Context extraction in recommendation systems in software engineering: a preliminary survey
Sana Maki, Sègla Kpodjedo, Ghizlane El Boussaidi · Computer Science and Software Engineering · 2015
Recommendation System in Software Engineering (RSSE) represents a new promising research area, whose goal is to help software developers in their tasks by providing them with context-dependent insights extracted from their current project or taken from best practices. A key challenge here is to retrieve the context from the programming task in order to provide useful recommendations. In this paper, we conduct a survey of RSSEs with a particular focus on different approaches used to extract the context. We propose a feature model to represent some important characteristics of such extraction and identify some open issues.