文章基本信息

标题：Crossbreed Algorithm for Regression Testing by Comparing Bee Colony Optimization (BCO), Genetic Algorithm (GA) and Ant Colony Optimization (ACO)
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作者：Jasjeet Kaur ; Tajinder Kaur
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：5
出版社：S.S. Mishra
摘要：Regression testing is a branch of testing in which we test the system in each and every manner. This is done to improve the performance of the system on the basis of faults found in the region. For better efficiency we combine the test case with other suitable test cases to enhance the performance. Now in this paper we have proposed a work in which we have combined BCO with COA to perform the optimization of the system as well as we would compare it with all the previous work done. COA is an optimization algorithm in which it is tested at each and every step that how the test cases should be combined to optimize the result .GA is an evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. BCO is a swarm intelligence algorithm.
关键词：Regression testing; Genetic algorithm (GA); Bee colony optimization (BCO); Ant colony ;optimization(ACO);Continuous orthogonal algorithm(COA)