{"title":"面向块级特征羡慕设计的缺陷检测","authors":"Árpád Kiss, Petru Florin Mihancea","doi":"10.1109/ICSME.2018.00064","DOIUrl":null,"url":null,"abstract":"Software is continuously evolving as bugs need to be fixed and new features need to be added. Design flaws hinder the simple evolution of software and thus, we have to detect and correct them. Feature Envy is an object-oriented design issue that can be detected at the level of methods using different state-of-the-art approaches. Unfortunately, these are insufficient because only a portion of a method may actually be affected by this flaw. Thus, only that part needs to be treated using the corresponding correction strategy, not the entire method. To address this issue, we propose the detection of Feature Envy code smell at the level of blocks of code. Initial evaluation suggests that our approach is promising in spotting the envious areas within a method.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"78 1","pages":"544-548"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards Feature Envy Design Flaw Detection at Block Level\",\"authors\":\"Árpád Kiss, Petru Florin Mihancea\",\"doi\":\"10.1109/ICSME.2018.00064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software is continuously evolving as bugs need to be fixed and new features need to be added. Design flaws hinder the simple evolution of software and thus, we have to detect and correct them. Feature Envy is an object-oriented design issue that can be detected at the level of methods using different state-of-the-art approaches. Unfortunately, these are insufficient because only a portion of a method may actually be affected by this flaw. Thus, only that part needs to be treated using the corresponding correction strategy, not the entire method. To address this issue, we propose the detection of Feature Envy code smell at the level of blocks of code. Initial evaluation suggests that our approach is promising in spotting the envious areas within a method.\",\"PeriodicalId\":6572,\"journal\":{\"name\":\"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)\",\"volume\":\"78 1\",\"pages\":\"544-548\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSME.2018.00064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSME.2018.00064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Feature Envy Design Flaw Detection at Block Level
Software is continuously evolving as bugs need to be fixed and new features need to be added. Design flaws hinder the simple evolution of software and thus, we have to detect and correct them. Feature Envy is an object-oriented design issue that can be detected at the level of methods using different state-of-the-art approaches. Unfortunately, these are insufficient because only a portion of a method may actually be affected by this flaw. Thus, only that part needs to be treated using the corresponding correction strategy, not the entire method. To address this issue, we propose the detection of Feature Envy code smell at the level of blocks of code. Initial evaluation suggests that our approach is promising in spotting the envious areas within a method.