Uljana Vladimirovna Tsiazhkorob, V. N. Ignatyev, A. Belevantsev
{"title":"Detection of uses of disposed resources in C\\# source code using static analysis","authors":"Uljana Vladimirovna Tsiazhkorob, V. N. Ignatyev, A. Belevantsev","doi":"10.15514/ispras-2022-34(6)-3","DOIUrl":null,"url":null,"abstract":"The paper is devoted to the scalable approach for the detection of uses of disposed resources in C# source code, that is based on static symbolic execution. The resulting detector is implemented as a part of an industrial SharpChecker, that performs a scalable inter-procedural path-, and context-sensitive analysis. The evaluation of the developed detector shows 70% true positive ratio allowing it to include to the standard set of detectors and provide functionality to users. The paper describes a detection algorithm that takes into account the limitations imposed by the existing infrastructure of SharpChecker, its evaluation on the set of open-source programs containing 6 mln LOC and some examples of found errors in real projects.","PeriodicalId":33459,"journal":{"name":"Trudy Instituta sistemnogo programmirovaniia RAN","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trudy Instituta sistemnogo programmirovaniia RAN","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15514/ispras-2022-34(6)-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper is devoted to the scalable approach for the detection of uses of disposed resources in C# source code, that is based on static symbolic execution. The resulting detector is implemented as a part of an industrial SharpChecker, that performs a scalable inter-procedural path-, and context-sensitive analysis. The evaluation of the developed detector shows 70% true positive ratio allowing it to include to the standard set of detectors and provide functionality to users. The paper describes a detection algorithm that takes into account the limitations imposed by the existing infrastructure of SharpChecker, its evaluation on the set of open-source programs containing 6 mln LOC and some examples of found errors in real projects.