Using Test Ranges to Improve Symbolic Execution
Using Test Ranges to Improve Symbolic Execution
复制标题
使用测试范围来改进符号执行
DOI：
10.1007/978-3-319-77935-5_28
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发表时间：
2018
期刊：
影响因子：
4.1
通讯作者：
Guowei Yang
中科院分区：
文献类型：
--
作者：
Rui Qiu;S. Khurshid;C. Păsăreanu;Junye Wen;Guowei Yang
符号执行是一种功能强大的系统化程序检测技术，在过去的十年中受到了广泛的研究关注。然而，在实践中，该技术仍然难以扩展。本文介绍了SynergiSE，一种新的方法来提高符号执行，解决其更广泛采用的一个关键瓶颈：昂贵和不完整的约束求解。为了降低成本，SynergiSE引入了约束求解结果的简洁编码，从而使符号执行能够分布在不同的工作者之间，同时在他们之间共享和重用约束求解结果，而不必通信约束求解结果的数据库。为了减轻不完整性，SynergiSE引入了一种用于测试的互补方法的集成，例如，基于搜索的测试生成，带有符号执行，从而使符号执行和其他技术能够协同应用。使用一套Java程序的实验结果表明，SynergiSE提出了一个很有前途的方法，提高符号执行。
Symbolic execution is a powerful systematic technique for checking programs, which has received a lot of research attention during the last decade. In practice however, the technique remains hard to scale. This paper introduces SynergiSE, a novel approach to improve symbolic execution by tackling a key bottleneck to its wider adoption: costly and incomplete constraint solving. To mitigate the cost, SynergiSE introduces a succinct encoding of constraint solving results, thereby enabling symbolic execution to be distributed among different workers while sharing and re-using constraint solving results among them without having to communicate databases of constraint solving results. To mitigate the incompleteness, SynergiSE introduces an integration of complementary approaches for testing, e.g., search-based test generation, with symbolic execution, thereby enabling symbolic execution and other techniques to apply in tandem. Experimental results using a suite of Java programs show that SynergiSE presents a promising approach for improving symbolic execution.
DOI：
10.4230/lipics.ecoop.2018.6
发表时间：
2018
期刊：
--
影响因子：
--
作者：
Junjie Chen;Wenxiang Hu;Lingming Zhang;Dan Hao;S. Khurshid;Lu Zhang
通讯作者：
Junjie Chen;Wenxiang Hu;Lingming Zhang;Dan Hao;S. Khurshid;Lu Zhang
影响因子：
3.5
作者：
Anand, Saswat;Burke, Edmund K.;Zhu, Hong
通讯作者：
Zhu, Hong