To Do or Not To Do: Distill crowdsourced negative caveats to augment api documentation

Jing Li*, Aixin Sun, Zhenchang Xing

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    Negative caveats of application programming interfaces (APIs) are about “how not to use an API,” which are often absent from the official API documentation. When these caveats are overlooked, programming errors may emerge from misusing APIs, leading to heavy discussions on Q&A websites like Stack Overflow. If the overlooked caveats could be mined from these discussions, they would be beneficial for programmers to avoid misuse of APIs. However, it is challenging because the discussions are informal, redundant, and diverse. For this, for example, we propose Disca, a novel approach for automatically Distilling desirable API negative caveats from unstructured Q&A discussions. Through sentence selection and prominent term clustering, Disca ensures that distilled caveats are context-independent, prominent, semantically diverse, and nonredundant. Quantitative evaluation in our experiments shows that the proposed Disca significantly outperforms four text-summarization techniques. We also show that the distilled API negative caveats could greatly augment API documentation through qualitative analysis.

    Original languageEnglish
    Pages (from-to)1460-1475
    Number of pages16
    JournalJournal of the Association for Information Science and Technology
    Volume69
    Issue number12
    DOIs
    Publication statusPublished - Dec 2018

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