| Popis: |
When working in large and complex codebases, developers face challenges using \textit{Find Usages} to understand how to reuse classes and methods. To better understand these challenges, we conducted a small exploratory study with 4 participants. We found that developers often wasted time reading long lists of similar usages or prematurely focused on a single usage. Based on these findings, we hypothesized that clustering usages by the similarity of their surrounding context might enable developers to more rapidly understand how to use a function. To explore this idea, we designed and implemented \textit{Find Unique Usages}, which extracts usages, computes a diff between pairs of usages, generates similarity scores, and uses these scores to form usage clusters. To evaluate this approach, we conducted a controlled experiment with 12 participants. We found that developers with Find Unique Usages were significantly faster, completing their task in 35% less time. |
