately, human resources are often insufficient to fix all reported and known bugs. To address this issue, several automated patch generation techniques have been proposed. In particular, a genetic-programming-based patch generation technique, GenProg, proposed by Weimer et al., has shown promising results. However, these techniques can generate nonsensical patches due to the randomness of their mutation operations. To address this limitation, we propose a novel patch generation approach, Pattern-based Automatic program Repair (Par), using fix patterns learned from existing human-written patches. We manually inspected more than 60,000 human-written patches and found there are several common fix patterns. Our approach leverages these fix patterns to generate program patches automatically. We experimentally evaluated Par on 119 real bugs. In addition, a user study involving 89 students and 164 developers confirmed that patches generated by our approach are more acceptable than those generated by GenProg. Par successfully generated patches for 27 out of 119 bugs, while GenProg was successful for only 16 bugs.
Fault location, Computer bugs, Context, Semantics, Manuals, Arrays, Maintenance engineering
D. Kim, J. Nam, J. Song and S. Kim, "Automatic patch generation learned from human-written patches," 2013 35th International Conference on Software Engineering (ICSE), San Francisco, CA, USA, 2013, pp. 802-811.