基于改进遗传算法的回归测试用例优先级排序

Priority Ranking of Regression Test Cases Based on Improved Genetic Algorithm

由于优先级排序测试效果较差、执行效率低,为此提出基于改进遗传算法的回归测试用例优先级排序方法。通过自然选择与遗传理论作为基本条件,结合群体中染色体任意信息交换机制和生物进化过程内适者生存规则,完成遗传算法,接着引入禁忌搜索方法,增强排序的局部超强搜索能力,然后在回归测试的过程内,利用多个目标函数对回归测试用例优先级排序以及评价,完成回归测试用例优先级排序。实验结果表明,经过时间以及覆盖的角度考察,执行时间较短,平均分支较大,说明该序列优良,本文方法的回归测试效果较好,执行效率高。

The traditional prioritization test results are poor and the execution efficiency is low.Therefore,this paper proposes a regression test case prioritization method based on improved genetic algorithm.First of all,the mechanism of chromosome arbitrary information exchange in population and survival rules of the fittest in the process of biological evolution were combined to achieve the genetic algorithm by using natural selection and genetic theory.Then,the tabu search method was introduced for enhancing the local super search ability of sorting.Finally,in the process of regression testing,multiple objective functions were used to prioritize and evaluate the regression test cases.Eventually,the regression test cases are prioritized.The results show that this method has short execution time,large average branch,excellent regression test effect and high execution efficiency.