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A threshold based approach to technical debt

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Robert J. EisenbergAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 37, Issue 2

Pages 1 - 6

https://doi.org/10.1145/2108144.2108151

Published: 03 April 2012 Publication History

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Abstract

Nearly two decades ago, Ward Cunningham introduced us to the term "technical debt" as a means of describing the long term costs associated with a suboptimal software design and implementation. For most programs, especially those with a large legacy code baseline, achieving zero absolute debt is an unnecessary and unrealistic goal. It is important to recall that a primary reason for managing and eliminating debt is to drive down maintenance costs and to reduce defects. A sufficiently low, manageable level of debt can minimize the long-term impact, i.e., "low debt interest payments". In this article, we define an approach for establishing program specific thresholds to define manageable levels of technical debt.

References

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Cunningham, W. 1992. The WyCash Portfolio Management System. OOPSLA '92 Experience Report.

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Gat, I. 2010. Revolution in Software: Using Technical Debt Techniques to Govern the Software Development Process. Executive Report. Cutter Consortium.

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Sonar, 2011. http://www.sonarsource.org/

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CWE/SANS Top 25 Most Dangerous Software Errors, The MITRE Corporation, 2011. http://cwe.mitre.org/top25/

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Perera JTempero ETu YBlincoe K(2024)A Systematic Mapping Study Exploring Quantification Approaches to Code, Design, and Architecture Technical DebtACM Transactions on Software Engineering and Methodology10.1145/367539333:7(1-44)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3675393
Fungprasertkul SBahsoon RKazman R(2024)Technical Debt Monitoring Decision Making with Skin in the GameACM Transactions on Software Engineering and Methodology10.1145/366480533:7(1-27)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3664805
Tsoukalas DMittas NArvanitou EAmpatzoglou AChatzigeorgiou AKehagias D(2024)Local and Global Explainability for Technical Debt IdentificationIEEE Transactions on Software Engineering10.1109/TSE.2024.342242750:8(2110-2123)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3422427
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Index Terms

A threshold based approach to technical debt
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics

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cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 37, Issue 2

March 2012

92 pages

ISSN:0163-5948

DOI:10.1145/2108144

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 03 April 2012

Published in SIGSOFT Volume 37, Issue 2

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Perera JTempero ETu YBlincoe K(2024)A Systematic Mapping Study Exploring Quantification Approaches to Code, Design, and Architecture Technical DebtACM Transactions on Software Engineering and Methodology10.1145/367539333:7(1-44)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3675393
Fungprasertkul SBahsoon RKazman R(2024)Technical Debt Monitoring Decision Making with Skin in the GameACM Transactions on Software Engineering and Methodology10.1145/366480533:7(1-27)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3664805
Tsoukalas DMittas NArvanitou EAmpatzoglou AChatzigeorgiou AKehagias D(2024)Local and Global Explainability for Technical Debt IdentificationIEEE Transactions on Software Engineering10.1109/TSE.2024.342242750:8(2110-2123)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3422427
Nikolaidis NMittas NAmpatzoglou AFeitosa DChatzigeorgiou A(2023)A metrics-based approach for selecting among various refactoring candidatesEmpirical Software Engineering10.1007/s10664-023-10412-w29:1Online publication date: 16-Dec-2023
https://dl.acm.org/doi/10.1007/s10664-023-10412-w
Ampatzoglou AChatzigeorgiou AArvanitou EBibi S(2022) SDK4ED : A platform for technical debt management Software: Practice and Experience10.1002/spe.309352:8(1879-1902)Online publication date: 4-May-2022
https://doi.org/10.1002/spe.3093
Nikolaidis NZisis DAmpatzoglou AChatzigeorgiou ASoudris D(2021)Experience With Managing Technical Debt in Scientific Software Development Using the EXA2PRO FrameworkIEEE Access10.1109/ACCESS.2021.30792719(72524-72534)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3079271
Rantala LRothermel GBae D(2020)Towards better technical debt detection with NLP and machine learning methodsProceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings10.1145/3377812.3381404(242-245)Online publication date: 27-Jun-2020
https://dl.acm.org/doi/10.1145/3377812.3381404
Lunde BColomo-Palacios R(2020)Continuous practices and technical debt: a systematic literature review2020 20th International Conference on Computational Science and Its Applications (ICCSA)10.1109/ICCSA50381.2020.00018(40-44)Online publication date: Jul-2020
https://doi.org/10.1109/ICCSA50381.2020.00018
Ampatzoglou AMittas NTsintzira AAmpatzoglou AArvanitou EChatzigeorgiou AAvgeriou PAngelis L(2020)Exploring the Relation between Technical Debt Principal and Interest: An Empirical ApproachInformation and Software Technology10.1016/j.infsof.2020.106391128(106391)Online publication date: Dec-2020
https://doi.org/10.1016/j.infsof.2020.106391
Kula ERastogi AHuijgens HDeursen AGousios GDumas MPfahl DApel SRusso A(2019)Releasing fast and slow: an exploratory case study at INGProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338978(785-795)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3338906.3338978
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A portfolio approach to technical debt management

Technical Debt in Agile Development: Report on the Ninth Workshop on Managing Technical Debt (MTD 2017)

Integrating technical debt management and software quality management processes: a framework and field tests

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