Test Selection Based on Improved Binary Particle Swarm Optimization

摘要：

Test Selection in DFT (Design For Test) is known to be a NP-complete problem. Applying particle swarm optimization algorithm to test selection is firstly proposed in this paper. By analyzing characteristics of test selection, it constructs particles and velocities of BPSO (Binary Particle Swarm Optimization); It optimizes the particles using the fitness, which includes the indexes of test selection, and adds multiform inertial weight to BPSO according to its characteristic of getting into local optimal easily. The experimental results show that the proposed algorithm can earlier achieve higher fault detection rate, isolation rate and more compact test sets when compared to other similar test selection algorithms.

作者: Ronghua JIANG Bin LONG Houjun WANG

作者单位: University of Electronic Science and Technology of China, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）