GRT: An Automated Test Generator Using Orchestrated Program Analysis
GRT: An Automated Test Generator Using Orchestrated Program Analysis
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DOI：
10.1109/ase.2015.102
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发表时间：
2015-11
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通讯作者：
Lei Ma;Cyrille Artho;Cheng Zhang;Hiroyuki Sato;Johannes Gmeiner;Rudolf Ramler
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作者：
Lei Ma;Cyrille Artho;Cheng Zhang;Hiroyuki Sato;Johannes Gmeiner;Rudolf Ramler
现有的随机测试技术虽然自动化程度高、使用方便，但在实际应用中存在代码覆盖率低、缺陷检测能力差等问题。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，可以有希望指导随机测试，以克服这些限制。引导随机测试（GRT）实现了这一思想。GRT对被测软件进行静态分析，提取相关知识，并结合运行时提取的信息指导整个测试生成过程。GRT是高度可配置的，它的六个程序分析组件中的每一个都实现为一个可插入的模块，其参数可以调整。除了生成测试用例外，GRT还自动创建测试覆盖报告。我们展示了我们在GRT工具开发方面的经验，并使用两个具体的应用场景演示了其实际用途。
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.