Hybrid optimization with constraints handling for combinatorial test case prioritization problems.

Network (Bristol, England) Pub Date : 2025-07-10 DOI:10.1080/0954898X.2025.2517130

Selvakumar J, Sudhir Sharma, Mukesh Kumar Tripathi

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Abstract

In software development, software testing is very crucial for developing good quality software, where the effectiveness of software is to be tested. For software testing, test suites and test cases need to be prepared in minimum execution time with the test case prioritization (TCP) problems. Generally, some of the researchers mainly focus on the constraint problems, such as time and fault on TCP. In this research, the novel Fractional Hybrid Leader Based Optimization (FHLO) is introduced with constraint handling for combinatorial TCP. To detect faults earlier, the TCP is an important technique as it reduces the regression testing cost and prioritizes the test case execution. Based on the detected fault and branch coverage, the priority of the test case for program execution is decided. Furthermore, the FHLO algorithm establishes the TCP for detecting the program fault, which prioritizes the test case, and relies on maximum values of Average Percentage of Branch Coverage (APBC) and Average Percentage of Fault Detected (APFD). From the analysis, the devised FHLO algorithm attains a maximum value of 0.966 for APFD and 0.888 for APBC.

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组合测试用例优先级问题的约束处理混合优化。

在软件开发中，软件测试对于开发高质量的软件是非常关键的，因为要测试软件的有效性。对于软件测试，测试套件和测试用例需要在最小的执行时间内准备好测试用例优先级（TCP）问题。一般来说，一些研究者主要关注TCP的约束问题，如时间和故障。本文提出了一种新的基于分数阶混合Leader的优化算法，并对组合TCP进行了约束处理。为了更早地检测故障，TCP是一项重要的技术，因为它降低了回归测试成本并优先执行测试用例。基于检测到的故障和分支覆盖率，决定程序执行的测试用例的优先级。此外，FHLO算法建立了检测程序故障的TCP协议，该协议对测试用例进行优先级排序，并依赖于平均分支覆盖率百分比（APBC）和平均故障检测百分比（APFD）的最大值。分析表明，所设计的FHLO算法在APFD和APBC上的最大值分别为0.966和0.888。

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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Network (Bristol, England)

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