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To Pay or Not to Pay Technical Debt

Author:

Frank BuschmannAuthors Info & Claims

IEEE Software, Volume 28, Issue 6

Pages 29 - 31

https://doi.org/10.1109/MS.2011.150

Published: 01 November 2011 Publication History

Abstract

Technical debt is a widely used metaphor to illustrate and discuss the consequences of design and coding decisions over time. The architect's position on technical debt, however, should be driven more by business aspects and less by technical concerns. Only then can architects assess when to incur technical debt and whether or not to retire it, when to retire it, and how.

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Ramulu HSchmitt HWermke DAcar YBalzarotti DXu W(2024)Security and privacy software creators' perspectives on unintended consequencesProceedings of the 33rd USENIX Conference on Security Symposium10.5555/3698900.3699083(3259-3276)Online publication date: 14-Aug-2024
https://dl.acm.org/doi/10.5555/3698900.3699083
Sheikhaei MTian YWang SXu B(2024)An empirical study on the effectiveness of large language models for SATD identification and classificationEmpirical Software Engineering10.1007/s10664-024-10548-329:6Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s10664-024-10548-3
Guo ZLiu SLiu JLi YChen LLu HZhou Y(2021)How Far Have We Progressed in Identifying Self-admitted Technical Debts? A Comprehensive Empirical StudyACM Transactions on Software Engineering and Methodology10.1145/344724730:4(1-56)Online publication date: 23-Jul-2021
https://dl.acm.org/doi/10.1145/3447247
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Published In

IEEE Software Volume 28, Issue 6

November 2011

99 pages

ISSN:0740-7459

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IEEE Computer Society Press

Washington, DC, United States

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Published: 01 November 2011

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Ramulu HSchmitt HWermke DAcar YBalzarotti DXu W(2024)Security and privacy software creators' perspectives on unintended consequencesProceedings of the 33rd USENIX Conference on Security Symposium10.5555/3698900.3699083(3259-3276)Online publication date: 14-Aug-2024
Sheikhaei MTian YWang SXu B(2024)An empirical study on the effectiveness of large language models for SATD identification and classificationEmpirical Software Engineering10.1007/s10664-024-10548-329:6Online publication date: 1-Oct-2024
Guo ZLiu SLiu JLi YChen LLu HZhou Y(2021)How Far Have We Progressed in Identifying Self-admitted Technical Debts? A Comprehensive Empirical StudyACM Transactions on Software Engineering and Methodology10.1145/344724730:4(1-56)Online publication date: 23-Jul-2021
Kumar SChen TBahsoon RBuyya RHoniden SNitto ECalinescu R(2020)DATESSOProceedings of the IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3387939.3391604(96-107)Online publication date: 29-Jun-2020
Rocha JZapalowski VNunes IMaldonado JFerrari FKulesza UUchôa Conte T(2017)Understanding Technical Debt at the Code Level from the Perspective of Software DevelopersProceedings of the XXXI Brazilian Symposium on Software Engineering10.1145/3131151.3131164(64-73)Online publication date: 20-Sep-2017
Fernández-Sánchez CGarbajosa JYagüe APerez J(2017)Identification and analysis of the elements required to manage technical debt by means of a systematic mapping studyJournal of Systems and Software10.1016/j.jss.2016.10.018124:C(22-38)Online publication date: 1-Feb-2017
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Mistrik ISoley RAli NGrundy JTekinerdogan B(2015)Software Quality AssuranceundefinedOnline publication date: 2-Nov-2015
Arabas SJarecka DJaruga AFijałkowski M(2014)Formula translation in Blitz++, NumPy and modern FortranScientific Programming10.1155/2014/87014622:3(201-222)Online publication date: 1-Jul-2014
Chauvel FSong HFerry NFleurey F(2014)Robustness Indicators for Cloud-Based Systems TopologiesProceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing10.1109/UCC.2014.40(307-316)Online publication date: 8-Dec-2014
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