Deletion and selection model for test case selection

A. Lawanna, Jittima Wongwuttiwaat, B. Srisura
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Abstract

Deletion and selection model is planned for improving the ability of selecting the relevant test cases of the modified programs by comparing the outcomes with the well-known traditional methods, which are random, dataflow, slicing, model based, code based, and coverage based analysis. This is because after adapting the programs for several times, numbers of test case will increase that can drop the whole performance of the new version. The problems are time consuming and producing bugs and other failures when using the updated software. The proposed model consists two main algorithms, which are deletion and selection regarding classifying types of the requirements. According to this, the percent of reducing the size by using the proposed model is better than the traditional methods. Besides, percent of finding bugs of the six comparative studies are higher than the offered technique approximately 55%. Moreover, the efficiency of applying the proposed method is greater than the existing technique as about 86 %.
用于测试用例选择的删除和选择模型
通过与传统的随机分析、数据流分析、切片分析、基于模型分析、基于代码分析、基于覆盖率分析的结果对比,规划了删除和选择模型的模型模型,以提高对修改后程序的相关测试用例的选择能力。这是因为在对程序进行多次调整之后,测试用例的数量将会增加,从而降低新版本的整体性能。在使用更新后的软件时,这些问题很耗时,而且会产生错误和其他故障。该模型主要包括两种算法:删除算法和选择算法。由此可见,使用该模型的尺寸缩减率优于传统方法。此外,六种比较研究的bug发现率都比提供的技术高约55%。此外,应用该方法的效率约为86%,高于现有技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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