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The online technical Q&A site Stack Overflow (SO) is popular among developersto support their coding and diverse development needs. To address shortcomingsin API official documentation resources, several research has thus focused onaugmenting official API documentation with insights (e.g., code examples) fromSO. The techniques propose to add code examples/insights about APIs into itsofficial documentation. Reviews are opinionated sentences withpositive/negative sentiments. However, we are aware of no previous researchthat attempts to automatically produce API documentation from SO by consideringboth API code examples and reviews. In this paper, we present two novelalgorithms that can be used to automatically produce API documentation from SOby combining code examples and reviews towards those examples. The firstalgorithm is called statistical documentation, which shows the distribution ofpositivity and negativity around the code examples of an API using differentmetrics (e.g., star ratings). The second algorithm is called concept-baseddocumentation, which clusters similar and conceptually relevant usagescenarios. An API usage scenario contains a code example, a textual descriptionof the underlying task addressed by the code example, and the reviews (i.e.,opinions with positive and negative sentiments) from other developers towardsthe code example. We deployed the algorithms in Opiner, a web-based platform toaggregate information about APIs from online forums. We evaluated thealgorithms by mining all Java JSON-based posts in SO and by conducting threeuser studies based on produced documentation from the posts.

Automatic API Usage Scenario Documentation from Technical Q&A Sites