Software Clustering using Hybrid Multi-Objective Black Hole Algorithm
نویسندگان
چکیده
Software clustering is the process of organizing software units into appropriate clusters so as to efficiently modularize complex program structure. In this paper, we investigate the use of hybrids of Black Hole algorithm (developed using weighted aggregation, auxiliary archive and Genetic Algorithm) to optimize multiple objectives for clustering of android mobile applications. It is empirically and statistically observed that multi-objective Black Hole algorithm when improved using Genetic Algorithm and auxiliary archive outperforms Two-Archive algorithm and its counterparts. Keywordsbio-inspired algorithm, edgesim, nature-inspired algorithm, serach based software engineering, software clsutering
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