Automatic summarization of API reviews

摘要

With the proliferation of online developer forums as informal documentation, developers often share their opinions about the APIs they use. However, given the plethora of opinions available for an API in various online developer forums, it can be challenging for a developer to make informed decisions about the APIs. While automatic summarization of opinions have been explored for other domains (e.g., cameras, cars), we found little research that investigates the benefits of summaries of public API reviews. In this paper, we present two algorithms (statistical and aspect-based) to summarize opinions about APIs. To investigate the usefulness of the techniques, we developed, Opiner, an online opinion summarization engine that presents summaries of opinions using both our proposed techniques and existing six off-the-shelf techniques. We investigated the usefulness of Opiner using two case studies, both involving professional software engineers. We found that developers were interested to use our proposed summaries much more frequently than other summaries (daily vs once a year) and that while combined with Stack Overflow, Opiner helped developers to make the right decision with more accuracy and confidence and in less time.