软件产品线测试优化的多目标进化算法NSGA-II和NSGA-III

Muhammad Abid Jamil, Ahmad Alhindi, Muhammad Arif, Mohamed K. Nour, Normi Sham Awang Abubakar, T. Aljabri
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引用次数: 3

摘要

软件产品线(SPL)工程方法利用可重用组件为特定领域生成新系统。事实上,产品线建立了需求、可重用组件、体系结构和共享产品,以开发新产品的功能。为了保持高质量,有必要进行彻底的测试过程。SPL中的每个产品都有不同数量的特性需要测试。因此,SPL的测试过程可以利用多目标优化算法对测试过程进行优化。本研究报告了多目标进化算法非支配排序遗传算法II (NSGA-II)和NSGA-III在特征模型(FMs)上优化SPL测试的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiobjective Evolutionary Algorithms NSGA-II and NSGA-III for Software Product Lines Testing Optimization
Software Product line (SPL) engineering methodology utilizes reusable components to generate a new system for a specific domain. In fact, the product line establishes requirements, reusable components, architecture, and shared products to develop new products' functionalities. In order to maintain high quality, there is a need for a thorough testing process. Each product in SPL having a different number of features need to be tested. Hence, the testing process of SPL can utilize a multi-objective optimization algorithm to optimize the testing process. This research, reports on the performance of a multi-objective Evolutionary Algorithms Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and NSGA-III on Feature Models (FMs) to optimize SPL testing.
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