NavClus: A Graphical Recommender for Assisting Code Exploration

Seonah Lee, Sungwon Kang, and Matt Staats

KAIST, South Korea

Track: Formal Tool Demonstrations
Session: Formal Demonstrations 1
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 developers daily interaction traces, comparing the developers 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.