Most of the search-based software remodularization(SBSR)approaches designed to address the software remodularization problem(SRP)areutilizing only structural information-based coupling and cohesion quality criteria.Ho...Most of the search-based software remodularization(SBSR)approaches designed to address the software remodularization problem(SRP)areutilizing only structural information-based coupling and cohesion quality criteria.However,in practice apart from these quality criteria,there require other aspects of coupling and cohesion quality criteria such as lexical and changed-history in designing the modules of the software systems.Therefore,consideration of limited aspects of software information in the SBSR may generate a sub-optimal modularization solution.Additionally,such modularization can be good from the quality metrics perspective but may not be acceptable to the developers.To produce a remodularization solution acceptable from both quality metrics and developers’perspectives,this paper exploited more dimensions of software information to define the quality criteria as modularization objectives.Further,these objectives are simultaneously optimized using a tailored manyobjective artificial bee colony(MaABC)to produce a remodularization solution.To assess the effectiveness of the proposed approach,we applied it over five software projects.The obtained remodularization solutions are evaluated with the software quality metrics and developers view of remodularization.Results demonstrate that the proposed software remodularization is an effective approach for generating good quality modularization solutions.展开更多
文摘Most of the search-based software remodularization(SBSR)approaches designed to address the software remodularization problem(SRP)areutilizing only structural information-based coupling and cohesion quality criteria.However,in practice apart from these quality criteria,there require other aspects of coupling and cohesion quality criteria such as lexical and changed-history in designing the modules of the software systems.Therefore,consideration of limited aspects of software information in the SBSR may generate a sub-optimal modularization solution.Additionally,such modularization can be good from the quality metrics perspective but may not be acceptable to the developers.To produce a remodularization solution acceptable from both quality metrics and developers’perspectives,this paper exploited more dimensions of software information to define the quality criteria as modularization objectives.Further,these objectives are simultaneously optimized using a tailored manyobjective artificial bee colony(MaABC)to produce a remodularization solution.To assess the effectiveness of the proposed approach,we applied it over five software projects.The obtained remodularization solutions are evaluated with the software quality metrics and developers view of remodularization.Results demonstrate that the proposed software remodularization is an effective approach for generating good quality modularization solutions.
