{"title":"Devirtualization for static analysis with low level intermediate representation","authors":"Artemiy Galustov, A. Borodin, A. Belevantsev","doi":"10.1109/ISPRAS57371.2022.10076859","DOIUrl":null,"url":null,"abstract":"We propose a points-to analysis that can recover targets for function pointer calls, virtual calls and method calls for using in a static analysis. We use a flow-insensitive analysis, and the analysis results are intended for flow- and path-sensitive analysis which can improve the initial analysis precision within a single function. We implemented the proposed approach in a static analyzer for finding errors in C, C++, Go, Java and Kotlin programs. The devirtualization algorithm is fast enough and spends less than 6% of the total analysis time. It can work for projects like Tizen 7 with 27.5 MLoc of source code.","PeriodicalId":103880,"journal":{"name":"2022 Ivannikov Ispras Open Conference (ISPRAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Ivannikov Ispras Open Conference (ISPRAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPRAS57371.2022.10076859","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
We propose a points-to analysis that can recover targets for function pointer calls, virtual calls and method calls for using in a static analysis. We use a flow-insensitive analysis, and the analysis results are intended for flow- and path-sensitive analysis which can improve the initial analysis precision within a single function. We implemented the proposed approach in a static analyzer for finding errors in C, C++, Go, Java and Kotlin programs. The devirtualization algorithm is fast enough and spends less than 6% of the total analysis time. It can work for projects like Tizen 7 with 27.5 MLoc of source code.