Hipikat: Recommending Pertinent Software Development Artifacts

Abstract

A newcomer to a software project must typically come up-to-speed on a large, varied amount of information about the project before becoming productive. Assimilating this information in the open-source context is difficult because a newcomer cannot rely on the mentoring approach that is commonly used in traditional software developments. To help a newcomer to an open-source project become productive faster, we propose Hipikat, a tool that forms an implicit group memory from the information stored in a project's archives, and that recommends artifacts from the archives that are relevant to a task that a newcomer is trying to perform. To investigate this approach, we have instantiated the Hipikat tool for the Eclipse open-source project. In this paper we describe the Hipikat tool, we report on a qualitative study conducted with a Hipikat mock-up on a medium-sized in-house project, and we report on a case study in which Hipikat recommendations were evaluated for a task on Eclipse.