GRT:使用编排程序分析的自动化测试生成器

Lei Ma, Cyrille Artho, Cheng Zhang, Hiroyuki Sato, Johannes Gmeiner, R. Ramler
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引用次数: 18

摘要

虽然具有高度自动化和易于使用的特点,但是现有的随机测试技术在实际软件应用中存在代码覆盖率低和缺陷检测能力差的问题。大多数工具使用纯黑盒方法,不使用特定于被测软件的知识。挖掘和利用被测软件的信息有望指导随机测试来克服这些限制。引导随机测试(GRT)实现了这个想法。GRT对被测软件进行静态分析,提取相关知识,并结合在运行时提取的信息来指导整个测试生成过程。GRT是高度可配置的,其六个程序分析组件中的每一个都实现为可插拔模块,其参数可以调整。除了生成测试用例,GRT还自动创建测试覆盖率报告。我们将展示我们在GRT工具开发方面的经验,并通过两个具体的应用程序场景演示其实际用法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GRT: An Automated Test Generator Using Orchestrated Program Analysis
While being highly automated and easy to use, existing techniques of random testing suffer from low code coverage and defect detection ability for practical software applications. Most tools use a pure black-box approach, which does not use knowledge specific to the software under test. Mining and leveraging the information of the software under test can be promising to guide random testing to overcome such limitations. Guided Random Testing (GRT) implements this idea. GRT performs static analysis on software under test to extract relevant knowledge and further combines the information extracted at run-time to guide the whole test generation procedure. GRT is highly configurable, with each of its six program analysis components implemented as a pluggable module whose parameters can be adjusted. Besides generating test cases, GRT also automatically creates a test coverage report. We show our experience in GRT tool development and demonstrate its practical usage using two concrete application scenarios.
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