{"title":"An Approach to Detect Android Antipatterns","authors":"Geoffrey Hecht","doi":"10.1109/ICSE.2015.243","DOIUrl":null,"url":null,"abstract":"Mobile applications are becoming complex software systems that must be developed quickly and evolve regularly to fit new user requirements and execution contexts. However, addressing these constraints may result in poor design choices, known as antipatterns, which may degrade software quality and performance. Thus, the automatic detection of antipatterns is an important activity that eases the future maintenance and evolution tasks. Moreover, it helps developers to refactor their applications and thus, to improve their quality. While antipatterns are well-known in object-oriented applications, their study in mobile applications is still in their infancy. In this paper, we presents a tooled approach, called Paprika, to analyze Android applications and to detect object-oriented and Android-specific antipatterns from binaries of applications.","PeriodicalId":330487,"journal":{"name":"2015 IEEE/ACM 37th IEEE International Conference on Software Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/ACM 37th IEEE International Conference on Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE.2015.243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Mobile applications are becoming complex software systems that must be developed quickly and evolve regularly to fit new user requirements and execution contexts. However, addressing these constraints may result in poor design choices, known as antipatterns, which may degrade software quality and performance. Thus, the automatic detection of antipatterns is an important activity that eases the future maintenance and evolution tasks. Moreover, it helps developers to refactor their applications and thus, to improve their quality. While antipatterns are well-known in object-oriented applications, their study in mobile applications is still in their infancy. In this paper, we presents a tooled approach, called Paprika, to analyze Android applications and to detect object-oriented and Android-specific antipatterns from binaries of applications.