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TDMentions: A Dataset of Technical Debt Mentions in Online Posts
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0003-1173-5187
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0002-0835-823X
2019 (English)In: 2019 IEEE/ACM INTERNATIONAL CONFERENCE ON TECHNICAL DEBT (TECHDEBT 2019), IEEE, 2019, p. 123-124Conference paper, Published paper (Refereed)
Abstract [en]

The term technical debt is easy to understand as a metaphor, but can quickly grow complex in practice. We contribute with a dataset, TDMentions, that enables researchers to study how developers and end users use the term technical debt in online posts and discussions. The dataset consists of posts from news aggregators and Q&A-sites, blog posts, and issues and commits on GitHub.
Place, publisher, year, edition, pages
IEEE, 2019. p. 123-124
Keywords [en]
Technical debt, Data mining, Social networks
National Category
Computer and Information Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-90909DOI: 10.1109/TechDebt.2019.00031ISI: 000502789500023Scopus ID: 2-s2.0-85071193532ISBN: 978-1-7281-3371-3 (print)OAI: oai:DiVA.org:lnu-90909DiVA, id: diva2:1385710
Conference
2nd IEEE/ACM International Conference on Technical Debt (TechDebt), Montreal, CANADA, MAY 26-27, 2019
Available from: 2020-01-15 Created: 2020-01-15 Last updated: 2021-02-03Bibliographically approved

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Ericsson, MorganWingkvist, Anna

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Citation style
  • apa
  • ieee
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
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