research-article

Mapping architectural decay instances to dependency models

Authors:

Nenad MedvidovicAuthors Info & Claims

MTD '13: Proceedings of the 4th International Workshop on Managing Technical Debt

Pages 39 - 46

Published: 20 May 2013 Publication History

Abstract

The architectures of software systems tend to drift or erode as they are maintained and evolved. These systems often develop architectural decay instances, which are instances of design decisions that negatively impact a system's lifecycle properties and are the analog to code-level decay instances that are potential targets for refactoring. While code-level decay instances are based on source-level constructs, architectural decay instances are based on higher levels of abstractions, such as components and connectors, and related concepts, such as concerns. Unlike code-level decay instances, architectural decay usually has more significant consequences. Not being able to detect or address architectural decay in time incurs architecture debt that may result in a higher penalty in terms of quality and maintainability (interest) over time. To facilitate architecture debt detection, in this paper, we demonstrate the possibility of transforming architectural models and concerns into an extended augmented constraint network (EACN), which can uniformly model the constraints among design decisions and environmental conditions. From an ACN, a pairwise-dependency relation (PWDR) can be derived, which, in turn, can be used to automatically and uniformly detect architectural decay instances.

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Cited By

Machado MChoren RHaddad HWainwright RChbeir R(2018)Improving the detection of evolutionary couplingProceedings of the 33rd Annual ACM Symposium on Applied Computing10.1145/3167132.3167283(1410-1416)Online publication date: 9-Apr-2018
https://dl.acm.org/doi/10.1145/3167132.3167283
Ernst NBellomo SOzkaya INord RGorton IDi Nitto EHarman MHeymans P(2015)Measure it? Manage it? Ignore it? software practitioners and technical debtProceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering10.1145/2786805.2786848(50-60)Online publication date: 30-Aug-2015
https://dl.acm.org/doi/10.1145/2786805.2786848

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Published In

cover image ACM Conferences

MTD '13: Proceedings of the 4th International Workshop on Managing Technical Debt

May 2013

71 pages

ISBN:9781467364430

Conference Chairs:
Philippe Kruchten
University of British Columbia, Canada
,
Robert Nord
Software Engineering Institute
,
Ipek Ozkaya
Software Engineering Institute

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IEEE Press

Publication History

Published: 20 May 2013

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ICSE '13

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SIGSOFT

ICSE '13: 35th International Conference on Software Engineering

May 20, 2013

California, San Francisco

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Overall Acceptance Rate 40 of 92 submissions, 43%

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Cited By

Machado MChoren RHaddad HWainwright RChbeir R(2018)Improving the detection of evolutionary couplingProceedings of the 33rd Annual ACM Symposium on Applied Computing10.1145/3167132.3167283(1410-1416)Online publication date: 9-Apr-2018
https://dl.acm.org/doi/10.1145/3167132.3167283
Ernst NBellomo SOzkaya INord RGorton IDi Nitto EHarman MHeymans P(2015)Measure it? Manage it? Ignore it? software practitioners and technical debtProceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering10.1145/2786805.2786848(50-60)Online publication date: 30-Aug-2015
https://dl.acm.org/doi/10.1145/2786805.2786848

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