{"title":"方面的源代码分析与GASR","authors":"J. Fabry, Coen De Roover, V. Jonckers","doi":"10.1109/SCAM.2013.6648184","DOIUrl":null,"url":null,"abstract":"To be able to modularize crosscutting concerns, aspects introduce new programming language features, often in a new language, with a specific syntax. These new features lead to new needs for source code analysis tools, resulting in the requirement for a general-purpose aspectual source code analysis tool. Ignoring this requirement has led to a nontrivial duplication of effort in the aspect-oriented software development community. This is because all code analysis efforts that we are aware of have either built ad-hoc analysis tools or were performed manually. In this paper we present Gasr: a source code analysis tool in the tradition of logic program querying that reasons over AspectJ source code. By hooking into the IDE plugins for AspectJ, Gasr provides a library of predicates that can be used to query aspectual source code. We demonstrate the use of Gasr by automating the recognition of a number of previously identified aspectual source code assumptions. We then detect assumption instances on two well-known case studies that were manually investigated in the earlier work. In addition to finding the already known aspect assumptions, Gasr encounters assumption instances that were overlooked before.","PeriodicalId":170882,"journal":{"name":"2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Aspectual source code analysis with GASR\",\"authors\":\"J. Fabry, Coen De Roover, V. Jonckers\",\"doi\":\"10.1109/SCAM.2013.6648184\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To be able to modularize crosscutting concerns, aspects introduce new programming language features, often in a new language, with a specific syntax. These new features lead to new needs for source code analysis tools, resulting in the requirement for a general-purpose aspectual source code analysis tool. Ignoring this requirement has led to a nontrivial duplication of effort in the aspect-oriented software development community. This is because all code analysis efforts that we are aware of have either built ad-hoc analysis tools or were performed manually. In this paper we present Gasr: a source code analysis tool in the tradition of logic program querying that reasons over AspectJ source code. By hooking into the IDE plugins for AspectJ, Gasr provides a library of predicates that can be used to query aspectual source code. We demonstrate the use of Gasr by automating the recognition of a number of previously identified aspectual source code assumptions. We then detect assumption instances on two well-known case studies that were manually investigated in the earlier work. In addition to finding the already known aspect assumptions, Gasr encounters assumption instances that were overlooked before.\",\"PeriodicalId\":170882,\"journal\":{\"name\":\"2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCAM.2013.6648184\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCAM.2013.6648184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To be able to modularize crosscutting concerns, aspects introduce new programming language features, often in a new language, with a specific syntax. These new features lead to new needs for source code analysis tools, resulting in the requirement for a general-purpose aspectual source code analysis tool. Ignoring this requirement has led to a nontrivial duplication of effort in the aspect-oriented software development community. This is because all code analysis efforts that we are aware of have either built ad-hoc analysis tools or were performed manually. In this paper we present Gasr: a source code analysis tool in the tradition of logic program querying that reasons over AspectJ source code. By hooking into the IDE plugins for AspectJ, Gasr provides a library of predicates that can be used to query aspectual source code. We demonstrate the use of Gasr by automating the recognition of a number of previously identified aspectual source code assumptions. We then detect assumption instances on two well-known case studies that were manually investigated in the earlier work. In addition to finding the already known aspect assumptions, Gasr encounters assumption instances that were overlooked before.