Niche vs. breadth: Calculating expertise over time through a fine-grained analysis

Identifying expertise in a project is essential for task allocation, knowledge dissemination, and risk management, among other activities. However, keeping a detailed record of such expertise at class and method levels is cumbersome due to project size, evolution, and team turnover. Existing approaches that automate this task have limitations in terms of the number and granularity of elements that can be analyzed and the analysis timeframe. In this paper, we introduce a novel technique to identify expertise for a given project, package, file, class, or method by considering not only the total number of edits that a developer has made, but also the spread of their changes in an artifact over time, and thereby the breadth of their expertise. We use Dominoes - our GPU-based approach for exploratory repository analysis - for expertise identification over any given granularity and time period with a short processing time. We evaluated our approach through Apache Derby and observed that granularity and time can have significant influence on expertise identification.