2022/07/31 by Christoph Treude, Treude, Christoph
Computer Science · #Advanced Software Engineering Methodologies #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Software Engineering (cs.SE) #Software Engineering Research #Software Engineering Techniques and Practices
paper · pdf · doi:10.48550/arxiv.2208.00443
openalex publication_date 2022/07/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recommender systems are a valuable tool for software engineers. For example, they can provide developers with a ranked list of files likely to contain a bug, or multiple auto-complete suggestions for a given method stub. However, the way these recommender systems interact with developers is often rudimentary -- a long list of recommendations only ranked by the model's confidence. In this vision paper, we lay out our research agenda for re-imagining how recommender systems for software engineering communicate their insights to developers. When issuing recommendations, our aim is to recommend diverse rather than redundant solutions and present them in ways that highlight their differences. We also want to allow for seamless and interactive navigation of suggestions while striving for holistic end-to-end evaluations. By doing so, we believe that recommender systems can play an even more important role in helping developers write better software.