research-article

Software documentation issues unveiled

Authors:

Olga Lucero Vega-Márquez,

Mario Linares-Vásquez,

Gabriele Bavota,

Michele LanzaAuthors Info & Claims

ICSE '19: Proceedings of the 41st International Conference on Software Engineering

Pages 1199 - 1210

https://doi.org/10.1109/ICSE.2019.00122

Published: 25 May 2019 Publication History

Abstract

(Good) Software documentation provides developers and users with a description of what a software system does, how it operates, and how it should be used. For example, technical documentation (e.g., an API reference guide) aids developers during evolution/maintenance activities, while a user manual explains how users are to interact with a system. Despite its intrinsic value, the creation and the maintenance of documentation is often neglected, negatively impacting its quality and usefulness, ultimately leading to a generally unfavorable take on documentation.

Previous studies investigating documentation issues have been based on surveying developers, which naturally leads to a somewhat biased view of problems affecting documentation. We present a large scale empirical study, where we mined, analyzed, and categorized 878 documentation-related artifacts stemming from four different sources, namely mailing lists, Stack Overflow discussions, issue repositories, and pull requests. The result is a detailed taxonomy of documentation issues from which we infer a series of actionable proposals both for researchers and practitioners.

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Published In

cover image ACM Conferences

ICSE '19: Proceedings of the 41st International Conference on Software Engineering

May 2019

1318 pages

General Chair:
Joanne M. Atlee
University of Waterloo, Canada
,
Program Chairs:
Tevfik Bultan
University of California, Santa Barbara
,
Jon Whittle
Monash University, Australia

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SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS: Computer Society

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IEEE Press

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Published: 25 May 2019

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ICSE '19: 41st International Conference on Software Engineering

May 25 - 31, 2019

Quebec, Montreal, Canada

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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https://dl.acm.org/doi/10.5555/3696899.3696901
Gao HZahedi MTreude CRosenstock SCheong M(2024)Documenting Ethical Considerations in Open Source AI ModelsProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686679(177-188)Online publication date: 24-Oct-2024
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