Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

5-2023

Abstract

Stack Overflow is a popular platform for developers to seek solutions to programming-related problems. However, prior studies identified that developers may suffer from the redundant, useless, and incomplete information retrieved by the Stack Overflow search engine. To help developers better utilize the Stack Overflow knowledge, researchers proposed tools to summarize answers to a Stack Overflow question. However, existing tools use hand-craft features to assess the usefulness of each answer sentence and fail to remove semantically redundant information in the result. Besides, existing tools only focus on a certain programming language and cannot retrieve up-to-date new posted knowledge from Stack Overflow. In this paper, we propose TECHSUMBOT, an automatic answer summary generation tool for a technical problem. Given a question, TECH-SUMBOT first retrieves answers using the Stack Overflow search engine, then TECHSUMBOT 1) ranks each answers sentence based on the sentence's usefulness, 2) estimates the centrality of each sentence to all candidates, and 3) removes the semantic redundant information. Finally, TECHSUMBOT returns the top 5 ranked answer sentences as the answer summary. We implement TECHSUMBOT in the form of a search engine website. To evalu-ate TECHSUMBOT in both automatic and manual manners, we construct the first Stack Overflow multi-answer summarization benchmark and design a manual evaluation study to assess the effectiveness of TECHSUMBOT and state-of-the-art baselines from the NLP and SE domain. Both results indicate that the summaries generated by TECHSUMBOT are more diverse, useful, and similar to the ground truth summaries. Tool Link: www.techsumbot.com Video Link: https://youtube.com/watchvozuJOp_vILMReplicationPackage: https://github.com/TechSumBot/TechSumBot

Keywords

Computer languages, Semantics, Manuals, Search engines, Benchmark testing, Software engineering

Discipline

Artificial Intelligence and Robotics | Software Engineering | Theory and Algorithms

Research Areas

Cybersecurity; Intelligent Systems and Optimization; Software and Cyber-Physical Systems

Publication

45th IEEE/ACM International Conference on Software Engineering: ICSE 2023 Companion Proceedings, Melbourne, Australia, May 14-20

First Page

132

Last Page

135

ISBN

9798350322644

Identifier

10.1109/ICSE-Companion58688.2023.00040

Publisher

IEEE

City or Country

New York, NY, USA

Additional URL

https://doi.org/10.1109/ICSE-Companion58688.2023.00040

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