Context

Software testing is essential in software engineering to improve software reliability. One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which has shown to be effective in the fault detection process.

Objective

Previous studies have demonstrated that DRT is greatly affected by the test case classification and the process of adjusting the testing profile. In this paper, we propose Distance-based DRT (D-DRT) strategies, aiming at enhancing the fault detection effectiveness of DRT.

Method

D-DRT strategies utilize distance information of inputs into the test case classification and the testing profile adjustment process. The test cases are vectorized based on the input parameters and classified into disjoint subdomains through certain clustering methods. And the distance information of subdomains, along with testing results, are used to adjust the testing profile, such that test cases that are closer to failure-causing subdomains are more likely to be selected.

Results

We conduct empirical studies to evaluate the performance of the proposed algorithms using 12 versions of 4 open-source programs. The experimental results show that, compared with Random Testing (RT), Random Partition Testing (RPT), DRT and Adaptive Testing (AT), our strategies achieve greater fault detection effectiveness with a low computational cost. Moreover, the distance-based testing profile adjustment method is the dominant factor in the improvement of the D-DRT strategy.

Conclusion

D-DRT strategies are effective testing strategies, and the distance-based testing profile adjustment method plays a crucial role.

中文翻译：

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具有测试用例聚类和基于距离的参数调整的动态随机测试

语境

在软件工程中，软件测试对于提高软件可靠性至关重要。软件测试策略的目标之一是更快地检测故障。动态随机测试（DRT）策略使用测试结果来指导测试用例的选择，这在故障检测过程中被证明是有效的。

目的

先前的研究表明，DRT受测试用例分类和调整测试配置文件的过程的影响很大。在本文中，我们提出了基于距离的DRT（D-DRT）策略，旨在提高DRT的故障检测效率。

方法

D-DRT策略利用输入的距离信息进入测试用例分类和测试配置文件调整过程。根据输入参数对测试用例进行矢量化处理，并通过某些聚类方法将其分为不相交的子域。子域的距离信息以及测试结果将用于调整测试配置文件，以便更可能选择更接近导致故障的子域的测试用例。

结果

我们进行了实证研究，以使用4个开源程序的12个版本来评估所提出算法的性能。实验结果表明，与随机测试（RT），随机分区测试（RPT），DRT和自适应测试（AT）相比，我们的策略以较低的计算成本实现了更高的故障检测效率。此外，基于距离的测试轮廓调整方法是改进D-DRT策略的主要因素。

结论

D-DRT策略是有效的测试策略，基于距离的测试配置文件调整方法起着至关重要的作用。