Evaluating Partial Correctness of Programs in Automated Program Repair

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@InProceedings{Ito:2021:GCCE,

• author = "Yusaku Ito and Hironori Washizaki and Kazunori Sakamoto and Yoshiaki Fukazawa",
• title = "Evaluating Partial Correctness of Programs in Automated Program Repair",
• booktitle = "2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)",
• year = "2021",
• pages = "742--743",
• abstract = "Genetic programming-based automated program repair is actively studied as a bug fixing method. The existing methods evaluates randomly generated solution candidates using the success rate of test suites. However, the candidates are sometimes evaluated inaccurately. This study proposes a method to more appropriately judge the correctness of program candidates. The proposed method verifies the correctness of the intermediate calculation process using statements to check the predicted conditions for internal variables. In an experiment involving the Defects4J dataset, the execution time was reduced in 15 of the 23 bugs.",
• keywords = "genetic algorithms, genetic programming, genetic improvement, APR",
• DOI = "doi:10.1109/GCCE53005.2021.9621861",
• ISSN = "2378-8143",
• month = oct,
• notes = "Also known as \cite{9621861}",

}

Genetic Programming entries for Yusaku Ito Hironori Washizaki Kazunori Sakamoto Yoshiaki Fukazawa

Citations