体系结构动态变化的软件测试资源分配算法

Software testing resource allocation algorithm for dynamic changes in architecture

测试资源分配是软件测试中的一个核心问题。已有相关研究大都假设软件的体系结构是静态不变的,且几乎没有考虑成本约束。针对该问题,提出一种体系结构动态变化的软件测试资源分配算法。首先构建了一种体系结构动态变化的多阶段多目标多约束测试资源分配模型;然后基于参数重估计、广义差分进化,在算法中加入了种群重新初始化,该方法能减小算法搜索空间并提升算法性能;最后在算法中加入了一种新的修复处理机制,该机制能有效剔除算法产生的无效解。与归一化加权求和多目标差分进化(WNS-MODE)算法和基于第三代广义差分进化的动态测试资源分配(DTRA-GDE3)算法相比,所提算法获得的解集的容量值分别提高了约11.81倍和0.39倍。在覆盖值指标方面,所提算法完全覆盖了WNS-MODE算法,并且相对于DTRA-GDE3算法提高了81个百分点。在超体积值指标方面,所提算法分别提高了近6倍和9倍。实验结果表明,所提算法能够更好地适应软件体系结构的动态变化,可为软件产品的动态测试提供更多和更优的测试资源分配方案,并满足用户需求的动态变化。

Testing resource allocation is a core problem in software testing.Most of the existing related studies assume that the software architecture is static and rarely consider cost constraints.To address this problem,a software testing resource allocation algorithm for dynamic changes in architecture was proposed.Firstly,a multi-stage multi-objective multiconstraint testing resource allocation model with dynamically changing architecture was constructed.Then,based on parameter re-estimation and generalized differential evolution,the population re-initialization was added to the algorithm,which was able to reduce the algorithm search space and improve the algorithm performance.Finally,a new repair processing mechanism was added to the algorithm,which was able to eliminate the invalid solutions generated by the algorithm effectively.Compared with the solution sets obtained by the Multi-Objective Differential Evolution based on Weighted Normalized Sum(WNS-MODE)algorithm and Dynamic Testing Resource Allocation based on Generalized Differential Evolution 3(DTRA-GDE3)algorithm,the solution set obtained by the proposed algorithm has the capacity value improved by about 11.81 times and 0.39 times respectively.In terms of coverage value metrics,the proposed algorithm completely covered the WNS-MODE algorithm and improved 81 percentage points with respect to the DTRA-GDE3 algorithm.In terms of the super volume value metrics,the proposed algorithm improved nearly 6 and 9 times,respectively.