Covana: precise identification of problems in pex

Xusheng Xiao, Tao Xie, N. Tillmann, J. D. Halleux
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引用次数: 4

Abstract

Achieving high structural coverage is an important goal of software testing. Instead of manually producing test inputs that achieve high structural coverage, testers or developers can employ tools built based on automated test-generation approaches, such as Pex, to automatically generate such test inputs. Although these tools can easily generate test inputs that achieve high structural coverage for simple programs, when applied on complex programs in practice, these tools face various problems, such as the problems of dealing with method calls to external libraries or generating method-call sequences to produce desired object states. Since these tools are currently not powerful enough to deal with these various problems in testing complex programs, we propose cooperative developer testing, where developers provide guidance to help tools achieve higher structural coverage. In this demo, we present Covana, a tool that precisely identifies and reports problems that prevent Pex from achieving high structural coverage. Covana identifies problems primarily by determining whether branch statements containing not-covered branches have data dependencies on problem candidates.
Covana:精确识别pex中的问题
实现高结构覆盖率是软件测试的一个重要目标。测试人员或开发人员可以使用基于自动测试生成方法(例如Pex)构建的工具,而不是手工生成获得高结构覆盖率的测试输入,来自动生成这样的测试输入。尽管这些工具可以很容易地为简单的程序生成高结构覆盖率的测试输入,但是当在实践中应用于复杂的程序时,这些工具面临着各种各样的问题,例如处理对外部库的方法调用的问题,或者生成方法调用序列以产生期望的对象状态的问题。由于这些工具目前还不够强大,无法处理测试复杂程序中的各种问题,我们建议合作开发人员测试,开发人员提供指导,帮助工具实现更高的结构覆盖率。在这个演示中,我们展示了Covana,一个精确识别和报告阻止Pex获得高结构覆盖率的问题的工具。Covana主要通过确定包含未覆盖分支的分支语句是否对问题候选者具有数据依赖性来识别问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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