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Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm

机译:基于混合人工蜂菌落算法的成对测试套件生成

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Abstract Software plays an important part of our daily life in order to aid and facilitate our routine tasks, especially a household one. However, the failure of software is a major threat to our lives, particularly the critical applications that employed daily. Due to the large number of inputs as well as time consumption for a test and cost, it is becoming hard to get exhaustive testing for any software in order to fault detection. For this reason, Combinatorial Testing Technique (CTT) is one of the famous techniques that have been used in fault detection of the software systems. Pairwise testing is one of the efficient CTT that used widely for fault detection based on the caused failures by two interactions parameters. There are many researchers that have been developed a pairwise testing strategy. Complementing to the earlier researches, this paper proposes 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. Empirical results shows that PhABC strategy outperforms other strategies in some cases and provides competitive results in other cases by generating the final test suite.
机译:抽象软件扮演我们日常生活的重要组成部分,以帮助和促进我们的日常任务,特别是家庭。然而,软件的失败是我们生活的主要威胁,特别是每天使用的关键应用。由于输入的大量输入以及测试和成本的时间消耗,因此难以获得任何软件的详尽测试,以便故障检测。因此,组合测试技术(CTT)是已在软件系统的故障检测中使用的着名技术之一。成对测试是基于两个交互参数的引起的故障广泛用于故障检测的有效CTT之一。有许多研究人员已经开发了一种成对的测试策略。本文补充了先前的研究,提出了一种基于具有粒子群优化(PSO)算法的人工蜂菌落(ABC)算法的杂交的综合对成对混合人造蜜蜂菌落(PHABC)策略的新成对试验套件。经验结果表明,PHABC策略在某些情况下优于其他策略,并通过产生最终测试套件在其他情况下提供竞争结果。

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