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Identifying and quantifying architectural debt

Authors:

Qiong FengAuthors Info & Claims

ICSE '16: Proceedings of the 38th International Conference on Software Engineering

Pages 488 - 498

https://doi.org/10.1145/2884781.2884822

Published: 14 May 2016 Publication History

Abstract

Our prior work showed that the majority of error-prone source files in a software system are architecturally connected. Flawed architectural relations propagate defects among these files and accumulate high maintenance costs over time, just like debts accumulate interest. We model groups of architecturally connected files that accumulate high maintenance costs as architectural debts. To quantify such debts, we formally define architectural debt, and show how to automatically identify debts, quantify their maintenance costs, and model these costs over time. We describe a novel history coupling probability matrix for this purpose, and identify architecture debts using 4 patterns of architectural flaws shown to correlate with reduced software quality. We evaluate our approach on 7 large-scale open source projects, and show that a significant portion of total project maintenance effort is consumed by paying interest on architectural debts. The top 5 architectural debts, covering a small portion (8% to 25%) of each project's error-prone files, capture a significant portion (20% to 61%) of each project's maintenance effort. Finally, we show that our approach reveals how architectural issues evolve into debts over time.

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Cited By

Kalhor SKeyvanpour MSalajegheh A(2024)A systematic review of refactoring opportunities by software antipattern detectionAutomated Software Engineering10.1007/s10515-024-00443-y31:2Online publication date: 15-May-2024
https://doi.org/10.1007/s10515-024-00443-y
Noguchi R(2024)The Nature of Technical Debt in the Development of Descriptive Models for MBSEINCOSE International Symposium10.1002/iis2.1316034:1(516-526)Online publication date: 7-Sep-2024
https://doi.org/10.1002/iis2.13160
Sousa ARocha LBritto R(2023)Architectural Technical Debt - A Systematic Mapping StudyProceedings of the XXXVII Brazilian Symposium on Software Engineering10.1145/3613372.3613399(196-205)Online publication date: 25-Sep-2023
https://dl.acm.org/doi/10.1145/3613372.3613399
Show More Cited By

Index Terms

Identifying and quantifying architectural debt
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

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Published In

cover image ACM Conferences

ICSE '16: Proceedings of the 38th International Conference on Software Engineering

May 2016

1235 pages

ISBN:9781450339001

DOI:10.1145/2884781

General Chair:
Laura Dillon
Michigan State University
,
Program Chairs:
Willem Visser
Stellenbosch University, South Africa
,
Laurie Williams
North Carolina State University

Copyright © 2016 ACM.

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 the author(s) 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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IEEE-CS\TCSE: TC on Software Engineering
IEEE-CS\DATC: IEEE Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 May 2016

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ICSE '16

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ICSE '16: 38th International Conference on Software Engineering

May 14 - 22, 2016

Texas, Austin

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Kalhor SKeyvanpour MSalajegheh A(2024)A systematic review of refactoring opportunities by software antipattern detectionAutomated Software Engineering10.1007/s10515-024-00443-y31:2Online publication date: 15-May-2024
https://doi.org/10.1007/s10515-024-00443-y
Noguchi R(2024)The Nature of Technical Debt in the Development of Descriptive Models for MBSEINCOSE International Symposium10.1002/iis2.1316034:1(516-526)Online publication date: 7-Sep-2024
https://doi.org/10.1002/iis2.13160
Sousa ARocha LBritto R(2023)Architectural Technical Debt - A Systematic Mapping StudyProceedings of the XXXVII Brazilian Symposium on Software Engineering10.1145/3613372.3613399(196-205)Online publication date: 25-Sep-2023
https://dl.acm.org/doi/10.1145/3613372.3613399
Karanikolas CDimitroulakos GMasselos K(2023)Simulating Software Evolution to Evaluate the Reliability of Early Decision-making among Design Alternatives toward MaintainabilityACM Transactions on Software Engineering and Methodology10.1145/356993132:3(1-38)Online publication date: 26-Apr-2023
https://dl.acm.org/doi/10.1145/3569931
Sas DAvgeriou P(2023)An architectural technical debt index based on machine learning and architectural smellsIEEE Transactions on Software Engineering10.1109/TSE.2023.3286179(1-27)Online publication date: 2023
https://doi.org/10.1109/TSE.2023.3286179
Jin WZhong DCai YKazman RLiu T(2023)Evaluating the Impact of Possible Dependencies on Architecture-Level MaintainabilityIEEE Transactions on Software Engineering10.1109/TSE.2022.317128849:3(1064-1085)Online publication date: 1-Mar-2023
https://doi.org/10.1109/TSE.2022.3171288
Tamburri DKazman RFahimi H(2023)On the Relationship Between Organizational Structure Patterns and Architecture in Agile TeamsIEEE Transactions on Software Engineering10.1109/TSE.2022.315041549:1(325-347)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TSE.2022.3150415
Jin WDai YZheng JQu YFan MHuang ZHuang DLiu TGrundy JPollock LPenta M(2023)Dependency Facade: The Coupling and Conflicts between Android Framework and Its CustomizationProceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00144(1674-1686)Online publication date: 14-May-2023
https://dl.acm.org/doi/10.1109/ICSE48619.2023.00144
Fang HCai YKazman RLefever J(2023)Identifying Anti-Patterns in Distributed Systems With Heterogeneous Dependencies2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C)10.1109/ICSA-C57050.2023.00035(116-120)Online publication date: Mar-2023
https://doi.org/10.1109/ICSA-C57050.2023.00035
Cai YKazman R(2023)Software design analysis and technical debt management based on design rule theoryInformation and Software Technology10.1016/j.infsof.2023.107322164(107322)Online publication date: Dec-2023
https://doi.org/10.1016/j.infsof.2023.107322
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