Test Point Selection Method Research Based on Genetic Algorithm and Binary Particle Swarm Optimization Algorithm

摘要

Test point selection is the foundation of testability analysis and design. A minimal complete subset of genetic algorithm and binary particle swarm optimization algorithm is proposed to meet testability index requirements. Firstly, the mathematical model is established based on analyzing the testability problems. Then, the heuristic function is constructed to measure the pros and cons of the test set. Experimental results show that the algorithm can effectively overcome the deficiency of a single algorithm going into a local optimum and premature convergence, and improve the searching efficiency to obtain a global optimal solution quickly.