基于用户反馈的API推荐工具

API Recommendation Tool Based on User Feedback

在软件开发的过程中,开发人员经常会检索合适的API来完成编程任务.为了提高软件开发效率,大量API推荐方法及工具应运而生.然而,这些方法大多数都没有考虑用户交互信息.本文提出了一个基于客户端/服务器架构的API推荐工具,将其以插件的形式集成到VS Code IDE中.本工具使用现有的API推荐工具生成初始API推荐列表,结合用户反馈信息,利用排序学习和主动学习技术对API推荐列表进行重新排序,实现了用户个性化推荐.大量实验证明,随着反馈数据量的增加,本工具的性能稳步提升.

Developers often search for appropriate APIs to complete programming tasks during software development.Many API recommendation approaches and tools have been proposed to improve the efficiency of software development,but most of these approaches do not consider user interaction information.In this study,we propose an API recommendation tool based on client/server architecture and integrate it into the VS Code IDE in the form of a plug-in.In our tool,initial API recommendation lists are generated by existing tools.Learning-to-rank and active learning techniques are used,combined with user feedback information,to re-rank the API recommendation lists,achieving personalized recommendation.Extensive experiments demonstrate that the performance of this tool has been steadily improved with the increase in feedback data.