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Towards crowd-sourced API documentation

Published: 25 May 2019 Publication History

Abstract

The learnability of an API suffers when the official documentation of the API is incomplete. Developers discuss usage scenarios of APIs in the online developer forums. As such, by automatically mining such crowd-sourced documentation of APIs, we can address the shortcomings of API official documentation. We present a framework to automatically mine usage scenarios about APIs from online developer forums. Each usage scenario of an API consists of a code example, a summary description, and the reactions (i.e., positive and negative opinions) of other developers towards the code example. We evaluate our API usage mining framework by producing a benchmark dataset. We observed a precision of 0.947 and a recall of 1.0 with the linking of a code example to an API mention in the forum.

References

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S. Subramanian, L. Inozemtseva, and R. Holmes, "Live API documentation," in Proc. 36th International Conference on Software Engineering, 2014, p. 10.
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C. Treude and M. P. Robillard, "Augmenting API documentation with insights from stack overflow," in Proc. 38th International Conference on Software Engineering, 2016, pp. 392--403.
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H. Phan, H. A. Nguyen, N. M. Tran, L. H. Truong, A. T. Nguyen, and T. N. Nguyen, "Statistical learning of api fully qualified names in code snippets of online forums," in Proceedings of 40th International Conference on Software Engineering, 2018, pp. 632--642.
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Published In

cover image ACM Conferences
ICSE '19: Proceedings of the 41st International Conference on Software Engineering: Companion Proceedings
May 2019
369 pages

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IEEE Press

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Published: 25 May 2019

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Author Tags

  1. API
  2. mining
  3. usage

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ICSE '19
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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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