论文标题
使用约束求解器代码覆盖范围意识到测试生成
Code Coverage Aware Test Generation Using Constraint Solver
论文作者
论文摘要
在软件测试上下文中，代码覆盖范围主要用作评估生成的测试套件质量的指标。最近，代码覆盖范围分析用作用于测试优化的白盒测试技术。大多数研究活动都专注于使用代码覆盖范围进行测试优先级和自动测试策略中的选择。文献中付出了更少的努力，以将代码覆盖范围用于测试生成。本文介绍了一个新的基于代码覆盖的测试案例生成（CCTG）概念，该概念通过在测试生成过程中利用代码覆盖范围分析来改变当前实践。 CCTG使用代码覆盖率数据来计算输入参数对约束求解器的影响，以使有效测试套件的生成自动化。我们将这种方法应用于一些现实世界中的案例研究。结果表明，新的测试生成方法可以生成有效的测试用例并检测新的故障。
Code coverage has been used in the software testing context mostly as a metric to assess a generated test suite's quality. Recently, code coverage analysis is used as a white-box testing technique for test optimization. Most of the research activities focus on using code coverage for test prioritization and selection within automated testing strategies. Less effort has been paid in the literature to use code coverage for test generation. This paper introduces a new Code Coverage-based Test Case Generation (CCTG) concept that changes the current practices by utilizing the code coverage analysis in the test generation process. CCTG uses the code coverage data to calculate the input parameters' impact for a constraint solver to automate the generation of effective test suites. We applied this approach to a few real-world case studies. The results showed that the new test generation approach could generate effective test cases and detect new faults.
