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Exploring the Relationship between Technical Debt and Lead Time: An Industrial Case Study
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0009-0004-5806-6624
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-1350-7030
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-1729-5154
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-1987-2234
2025 (English)In: Proceedings - 2025 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2025, Institute of Electrical and Electronics Engineers (IEEE), 2025, p. 693-703Conference paper, Published paper (Refereed)
Abstract [en]

Background: Software companies must balance fast delivery and quality, a trade-off that often introduces technical debt and wastes developer's time. Technical debt tends to increase as software evolves, which is assumed to slow down development and maintenance activities. However, the potential relationship between technical debt and lead time lacks empirical evidence.

Objective: This paper reports an empirical study to explore the potential relationship between technical debt and lead time in resolving Jira tickets. We further aim to measure the extent to which technical debt can explain the variation in lead time.

Method: We conducted an industrial case study to explore this relationship in six components, each of which was analyzed individually. Technical debt was measured using SonarQube and normalized with the component's size. Lead times to resolve Jira tickets were collected from Jira and averaged monthly.

Results: The study found little to no correlation between technical debt and lead time to resolve Jira tickets in five components, with technical debt explaining a variation in lead time ranging from 0% to 41%. However, it is less than 30% in most of the components.

Conclusion: Technical debt alone does not fully explain the variation in lead time. There should be some other confounding variables (e.g., size and complexity of the changes, number of teams involved, priorities, component ownership) affecting lead time or a residual effect, i.e., interest, that might manifest later. Further investigation into those confounding variables is essential. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2025. p. 693-703
Keywords [en]
Case Study, Industrial Study, Lead Time, Technical Debt, Computer software maintenance, Software design, Software quality, Case-studies, Development activity, Empirical studies, Industrial case study, Leadtime, Maintenance activity, Software company, Technical debts, Trade off, Industrial research
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-28084DOI: 10.1109/SANER64311.2025.00071ISI: 001506888600063Scopus ID: 2-s2.0-105007291171ISBN: 9798331535100 (print)OAI: oai:DiVA.org:bth-28084DiVA, id: diva2:1968574
Conference
32nd IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2025, Monteral, March, 4-7, 2025
Part of project
SERT- Software Engineering ReThought, Knowledge Foundation
Funder
Knowledge Foundation, 20180010Available from: 2025-06-13 Created: 2025-06-13 Last updated: 2025-10-21Bibliographically approved

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CiteExportLink to record
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