一句话：研究表明命令推荐系统能帮助计算机科学学生掌握更多 IDE 命令，且非个性化流行度算法接受度最高。
开发工具影响软件工程师的生产力和软件质量，因此让未来软件工程师有效使用 IDE 功能十分重要。已有推荐研究多关注算法预测用户最终会使用哪些命令，却较少考察完整推荐系统在真实场景中的接受度。本文部署命令推荐系统，自动向计算机科学学生建议新的、有用的 IDE 命令，包括按钮和快捷键，并围绕系统整体接受度设计研究问题。评估结果表明，此类命令推荐系统能被学生较好接受；在有系统支持时，学生使用其开发环境中更大范围的命令。进一步结果发现，非个性化、基于流行度的算法获得最高接受率和有用性评分，而上下文感知算法推荐出最新颖的命令。
Development tools have an impact on software engineers' productivity and quality of software construction. We believe that it is crucial to teach future software engineers how to exploit integrated development environment functionality, if we want to encourage the effective application of software development principles and practices. Our research shows that recommender systems can be deployed to improve integrated development environment knowledge of computer science students by automatically suggesting new and useful commands, such as buttons and shortcuts that execute different functions. While previous work focused on optimizing the algorithmic predictive capability of a recommender to identify the commands that the users will eventually use, we have addressed a set of research questions related to the overall acceptance of a complete recommender system in a real-life setting. The evaluation results show that a command recommender system can be well accepted by computer science students. In particular, when students are supported by such a system, they use a considerably larger set of commands available in their development environment. Moreover, the results show that the highest acceptance rate and the usefulness score were achieved by a non-personalized, popularity-based algorithm, while the most novel commands were suggested by a context-aware algorithm.
DOI 原文 ·
@inproceedings{paperbot4557,
title = {Improving integrated development environment commands knowledge with recommender systems},
author = {Marko Gasparic and Tural Gurbanov and Francesco Ricci},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3183377.3183386}
}