research-article

Investigating the impact of design debt on software quality

Authors:

Nico Zazworka,

Michele A. Shaw,

Forrest Shull,

Carolyn SeamanAuthors Info & Claims

MTD '11: Proceedings of the 2nd Workshop on Managing Technical Debt

Pages 17 - 23

https://doi.org/10.1145/1985362.1985366

Published: 23 May 2011 Publication History

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Abstract

Technical debt is a metaphor describing situations where developers accept sacrifices in one dimension of development (e.g. software quality) in order to optimize another dimension (e.g. implementing necessary features before a deadline). Approaches, such as code smell detection, have been developed to identify particular kinds of debt, e.g. design debt. What has not yet been understood is the impact design debt has on the quality of a software product. Answering this question is important for understanding how growing debt affects a software product and how it slows down development, e.g. though introducing rework such as fixing bugs. In this case study we investigate how design debt, in the form of god classes, affects the maintainability and correctness of software products by studying two sample applications of a small-size software development company. The results show that god classes are changed more often and contain more defects than non-god classes. This result complements findings of earlier research and suggests that technical debt has a negative impact on software quality, and should therefore be identified and managed closely in the development process.

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Tandon SKumar VSingh V(2024)Study of Code Smells: A Review and Research AgendaInternational Journal of Mathematical, Engineering and Management Sciences10.33889/IJMEMS.2024.9.3.0259:3(472-498)Online publication date: 1-Jun-2024
https://doi.org/10.33889/IJMEMS.2024.9.3.025
Riquet NDevroey XVanderose BCodabux ZGalster MSpinola R(2024)Debt Stories: Capturing Social and Technical Debt in the IndustryProceedings of the 7th ACM/IEEE International Conference on Technical Debt10.1145/3644384.3644473(40-44)Online publication date: 14-Apr-2024
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Nunes HSantana AFigueiredo ECosta HBaysal OLinares-Vasquez MMoran KSteinmacher I(2024)Tuning Code Smell Prediction Models: A Replication StudyProceedings of the 32nd IEEE/ACM International Conference on Program Comprehension10.1145/3643916.3644436(316-327)Online publication date: 15-Apr-2024
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Index Terms

Investigating the impact of design debt on software quality
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics

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Information & Contributors

Information

Published In

MTD '11: Proceedings of the 2nd Workshop on Managing Technical Debt

May 2011

54 pages

ISBN:9781450305860

DOI:10.1145/1985362

Program Chairs:
Ipek Ozkaya
Software Engineering Institute, USA
,
Philippe Kruchten
University of British Columbia, Canada
,
Rod Nord
Software Engineering Institute, USA
,
Nanette Brown
Software Engineering Institute, USA

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: 23 May 2011

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ICSE11: International Conference on Software Engineering

May 23, 2011

HI, Waikiki, Honolulu, USA

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Cited By

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Tandon SKumar VSingh V(2024)Study of Code Smells: A Review and Research AgendaInternational Journal of Mathematical, Engineering and Management Sciences10.33889/IJMEMS.2024.9.3.0259:3(472-498)Online publication date: 1-Jun-2024
https://doi.org/10.33889/IJMEMS.2024.9.3.025
Riquet NDevroey XVanderose BCodabux ZGalster MSpinola R(2024)Debt Stories: Capturing Social and Technical Debt in the IndustryProceedings of the 7th ACM/IEEE International Conference on Technical Debt10.1145/3644384.3644473(40-44)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3644384.3644473
Nunes HSantana AFigueiredo ECosta HBaysal OLinares-Vasquez MMoran KSteinmacher I(2024)Tuning Code Smell Prediction Models: A Replication StudyProceedings of the 32nd IEEE/ACM International Conference on Program Comprehension10.1145/3643916.3644436(316-327)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643916.3644436
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Zarrad ABahsoon RManimaran P(2024)Optimizing regression testing with AHP-TOPSIS metric system for effective technical debt evaluationAutomated Software Engineering10.1007/s10515-024-00458-531:2Online publication date: 8-Jul-2024
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Alharbi MAlshayeb M(2024)An empirical investigation of the relationship between pattern grime and code smellsJournal of Software: Evolution and Process10.1002/smr.266636:9Online publication date: 16-Sep-2024
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