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Test Case Generation for Web Application Based on Markov Reward Process
Journal of Physics: Conference Series Pub Date : 2021-02-20 , DOI: 10.1088/1742-6596/1792/1/012039
Jing Cao 1, 2 , Xiaoqiang Liu 1 , Hui Guo 1 , Lizhi Cai 2 , Yun Hu 2
Affiliation  

Web applications often face continuous updating due to functional change or UI renew, while it remains a challenge to guarantee their correctness. The goal of software testing is to find defects in a limited time range whereas exhaustive testing is an ideal yet time-consuming process. In this research, we propose an approach to generating test cases automatically based on the Markov reward process which innovatively contains a reward function for test results to guide the generation of test cases. By using the N-step algorithm, this approach can generate the test flow with the highest risk priority which can capture software defects as quickly as possible. The experiment on an e-commerce system shows that there is significant improvement on the defect detection capability of test cases generated through Markov reward process.



中文翻译:

基于马尔可夫奖励过程的Web应用测试用例生成

由于功能更改或UI更新,Web应用程序经常面临不断的更新,而保证其正确性仍然是一个挑战。软件测试的目标是在有限的时间范围内发现缺陷,而详尽的测试则是一个理想而又耗时的过程。在这项研究中,我们提出了一种基于马尔可夫奖励过程的自动生成测试用例的方法,该方法创新地包含了对测试结果的奖励功能,以指导测试用例的生成。通过使用N步算法,此方法可以生成具有最高风险优先级的测试流程,从而可以尽快捕获软件缺陷。在电子商务系统上进行的实验表明,通过马尔可夫奖励过程生成的测试用例的缺陷检测能力有了显着提高。

更新日期:2021-02-20
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