Abstract
Abstract Nowadays, component identification is one of the main challenges of software analysis and design. The component identification process aims at clustering classes into components and subcomponents. There are a number of methods to identify components in the literature; however, most of them cannot be customized to software architect’s preferences. To address this limitation, in this paper, we propose a preference-based method by the name of preference-based component identification using particle swarm optimization (PCI-PSO) to identify logical components. PCI-PSO provides a novel method to handle the software architect’s preferences using an interactive (i.e. human in the loop) search. PCI-PSO employs a customized PSO to automatically classify classes into suitable logical components and avoid the problem of identifying the proper number of components. We evaluated the effectiveness of PCI-PSO with four real-world cases. Results revealed that PCI-PSO has an ability to identify more cohesive and independent components with respect to the software architect’s preferences in comparison to the existing component identification methods.
Published Version
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