Combining techniques for software quality classification: An integrated decision network approach

Accurately predicting fault-prone modules is a major problem in quality control of a software system during software development. Selecting an appropriate suggestion from various software quality classification models is a difficult decision for software project managers. In this paper, an integrated decision network is proposed to combine the well-known software quality classification models in providing the summarized suggestion. A particle swarm optimization algorithm is used to search for suitable combinations among the software quality classification models in the integrated decision network. The experimental results show that the proposed integrated decision network outperforms the independent software quality classification models. It also provides an appropriate summary for decision makers.