一种组合测试用例生成的可配置混合算法

摘要

组合测试是一种经过实践证明的科学有效的测试方法,其研究重点之一是组合测试用例集的生成算法.基于参数顺序渐进扩充策略IPO(In-Parameter-Order)是其中一种具有代表性的通用算法,其优势在于水平扩充算法的可选择性和测试用例集的可扩展性.算法在提取影响IPO策略效果的参数的基础上,给出可配置的IPO策略;采用遗传算法(Genetic-Algorithm)配置IPO策略中的水平扩充,得到新的混合算法IPO_GA.通过实验对可配置IPO策略中各个参数对算法的影响进行了对比分析;将IPO_GA与部分已有算法进行了比较,结果表明在水平扩充过程中染色体较短时,IPO_GA效果较好;在解空间规模过大而导致染色体较长时,IPO_GA效果略差.%Combinatorial Testing is a method of testing which proves to be scientific and effective by practice, one research priority is Combinatorial Testing suite generation algorithms. In Parameter Order test generation strategy is representative in such algorithms,advantages of which relies on the selectivity of horizontal expanding and the extendibility of test suite. On the foundation of extracting the parameters which affects the implementation of IPO, a configurable framework was presented and implemented)a new mixed algorithm IPO_GA was presented which uses Genetic Algorithm to do horizontal expanding in the configurable IPO framework. Experiments and analysis were done on each parameter of the configurable IPO framework and IPO_GA was compared with some existing algorithms, results show that IPO_GA performs better while the size of a chromosome is short when doing horizontal expanding;otherwise if the size of a chromosome is too large,IPO_GA performs worse than expected.