NavClus:一个帮助代码探索的图形化推荐器

Seonah Lee, Sungwon Kang, Matthew Staats
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引用次数: 6

摘要

最近,人们提出了一些图形化工具来帮助开发人员在处理大型软件项目时避免迷失方向。这些工具将开发人员访问过的位置可视化,使他们能够快速回忆起他们已经访问过的位置。然而,开发人员还花费了大量的时间来探索要访问的源位置,这是现有工具目前不支持的任务。在这项工作中,我们提出了一个图形代码推荐器NavClus,它可以帮助开发人员找到相关的、未开发的源代码位置来访问。NavClus通过挖掘开发人员的日常交互痕迹,将开发人员当前的工作环境与之前看到的环境进行比较,然后预测相关的访问源位置。这些位置与类图中已经探索过的位置一起以图形方式显示。因此,使用NavClus,开发人员可以快速找到、到达并关注与其工作环境相关的源位置。http://www.youtube.com/watch?v=rbrc5ERyWjQ。
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NavClus: A graphical recommender for assisting code exploration
Recently, several graphical tools have been proposed to help developers avoid becoming disoriented when working with large software projects. These tools visualize the locations that developers have visited, allowing them to quickly recall where they have already visited. However, developers also spend a significant amount of time exploring source locations to visit, which is a task that is not currently supported by existing tools. In this work, we propose a graphical code recommender NavClus, which helps developers find relevant, unexplored source locations to visit. NavClus operates by mining a developer's daily interaction traces, comparing the developer's current working context with previously seen contexts, and then predicting relevant source locations to visit. These locations are displayed graphically along with the already explored locations in a class diagram. As a result, with NavClus developers can quickly find, reach, and focus on source locations relevant to their working contexts. http://www.youtube.com/watch?v=rbrc5ERyWjQ.
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