Software Product Maintainability Prediction: A Survey of Secondary Studies

Software Product Maintainability Prediction (SPMP) has received more attention from researchers to control the high costs of software maintenance. Many studies related to this topic have been published in the recent years. Some of them, referred to as secondary studies, focused on the interpretation and synthesis of available published research by giving an up-to-date state of the art about SPMP. This state of the art is provided in a form of literature survey or in a rigorous systematic literature review. The objective of this paper is to investigate these secondary studies to discuss methods that they use and contents that they cover. A set of survey research questions have been proposed and discussed through the investigation of nine selected secondary studies collected from different digital libraries. Based on the results, the analysis shows that maintainability prediction models/techniques as well as maintainability key predictors measures/factors are the most studied aspects in SPMP. Moreover, there is a need to address in depth the performance of SPMP models as well as their validation. We believe that this study will be a reliable basis for further research in software maintainability studies.