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The existing rule-based perforrnance optimization approaches at software architecture (SA) level don' t fully concern the improvement range of the rule and the uncertainty of the count and the order of each rule usage in the opti mization process. As a result , the search space for performance improvement is limited and the better solutions are hard to find. Aim丑lÌng a 川t this problem 丑1 , firs 悦tly , a group of the random search rules (RSRsω) we盯re designed based on pe盯rforrn 丑mnce

基于随机搜索规则的软件体系结构层性能演化优化方法 (Random Search Rule Based Performance Evolutionary Optimization Method at Software Architecture Level).