Enabling heterogeneous recommendations in OSS development

Abstract

Open source software (OSS) forges contain rich data sources that are useful for supporting development activities. Research has been done to promote techniques and tools for providing open source developers with innovative features aiming at obtaining improvements in terms of development effort, cost savings, and developer productivity, just to mention a few. In the context of the EU H2020 CROSSMINER project we are conceiving a set of recommendations to assist software programmers in different phases of the development process. To this end, we defined a graph-based representation to encode in a homogeneous manner different aspects of OSS ecosystems as well as to incorporate various well-founded recommendation techniques. Following the proposed paradigm, we have implemented recommender systems for providing various artifacts, such as third-party libraries and API usage. The preliminary results we achieved so far are promising: our proposed systems are able to suggest highly relevant items with respect to the current development context. In this paper, we describe what has been achieved so far as well as our planned medium and longer-term objectives. As a proof of concept, we present a use case where we built a context-aware recommender system to recommend API function calls and usage patterns.