概要: Automated program repair is a promising way to reduce costs on program debugging dramatically. Some repair techniques with genetic algorithm have been proposed, and they were able to fix several dozen of actual bugs in open source software. However, existing techniques occasionally take a long time to generate a repaired version of a given program. The dominant factor for that is generating so many programs that do not pass given test cases. In this research, we are trying to generate a repaired program, which passes all the test cases, in less time. Our key idea is using code similarity to select code lines to be inserted into a given program. More concretely, we propose to select code lines in code regions similar to the faulty code regions. In existing techniques, code lines for insertion are randomly selected from a given program. Currently, we are still in an early stage of this research. In this paper, we report some promising results of our pilot study, which show that using code similarity is very effective to generate repaired programs in less time. タグ: Automated, program, repair, Source, code, analysis, Genetic, programming

@inproceedings{HarukiYokoyama2016,
  author = {Haruki Yokoyama and Yoshiki Higo and Keisuke Hotta and Takafumi Ohta and Kozo Okano and Shinji Kusumoto},
  title = {Toward Improving Ability to Repair Bugs Automatically –A Patch Candidate Location Mechanism Using Code Similarity–},
  booktitle = {31st ACM Symposium on Applied Computing},
  pages = {1364--1370},
  year = {2016},
  month = {apr}
}