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An Ant Colony Algorithm to Prioritize the Regression Test Cases of Object-Oriented Programs

机译:蚁群算法优先处理面向对象程序的回归测试用例

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Background/Objectives: The limited resources force to choose an effective prioritization technique, which makes an ordering of the test case so that the most suitable test case will execute first. Methods/Statistical Analysis: Regression test case prioritization using Ant colony optimization for the object-oriented program is proposed in this paper. Using the previous version test pool a complete graph is generated. The node of the graph represents test case and their fault exposing potential is used by the ant to select a prioritization sequence. Findings: The effectiveness of the test case ordering is measured using APFD (Average percentage of Faults Detected). Experiments on three object oriented subject programs are performed to judge the said approach. The empirical results indicate that the algorithm implemented using ant colony optimization gives higher APFD value than the random techniques. Applications/Improvements: This technique may be used by the quality assurance team for prioritizing test case as it space and time complexity is less as compared to random ordering.
机译:背景/目标:有限的资源迫使选择一种有效的优先级排序技术,该技术对测试用例进行排序,以便最合适的测试用例将首先执行。方法/统计分析:本文提出了基于蚁群算法的回归测试用例优先级排序方法。使用先前版本的测试池,将生成完整的图形。图的节点表示测试用例,蚂蚁使用它们的故障暴露潜力来选择优先顺序。结果:使用APFD(检测到的故障的平均百分比)来衡量测试案例排序的有效性。对三个面向对象的主题程序进行了实验,以判断所述方法。实验结果表明,与随机技术相比,使用蚁群优化实现的算法具有更高的APFD值。应用程序/改进:质量保证团队可以使用此技术来确定测试案例的优先级,因为与随机排序相比,它的空间和时间复杂度要小。

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