arrow
Return

Diverse title generation for Stack Overflow posts with multiple-sampling-enhanced transforme

delete2023-06-01
delete6
delete
OA
AI
Z
Zhang, Fengji
J
Jin Liu *
Y
Yao Wan
X
Xiao Yu *
刘笑 cover
刘笑 (Xiao Liu)
J
Jacky Keung
DOI:10.1016/j.jss.2023.111672delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Stack Overflow is one of the most popular programming communities where developers can seek help for their encountered problems. Nevertheless, if inexperienced developers fail to describe their problems clearly, it is hard for them to attract sufficient attention and get the anticipated answers. To address such a problem, we propose M3NSCT5, a novel approach to automatically generate multiple post titles from the given code snippets. Developers may take advantage of the generated titles to find closely related posts and complete their problem descriptions. M3NSCT5 employs the CodeT5 backbone, which is a pre-trained Transformer model with an excellent language understanding and generation ability. To alleviate the ambiguity issue that the same code snippets could be aligned with different titles under varying contexts, we propose the maximal marginal multiple nucleus sampling strategy to generate multiple high-quality and diverse title candidates at a time for the developers to choose from. We build a large-scale dataset with 890,000 question posts covering eight programming languages to validate the effectiveness of M3NSCT5. The automatic evaluation results on the BLEU and ROUGE metrics demonstrate the superiority of M3NSCT5 over six state-of-the-art baseline models. Moreover, a human evaluation with trustworthy results also demonstrates the great potential of our approach for real-world applications.(c) 2023 Elsevier Inc. All rights reserved.
Keywords:
Stack Overflow
Title generation
CodeT5
Nucleus sampling
Maximal marginal ranking
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Systems and Software cover
Journal of Systems and Software
IF:
4.1
Papers:
5.4K
Citations:
8.4K

Organization

C
City University of Hong Kong
Scholars:
2.3W
Papers: 3.0W
Citations: 6.1W
W
Wuhan University of Technology
Scholars:
3.4W
Papers: 2.4W
Citations: 4.4W
D
Deakin University
Scholars:
2.0W
Papers: 2.1W
Citations: 2.8W
W
wuhan university
Scholars:
8.0W
Papers: 5.8W
Citations: 70
researcher View more organizations