一句话：提出研究议程，重新构想软件工程推荐系统如何向开发者传达建议，强调推荐多样性、差异呈现、交互导航与端到端评估。
推荐系统对软件工程师很有价值，例如提供可能含缺陷文件的排序列表或方法桩的多个自动补全建议。然而，它们与开发者的交互往往很原始：仅按模型置信度排列一长串推荐。这篇愿景论文提出一个研究议程，重新构想软件工程推荐系统如何向开发者传达洞见。其目标是在给出推荐时推荐多样而非冗余的解决方案，并以突出差异的方式呈现，同时支持对建议的无缝交互式导航，并追求整体性的端到端评估。作者认为，这样做能让推荐系统在帮助开发者写出更好软件方面发挥更重要作用。
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.
DOI 原文 ·
@inproceedings{paperbot7324,
title = {Taming Multi-Output Recommenders for Software Engineering},
author = {Christoph Treude},
booktitle = {ASE},
year = {2022},
doi = {10.1145/3551349.3559557}
}