Test point selection strategy under unreliable test based on heuristic particle swarm optimization algorithm

D. Sen, Jing Bo, Yang Zhou
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引用次数: 3

Abstract

A heuristic particle swarm optimization algorithm is proposed to solve the problem of test point selection with unreliable test. Firstly, a heuristic function is established to value the capability of test point detection, coverage and reliance. Then based on the heuristic function and least test cost principle, a fitness function of unreliable test is created. Lastly, the method for test point selection using improved particle swarm optimization algorithm is presented. Comparing with other method of test point selection, the results show that the method is easy to find the global optimal test point in large-scale system. It can also minimize test cost on requirement of testability targets.
基于启发式粒子群优化算法的不可靠测试点选择策略
针对不可靠测试条件下的测试点选择问题,提出了一种启发式粒子群优化算法。首先,建立了一个启发式函数来评价测试点检测能力、覆盖率和可靠性。然后基于启发式函数和最小测试代价原理,建立了不可靠测试的适应度函数。最后,提出了基于改进粒子群算法的测试点选择方法。与其他测试点选择方法进行比较,结果表明该方法易于在大型系统中找到全局最优测试点。在满足可测试性目标要求的情况下,使测试成本最小化。
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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