测试性增长中资源优化配置模型及求解

Resource allocation problem formulation and solution in testability growth

良好的测试性设计对系统维修性具有重要意义,测试性增长试验通过一系列测试性设计缺陷发现和纠正措施,可保证系统测试性指标达到设计要求。针对基于延缓纠正的测试性增长过程中的资源配置问题进行研究,基于增长试验目标是否明确和试验资源是否受限制问题构建资源优化配置模型,并提出一种基于拉格朗日松弛和本地搜索的快速优化算法。仿真结果表明:该模型能够有效指导测试性增长中的资源优化配置问题,所提混合优化方法能够高效、准确地求解整数规划问题。

Testability is crucial for the enhancement of system maintainability, and testability growth can promote the testability metric of the system to satisfy the design requirements by a series action of identifying and correcting the testability design defects. The test resources allocating problem arising in delay fix based testability growth was studied and modeled, considering that whether there are constrains on the growth object and growth test cost or not. A Lagrangian relaxation algorithm and local search hybrid optimal algorithm were applied to solve this problem. Simulation results show that the proposed model is feasible for the test resources allocating problem in testability growth test, and the hybrid optimal algorithm can promise the effectiveness and accuracy to the integer programming problem.