TY - JOUR
T1 - To Do or Not To Do
T2 - Distill crowdsourced negative caveats to augment api documentation
AU - Li, Jing
AU - Sun, Aixin
AU - Xing, Zhenchang
N1 - Publisher Copyright:
© 2018 ASIS&T
PY - 2018/12
Y1 - 2018/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85052505816&partnerID=8YFLogxK
U2 - 10.1002/asi.24067
DO - 10.1002/asi.24067
M3 - Article
SN - 2330-1635
VL - 69
SP - 1460
EP - 1475
JO - Journal of the Association for Information Science and Technology
JF - Journal of the Association for Information Science and Technology
IS - 12
ER -