MARBLE: Mining for Boilerplate Code to Identify API Usability Problems

Designing usable APIs is critical to developers’ productivity and software quality, but is quite difficult. One of the challenges is that anticipating API usability barriers and real world usage is difficult, due to a lack of automated approaches to mine usability data at scale. In this paper, we focus on one particular grievance that developers repeatedly express in online discussions about APIs: “boilerplate code.” We investigate what properties make code count as boilerplate, the reasons for boilerplate, and how programmers can reduce the need for it. We then present MARBLE, a novel approach to automatically mine boilerplate code candidates from API client code repositories. MARBLE adapts existing techniques, including an API usage mining algorithm, an AST comparison algorithm, and a graph partitioning algorithm. We evaluate MARBLE with 13 Java APIs, and show that our approach successfully identifies both already known and new API-related boilerplate code instances.

• Data Mining and Modeling

• Software Engineering