Vamshi Krishna Epuri, Sushma Sakala, Tae-Hyuk Ahn, Myoungkyu Song
{"title":"在不断发展的软件中管理重复程序变更的工具支持","authors":"Vamshi Krishna Epuri, Sushma Sakala, Tae-Hyuk Ahn, Myoungkyu Song","doi":"10.1049/IET-SEN.2018.5356","DOIUrl":null,"url":null,"abstract":"Software modification often requires consistent program changes, a group of similar, related changes, at multiple locations in a program. Developers are typically uneasy to (i) detect potential change anomalies such as omission errors or incorrect edits and (ii) determine related locations to apply consistent changes, which is a tedious and error-prone process. To address this problem, this study presents a technique for managing consistent program changes, checking and applying repetitive program transformation (CARP). Given program differencing results between original and edited program versions, CARP (i) infers change patterns to detect change anomalies, (ii) identifies required edit locations, and (iii) automatically applies adequate edits. It has been implemented in the context of the integrated development environment as an Eclipse plug-in. The authors evaluated CARP on three open-source projects and found that CARP detects seeded anomalies with 99.1% accuracy on average. Furthermore, it identifies change locations and transforms them with 98% accuracy. Their results show that CARP should help developers detect potential change anomalies in repetitive program changes and perform consistent changes automatically.","PeriodicalId":13395,"journal":{"name":"IET Softw.","volume":"25 1","pages":"447-455"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tool support for managing repetitive program changes in evolving software\",\"authors\":\"Vamshi Krishna Epuri, Sushma Sakala, Tae-Hyuk Ahn, Myoungkyu Song\",\"doi\":\"10.1049/IET-SEN.2018.5356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software modification often requires consistent program changes, a group of similar, related changes, at multiple locations in a program. Developers are typically uneasy to (i) detect potential change anomalies such as omission errors or incorrect edits and (ii) determine related locations to apply consistent changes, which is a tedious and error-prone process. To address this problem, this study presents a technique for managing consistent program changes, checking and applying repetitive program transformation (CARP). Given program differencing results between original and edited program versions, CARP (i) infers change patterns to detect change anomalies, (ii) identifies required edit locations, and (iii) automatically applies adequate edits. It has been implemented in the context of the integrated development environment as an Eclipse plug-in. The authors evaluated CARP on three open-source projects and found that CARP detects seeded anomalies with 99.1% accuracy on average. Furthermore, it identifies change locations and transforms them with 98% accuracy. Their results show that CARP should help developers detect potential change anomalies in repetitive program changes and perform consistent changes automatically.\",\"PeriodicalId\":13395,\"journal\":{\"name\":\"IET Softw.\",\"volume\":\"25 1\",\"pages\":\"447-455\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Softw.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/IET-SEN.2018.5356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Softw.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/IET-SEN.2018.5356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tool support for managing repetitive program changes in evolving software
Software modification often requires consistent program changes, a group of similar, related changes, at multiple locations in a program. Developers are typically uneasy to (i) detect potential change anomalies such as omission errors or incorrect edits and (ii) determine related locations to apply consistent changes, which is a tedious and error-prone process. To address this problem, this study presents a technique for managing consistent program changes, checking and applying repetitive program transformation (CARP). Given program differencing results between original and edited program versions, CARP (i) infers change patterns to detect change anomalies, (ii) identifies required edit locations, and (iii) automatically applies adequate edits. It has been implemented in the context of the integrated development environment as an Eclipse plug-in. The authors evaluated CARP on three open-source projects and found that CARP detects seeded anomalies with 99.1% accuracy on average. Furthermore, it identifies change locations and transforms them with 98% accuracy. Their results show that CARP should help developers detect potential change anomalies in repetitive program changes and perform consistent changes automatically.