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The magnificent seven: towards a systematic estimation of technical debt interest

Authors:

Antonio Martini,

Jan BoschAuthors Info & Claims

XP '17: Proceedings of the XP2017 Scientific Workshops

Article No.: 7, Pages 1 - 5

https://doi.org/10.1145/3120459.3120467

Published: 22 May 2017 Publication History

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Abstract

The interest of Technical Debt is difficult to assess. The negative effects (severity) of Technical Debt might depend on the context of the organization and the estimations might be subjective. There is a need for assessing Technical Debt interest in a more systematic way.

Based on the results of previous research, we have developed and used a lightweight tool, AnaConDebt, to assess the severity of the interest of 9 Technical Debt items with the stakeholders in 3 Agile teams. The systematic and semi-automatic assessment of seven factors and their growth has been compared to the stakeholders' intuitive estimations.

The results show that the outcome of the tool is very close to the estimation given by the stakeholders. The implications are that, if further data support the hypothesis, the severity of the interest can be systematically assessed by the stakeholders by estimating only seven factors in a cost-effective manner with acceptable results.

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Cited By

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Archela GMelo AGava VHong JPark J(2024)Technical Debt Management in Agile ContextProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3635946(826-833)Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1145/3605098.3635946
Aldaeej ASeaman C(2024)A rule-based decision model to support technical debt decisions: A multiple case study of web and mobile app startupsInformation and Software Technology10.1016/j.infsof.2024.107542175(107542)Online publication date: Dec-2024
https://doi.org/10.1016/j.infsof.2024.107542
Levén WBroman HBesker TTorkar R(2024)The broken windows theory applies to technical debtEmpirical Software Engineering10.1007/s10664-024-10456-629:4Online publication date: 24-May-2024
https://dl.acm.org/doi/10.1007/s10664-024-10456-6
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Index Terms

The magnificent seven: towards a systematic estimation of technical debt interest
1. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Risk management

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Published In

XP '17: Proceedings of the XP2017 Scientific Workshops

May 2017

124 pages

ISBN:9781450352642

DOI:10.1145/3120459

Conference Chair:
Roberto Tonelli
University of Cagliari Italy

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 May 2017

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Software Center

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XP '17 Workshops

XP '17 Workshops: Proceedings of the Scientific Workshops of XP2017

May 22 - 26, 2017

Cologne, Germany

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Overall Acceptance Rate 11 of 15 submissions, 73%

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Cited By

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Archela GMelo AGava VHong JPark J(2024)Technical Debt Management in Agile ContextProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3635946(826-833)Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1145/3605098.3635946
Aldaeej ASeaman C(2024)A rule-based decision model to support technical debt decisions: A multiple case study of web and mobile app startupsInformation and Software Technology10.1016/j.infsof.2024.107542175(107542)Online publication date: Dec-2024
https://doi.org/10.1016/j.infsof.2024.107542
Levén WBroman HBesker TTorkar R(2024)The broken windows theory applies to technical debtEmpirical Software Engineering10.1007/s10664-024-10456-629:4Online publication date: 24-May-2024
https://dl.acm.org/doi/10.1007/s10664-024-10456-6
Albuquerque DGuimarães ETonin GRodríguezs PPerkusich MAlmeida HPerkusich AChagas F(2023)Managing Technical Debt Using Intelligent Techniques - A Systematic Mapping StudyIEEE Transactions on Software Engineering10.1109/TSE.2022.321476449:4(2202-2220)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TSE.2022.3214764
Avgeriou POzkaya IChatzigeorgiou ACiolkowski MErnst NKoontz RPoort EShull F(2023)Technical Debt Management: The Road Ahead for Successful Software Delivery2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE)10.1109/ICSE-FoSE59343.2023.00007(15-30)Online publication date: 14-May-2023
https://doi.org/10.1109/ICSE-FoSE59343.2023.00007
Feng XPeriyasamy K(2022)A Cost Estimation Model for Scrum ProjectsJournal of Computing Sciences in Colleges10.5555/3580619.358062438:4(30-37)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.5555/3580619.3580624
Detofeno TMalucelli AReinehr S(2022)PriorTD: A Method for Prioritization Technical DebtProceedings of the XXXVI Brazilian Symposium on Software Engineering10.1145/3555228.3555238(230-240)Online publication date: 5-Oct-2022
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Xiao LCai YKazman RMo RFeng Q(2022)Detecting the Locations and Predicting the Maintenance Costs of Compound Architectural DebtsIEEE Transactions on Software Engineering10.1109/TSE.2021.310222148:9(3686-3715)Online publication date: 1-Sep-2022
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Staron M(2022)Introduction to the Metrics ThemeAccelerating Digital Transformation10.1007/978-3-031-10873-0_9(155-161)Online publication date: 20-Oct-2022
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Jongeling RCiccozzi FCicchetti ACarlson J(2022)Chapter 6 Lightweight Consistency Checking for Agile Model-Based Development in PracticeAccelerating Digital Transformation10.1007/978-3-031-10873-0_8(131-151)Online publication date: 20-Oct-2022
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