PhABC:一种具有约束支持的成对测试套件生成的混合人工蜂群策略

A. K. Alazzawi, H. Rais, S. Basri, Y. A. Alsariera
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引用次数: 12

摘要

由于软件开发过程导致组件数量和相关时间的增加,软件测试成为我们日常生活的重要组成部分。由于财政资源和时间的限制,几乎彻底的测试是没有希望的。由于这个原因,许多研究人员采用了成对测试来减少测试用例的穷尽数量。成对测试是一种强大的组合测试技术,广泛用于测试数据的生成。现有的各种研究工作都是使用元启发式算法作为两两测试策略的基础。在补充前人研究工作的基础上,提出了一种基于人工蜂群(ABC)算法与粒子群优化(PSO)算法杂交的成对杂交人工蜂群(PhABC)策略。PhABC的输出是一组有前途的最优测试集组合。实验结果表明,即使在现有的约束条件下,PhABC也比现有的其他研究策略表现更好,产生更好的测试集。
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PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support
Software testing becoming significant part of our daily life due to a software-development process that led to increase the components number and the associated time. Due to the financial resources and time constraints, practically exhaustive testing is hopeless. For this reason, numerous researchers have adopted pairwise testing to decrease the exhaustive number of test cases. Pairwise testing is one of a powerful Combinatorial Testing Technique (CTT) that used widely for test data generation. Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. Supplementing to earlier research work, this paper proposed a new pairwise test suite generation called pairwise hybrid artificial bee colony (PhABC) strategy based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. The output of PhABC is a set of promising optimal test set combinations. The results of the experiments showed that PhABC outperformed and yielded better test sets than other existing other research strategies even with the existing constraints.
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