Analyzing and Supporting Adaptation of Online Code Examples
Technical TrackIndustry Program
Developers often resort to online Q&A forums such as Stack Overflow for filling their programming needs. Although SO examples are good starting points, they are often incomplete and inadequate for the local context of the developers; adaptation of those examples is necessary to integrate them to production code. As a consequence, the process of adapting online examples is done over and over again, by multiple developers independently. We study these adaptations and variations, serving as the basis for a tool that helps integrate these online code examples in a target context in an interactive manner. We perform a large-scale empirical study about nature and extent of adaptations and variations of SO snippets. We construct a comprehensive dataset linking SO posts to GitHub counterparts based on clone detection, time stamp analysis, and explicit URL references. We then qualitatively inspect 400 SO examples and their GitHub counterparts and develop a taxonomy of 24 adaptation types. Using this taxonomy, we build an automated adaptation analysis technique on top of GumTree to classify the entire dataset into these categories. We build a Chrome extension called ExampleStack that automatically lifts an adaptation-aware template from each SO example and its GitHub counterparts to identify hot spots where most changes happen. A user study with twelve programmers shows that seeing the commonality and variations in similar GitHub counterparts increases their confidence about how to reuse the given SO example, and helps grasp a more comprehensive view about how to reuse the example differently and avoid common pitfalls.