research-article

Technical Debt: Broadening Perspectives Report on the Seventh Workshop on Managing Technical Debt (MTD 2015)

Authors:

Paris Avgeriou,

Robert L. Nord,

Philippe KruchtenAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 41, Issue 2

Pages 38 - 41

https://doi.org/10.1145/2894784.2894800

Published: 11 May 2016 Publication History

Abstract

Increasingly software engineers use the metaphor of technical debt to communicate issues related to the growing cost of change. In this article, we report on the Seventh Workshop on Managing Technical Debt (MTD 2015), held in Bremen, Germany, on October 2, 2015, collocated with the International Conference on Software Maintenance and Evolution (ICSME). The 30 workshop participants from industry and academia engaged in lively discussions, which helped clarify issues, refine questions, and promote common understanding about technical debt in software.

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Cited By

Bi FVogel-Heuser BDu FHanich NCho E(2023)Technical Debt Contagiousness Metrics for Measurement and Prioritization in Mechatronics2023 ACM/IEEE International Conference on Technical Debt (TechDebt)10.1109/TechDebt59074.2023.00012(42-51)Online publication date: May-2023
https://doi.org/10.1109/TechDebt59074.2023.00012
Bi FVogel-Heuser BSapera E(2023)Towards an Interdisciplinary Technical Debt Interaction and Visualization Tool2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)10.1109/ICPS58381.2023.10128069(1-8)Online publication date: 8-May-2023
https://doi.org/10.1109/ICPS58381.2023.10128069
Bi FVogel-Heuser BHuang ZOcker F(2023)Characteristics, causes, and consequences of technical debt in the automation domainJournal of Systems and Software10.1016/j.jss.2023.111725204:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111725
Show More Cited By

Technical Debt: Broadening Perspectives Report on the Seventh Workshop on Managing Technical Debt (MTD 2015)
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
2. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Software management

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 41, Issue 2

March 2016

75 pages

ISSN:0163-5948

DOI:10.1145/2894784

Editor:
Michael Wing

Issue’s Table of Contents

Copyright © 2016 Copyright is held by the owner/author(s).

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 May 2016

Published in SIGSOFT Volume 41, Issue 2

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Cited By

Bi FVogel-Heuser BDu FHanich NCho E(2023)Technical Debt Contagiousness Metrics for Measurement and Prioritization in Mechatronics2023 ACM/IEEE International Conference on Technical Debt (TechDebt)10.1109/TechDebt59074.2023.00012(42-51)Online publication date: May-2023
https://doi.org/10.1109/TechDebt59074.2023.00012
Bi FVogel-Heuser BSapera E(2023)Towards an Interdisciplinary Technical Debt Interaction and Visualization Tool2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)10.1109/ICPS58381.2023.10128069(1-8)Online publication date: 8-May-2023
https://doi.org/10.1109/ICPS58381.2023.10128069
Bi FVogel-Heuser BHuang ZOcker F(2023)Characteristics, causes, and consequences of technical debt in the automation domainJournal of Systems and Software10.1016/j.jss.2023.111725204:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111725
Kotti ZGalanopoulou RSpinellis D(2022)Machine Learning for Software Engineering: A Tertiary StudyACM Computing Surveys10.1145/357290555:12(1-39)Online publication date: 30-Nov-2022
https://dl.acm.org/doi/10.1145/3572905
Nielsen MMadsen C(2022)Stakeholder influence on technical debt management in the public sector: An embedded case studyGovernment Information Quarterly10.1016/j.giq.2022.10170639:3(101706)Online publication date: Jul-2022
https://doi.org/10.1016/j.giq.2022.101706
Ahmad MGustavsson T(2022)The Pandora's box of social, process, and people debts in software engineeringJournal of Software: Evolution and Process10.1002/smr.2516Online publication date: 9-Oct-2022
https://doi.org/10.1002/smr.2516
Edith Nielsen MSkaarup S(2021)IT Portfolio management as a framework for managing Technical DebtProceedings of the 14th International Conference on Theory and Practice of Electronic Governance10.1145/3494193.3494296(89-96)Online publication date: 6-Oct-2021
https://dl.acm.org/doi/10.1145/3494193.3494296
Soliman MAvgeriou PLi Y(2021)Architectural design decisions that incur technical debt — An industrial case studyInformation and Software Technology10.1016/j.infsof.2021.106669139:COnline publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1016/j.infsof.2021.106669
Vogel-Heuser BBi F(2020)Interdisciplinary effects of technical debt in companies with mechatronic products – a qualitative studyJournal of Systems and Software10.1016/j.jss.2020.110809(110809)Online publication date: Aug-2020
https://doi.org/10.1016/j.jss.2020.110809
Vogel-Heuser BNeumann E(2017)Adapting the concept of technical debt to software of automated Production Systems focusing on fault handling, mode of operation and safety aspectsIFAC-PapersOnLine10.1016/j.ifacol.2017.08.130850:1(5887-5894)Online publication date: Jul-2017
https://doi.org/10.1016/j.ifacol.2017.08.1308

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