TY - GEN
T1 - Extracting API tips from developer question and answer websites
AU - Wang, Shaohua
AU - Phan, Nhathai
AU - Wang, Yan
AU - Zhao, Yong
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - The success of question and answer (Q&A) websites attracts massive user-generated content for using and learning APIs, which easily leads to information overload: many questions for APIs have a large number of answers containing useful and irrelevant information, and cannot all be consumed by developers. In this work, we develop DeepTip, a novel deep learning-based approach using different Convolutional Neural Network architectures, to extract short practical and useful tips from developer answers. Our extensive empirical experiments prove that DeepTip can extract useful tips from a large corpus of answers to questions with high precision (i.e., avg. 0.854) and coverage (i.e., 0.94), and it outperforms two state-of-the-art baselines by up to 56.7% and 162%, respectively, in terms of Precision. Furthermore, qualitatively, a user study is conducted with real Stack Overflow users and its results confirm that tip extraction is useful and our approach generates high-quality tips.
AB - The success of question and answer (Q&A) websites attracts massive user-generated content for using and learning APIs, which easily leads to information overload: many questions for APIs have a large number of answers containing useful and irrelevant information, and cannot all be consumed by developers. In this work, we develop DeepTip, a novel deep learning-based approach using different Convolutional Neural Network architectures, to extract short practical and useful tips from developer answers. Our extensive empirical experiments prove that DeepTip can extract useful tips from a large corpus of answers to questions with high precision (i.e., avg. 0.854) and coverage (i.e., 0.94), and it outperforms two state-of-the-art baselines by up to 56.7% and 162%, respectively, in terms of Precision. Furthermore, qualitatively, a user study is conducted with real Stack Overflow users and its results confirm that tip extraction is useful and our approach generates high-quality tips.
KW - API
KW - CNN
KW - Deep learning
KW - Sentence classification
KW - Tip extraction
UR - http://www.scopus.com/inward/record.url?scp=85072345840&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072345840&partnerID=8YFLogxK
U2 - 10.1109/MSR.2019.00058
DO - 10.1109/MSR.2019.00058
M3 - Conference contribution
AN - SCOPUS:85072345840
T3 - IEEE International Working Conference on Mining Software Repositories
SP - 321
EP - 332
BT - Proceedings - 2019 IEEE/ACM 16th International Conference on Mining Software Repositories, MSR 2019
PB - IEEE Computer Society
T2 - 16th IEEE/ACM International Conference on Mining Software Repositories, MSR 2019
Y2 - 26 May 2019 through 27 May 2019
ER -