{"title":"“Symcrete” memory Model with Lazy Initialization and Objects of Symbolic Sizes in KLEE","authors":"Sergey Antonovich Morozov, Aleksandr Vladimirovich Misonizhnik, Dmitry Aleksandrovich Mordvinov, Dmitry Vladimirovich Koznov, Dmitry Arkadevich Ivanov","doi":"10.15514/ispras-2023-35(3)-7","DOIUrl":null,"url":null,"abstract":"Dynamic symbolic execution is a well-known technique for testing applications. It introduces symbolic variables – program data with no concrete value at the moment of instantiation – and uses them to systematically explore the execution paths in a program under analysis. However, not every value can be easily modelled as symbolic: for instance, some values may take values from restricted domains or have complex invariants, hard enough to model using existing logic theories, despite it is not a problem for concrete computations. In this paper, we propose an implementation of infrastructure for dealing with such “hard-to-be-modelled” values. We take the approach known as symcrete execution and implement its robust and scalable version in the well-known KLEE symbolic execution engine. We use this infrastructure to support the symbolic execution of LLVM programs with complex input data structures and input buffers with indeterminate sizes.","PeriodicalId":33459,"journal":{"name":"Trudy Instituta sistemnogo programmirovaniia RAN","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","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-2023-35(3)-7","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
Dynamic symbolic execution is a well-known technique for testing applications. It introduces symbolic variables – program data with no concrete value at the moment of instantiation – and uses them to systematically explore the execution paths in a program under analysis. However, not every value can be easily modelled as symbolic: for instance, some values may take values from restricted domains or have complex invariants, hard enough to model using existing logic theories, despite it is not a problem for concrete computations. In this paper, we propose an implementation of infrastructure for dealing with such “hard-to-be-modelled” values. We take the approach known as symcrete execution and implement its robust and scalable version in the well-known KLEE symbolic execution engine. We use this infrastructure to support the symbolic execution of LLVM programs with complex input data structures and input buffers with indeterminate sizes.