research-article

Detecting speech act types in developer question/answer conversations during bug repair

Authors:

Paige Rodeghero,

Collin McMillanAuthors Info & Claims

ESEC/FSE 2018: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Pages 491 - 502

https://doi.org/10.1145/3236024.3236031

Published: 26 October 2018 Publication History

Abstract

This paper targets the problem of speech act detection in conversations about bug repair. We conduct a ``Wizard of Oz'' experiment with 30 professional programmers, in which the programmers fix bugs for two hours, and use a simulated virtual assistant for help. Then, we use an open coding manual annotation procedure to identify the speech act types in the conversations. Finally, we train and evaluate a supervised learning algorithm to automatically detect the speech act types in the conversations. In 30 two-hour conversations, we made 2459 annotations and uncovered 26 speech act types. Our automated detection achieved 69% precision and 50% recall. The key application of this work is to advance the state of the art for virtual assistants in software engineering. Virtual assistant technology is growing rapidly, though applications in software engineering are behind those in other areas, largely due to a lack of relevant data and experiments. This paper targets this problem in the area of developer Q/A conversations about bug repair.

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Index Terms

Detecting speech act types in developer question/answer conversations during bug repair
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software

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cover image ACM Conferences

ESEC/FSE 2018: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

October 2018

987 pages

ISBN:9781450355735

DOI:10.1145/3236024

General Chair:
Gary T. Leavens
University of Central Florida, USA
,
Program Chairs:
Alessandro Garcia
PUC-Rio, Brazil
,
Corina S. Păsăreanu
NASA Ames Research Center, USA

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Published: 26 October 2018

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https://doi.org/10.36057/jilp.v7i2.662
Khojah RMohamad MLeitner Pde Oliveira Neto F(2024)Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering PracticeProceedings of the ACM on Software Engineering10.1145/36607881:FSE(1819-1840)Online publication date: 12-Jul-2024
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