Finding Building Blocks for Software Clustering

摘要

It is generally believed that good modularization of software leads to systems which are easier to design, develop, test, maintain and evolve. Software clustering using search-based techniques has been well studied using a hill climbing approach. Hill climbing suffers from the problem of local optima, so some improvement may be expected by by considering more sophisticated search-based techniques. However, hitherto, the use of other techniques to overcome this problem such as Genetic Algorithms (GA) and Simulated Annealing have been disappointing. This poster paper looks at the possibility of using results from multiple hill climbs to form a basis for subsequent search. The findings will be presented in the poster created for the poster session in GECCO 2003.