{"title":"用GenExp修正指令表达式逻辑错误:一个遗传规划解决方案","authors":"M. Bekkouche","doi":"10.56415/csjm.v31.12","DOIUrl":null,"url":null,"abstract":"Correcting logical errors in a program is not simple even with the availability of an error locating tool. In this article, we introduce GenExp, a genetic programming approach to automate the task of repairing instruction expressions from logical errors. \\correction{Starting} from an error location specified by the programmer, we search for a replacement instruction that passes all test cases. Specifically, we generate expressions that will substitute the selected instruction expression until \\correction{we} obtain one that \\correction{corrects} the input program. \\correction{The search space is exponentially large, making exhaustive methods inefficient.} \\correction{Therefore, we utilize a genetic programming meta-heuristic that organizes the search process into stages, with each stage producing a group of individuals.} The results showed that our approach can find at least one plausible patch for almost all cases considered in experiments and outperforms a notable state-of-the-art error repair approach \\correction{like} ASTOR. Although our tool is slower than ASTOR, it \\correction{provides} greater precision in detecting plausible repairs, making it a suitable option for users who prioritize accuracy over speed.","PeriodicalId":262087,"journal":{"name":"Comput. Sci. J. Moldova","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correcting Instruction Expression Logic Errors with GenExp: A Genetic Programming Solution\",\"authors\":\"M. Bekkouche\",\"doi\":\"10.56415/csjm.v31.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Correcting logical errors in a program is not simple even with the availability of an error locating tool. In this article, we introduce GenExp, a genetic programming approach to automate the task of repairing instruction expressions from logical errors. \\\\correction{Starting} from an error location specified by the programmer, we search for a replacement instruction that passes all test cases. Specifically, we generate expressions that will substitute the selected instruction expression until \\\\correction{we} obtain one that \\\\correction{corrects} the input program. \\\\correction{The search space is exponentially large, making exhaustive methods inefficient.} \\\\correction{Therefore, we utilize a genetic programming meta-heuristic that organizes the search process into stages, with each stage producing a group of individuals.} The results showed that our approach can find at least one plausible patch for almost all cases considered in experiments and outperforms a notable state-of-the-art error repair approach \\\\correction{like} ASTOR. Although our tool is slower than ASTOR, it \\\\correction{provides} greater precision in detecting plausible repairs, making it a suitable option for users who prioritize accuracy over speed.\",\"PeriodicalId\":262087,\"journal\":{\"name\":\"Comput. Sci. J. Moldova\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comput. Sci. J. Moldova\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56415/csjm.v31.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comput. Sci. J. Moldova","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56415/csjm.v31.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Correcting Instruction Expression Logic Errors with GenExp: A Genetic Programming Solution
Correcting logical errors in a program is not simple even with the availability of an error locating tool. In this article, we introduce GenExp, a genetic programming approach to automate the task of repairing instruction expressions from logical errors. \correction{Starting} from an error location specified by the programmer, we search for a replacement instruction that passes all test cases. Specifically, we generate expressions that will substitute the selected instruction expression until \correction{we} obtain one that \correction{corrects} the input program. \correction{The search space is exponentially large, making exhaustive methods inefficient.} \correction{Therefore, we utilize a genetic programming meta-heuristic that organizes the search process into stages, with each stage producing a group of individuals.} The results showed that our approach can find at least one plausible patch for almost all cases considered in experiments and outperforms a notable state-of-the-art error repair approach \correction{like} ASTOR. Although our tool is slower than ASTOR, it \correction{provides} greater precision in detecting plausible repairs, making it a suitable option for users who prioritize accuracy over speed.