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Improving Integrated Development Environment Commands Knowledge With Recommender Systems

机译:推荐系统改善集成开发环境的命令知识

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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.
机译:开发工具会影响软件工程师的生产率和软件构建质量。我们认为,如果我们想鼓励有效地应用软件开发原则和实践,那么教给未来的软件工程师如何利用集成开发环境功能至关重要。我们的研究表明,可以通过自动建议新的和有用的命令(例如执行不同功能的按钮和快捷键)来部署推荐系统,以提高计算机科学专业学生的集成开发环境知识。先前的工作集中在优化推荐器的算法预测能力以识别用户最终将使用的命令的同时,我们已经解决了一系列与现实环境中对整个推荐器系统的总体接受程度有关的研究问题。评估结果表明,计算机科学专业的学生可以很好地接受命令推荐系统。尤其是,当学生得到这种系统的支持时,他们会使用开发环境中可用的大量命令。此外,结果表明,通过非个性化的基于流行度的算法可以实现最高的接受率和有用性评分,而通过上下文感知的算法可以建议最新颖的命令。

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