An Approach to Context-Based Recommendation in Software Development

Authors

Abstract

A software developer programming in an object-oriented programming language deals with a source code structure that may contain hundreds of source code elements. These elements are commonly related to each other and working on a specific element may require the developer to access other related elements. We propose a recommendation approach that uses the context of the developer to retrieve and rank recommendations of relevant source code elements in the IDE. These recommendations provide a shortcut to reach the desired elements and increase the awareness of the developer in relation to elements that may be of interest in that moment. We have tested our approach with a group of developers and the results show that context has a promising role in predicting and ranking the source code elements needed by a developer at each moment.

Keywords

Recommendation Systems, Context Modeling, Ontologies, Software Development, IDE

Subject

Artificial Intelligence

Related Project

SDiC: Software Development in Context

Conference

6th ACM Conference on Recommender Systems (RecSys), September 2012