Endowing third-party libraries recommender systems with explicit user feedback mechanisms
Riccardo Rubei, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen · 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · 2022
During their daily routine, developers often deal with a plethora of resources, attempting to search for relevant artifacts that can be added to the project under development. This kind of information overload may render developers overwhelmed, thus undermining their productivity and efficiency. Recommender systems are an effective means of easing such a burden, providing relevant items for the current programming contexts, e.g., third-party libraries (TPLs), API calls, or code snippets. By focusing on TPLs, there has been no work to allow for the integration of tailored feedback mechanisms with which users can conveniently accept or discard libraries. In this paper, we propose an approach to handle explicit user feedback, including positive, negative, and additive. Thus, further than accepting or discarding the recommended TPLs, users can also endorse libraries that, in their opinion, are relevant for the current context, even though they are not included in the provided recommendations. As a proof of concept, we demonstrate how user feedback generated by the proposed mechanism can change the outcome of a real TPLs recommender system. The results show that our proposed approach helps the considered system retrieve relevant items, under different configurations.