Random unit-test generation with MUT-aware sequence recommendation

Wujie Zheng, Qirun Zhang, Michael R. Lyu, Tao Xie
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引用次数: 29

Abstract

A key component of automated object-oriented unit-test generation is to find method-call sequences that generate desired inputs of a method under test (MUT). Previous work cannot find desired sequences effectively due to the large search space of possible sequences. To address this issue, we present a MUT-aware sequence recommendation approach called RecGen to improve the effectiveness of random object-oriented unit-test generation. Unlike existing random testing approaches that select sequences without considering how a MUT may use inputs generated from sequences, RecGen analyzes object fields accessed by a MUT and recommends a short sequence that mutates these fields. In addition, for MUTs whose test generation keeps failing, RecGen recommends a set of sequences to cover all the methods that mutate object fields accessed by the MUT. This technique further improves the chance of generating desired inputs. We have implemented RecGen and evaluated it on three libraries. Evaluation results show that RecGen improves code coverage over previous random testing tools.
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随机单元测试生成与mut_aware序列推荐
自动化的面向对象单元测试生成的一个关键组件是找到生成被测方法所需输入的方法调用序列。以往的工作由于可能序列的搜索空间大,不能有效地找到想要的序列。为了解决这个问题,我们提出了一种称为RecGen的mutt感知序列推荐方法,以提高随机面向对象单元测试生成的有效性。现有的随机测试方法在选择序列时不考虑MUT如何使用从序列生成的输入,而RecGen分析MUT访问的对象字段,并推荐一个短序列来改变这些字段。此外,对于测试生成不断失败的MUT, RecGen建议使用一组序列来覆盖所有改变MUT访问的对象字段的方法。这种技术进一步提高了生成所需输入的机会。我们已经在三个库上实现了RecGen并对其进行了评估。评估结果表明,RecGen比以前的随机测试工具提高了代码覆盖率。
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