Background
Enterprise Architecture Debt, EAD, has been defined as “the counterpart to Technical Debt” in the domain of Enterprise Architecture. Technical debt, TD, is a metaphor used in software development to describe various parts of the development lifecycle that causes higher costs and lower quality in the long run. As Seaman et al. describe it, technical debts can be seen as a type of debt that may speed up software development in the short run, but such benefit is achieved at the cost of extra work in the future.
Hacks et al. proposed a new metaphor for EAD to provide a more holistic view of TD, that is: “Enterprise Architecture Debt is a metric that depicts the deviation of the currently present state of an enterprise from a hypothetical ideal state.”
Furthermore, Salentin and Hacks suggested a catalog of measurements for EA Smells. Code smells are a component of TD. In short, code smells are parts of the source code that can seemingly be good but can indicate a deeper problem when implemented and impacting design quality. EA Smells is the counterpart of code smells in a holistic view.
Software architectural smells are also a component of TD and are indicators for bad practices or anti-patterns in a software system. In practice, software architecture is changed throughout its lifecycle. This may mean that new architectural design being added and existing one being modified. As the system grows, so will its TD. As Hacks et al. have suggested a catalog of measurements for EA Smells, I would in this research look for software architectural smells in the EAD domain.
Research Question
What Software Architectural Smells can be adapted to the EAD domain?
Contact Persons
Further Information
EA Smells catalog: https://ba-ea-smells.pages.rwth-aachen.de/ea-smells/
EA Smells prototype: https://git.rwth-aachen.de/ba-ea-smells/program
Related Work
Lehmann, Barry-Detlef; Alexander, Peter; Lichter, Horst; Hacks, Simon
Towards the Identification of Process Anti-Patterns in Enterprise Architecture Models Proceedings Article
In: 8th International Workshop on Quantitative Approaches to Software Quality in conjunction with the 27th Asia-Pacific Software Engineering Conference (APSEC 2020), pp. 47-54, CEUR-WS, 2020.
@inproceedings{Lehmann2020,
title = {Towards the Identification of Process Anti-Patterns in Enterprise Architecture Models},
author = {Barry-Detlef Lehmann and Peter Alexander and Horst Lichter and Simon Hacks},
url = {http://ceur-ws.org/Vol-2767/06-QuASoQ-2020.pdf},
year = {2020},
date = {2020-12-11},
booktitle = {8th International Workshop on Quantitative Approaches to Software Quality in conjunction with the 27th Asia-Pacific Software Engineering Conference (APSEC 2020)},
volume = {2767},
pages = {47-54},
publisher = {CEUR-WS},
abstract = {IT processes constitute the backbone of an integrated enterprise architecture (EA). The model thereof sustains the development and management of the EA. Nevertheless, the quality of such models tends to degrade over time due to, e.g. improper modeling practices or ineffective evaluation. In this regard, the knowledge of relevant modeling anti-patterns can help identify, mitigate, and prevent the occurrence of sub-optimal or adverse constructs in the model. In the field of business process modeling (BPM), a plethora of BPM anti-patterns has been defined and compiled in various taxonomies. However, these BPM anti-patterns mostly focus on technical issues, which thus are applicable for evaluating workflows but not EA-level processes. We strongly argue that the concept of process anti-pattern in EA domain can facilitate EA analyses on process-related issues. To address this gap, this paper presents a catalogue of 18 EA process modeling anti-patterns, which we derived from the existing BPM anti-patterns. Our result should serve as food for thought and motivation for future research in this context.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
IT processes constitute the backbone of an integrated enterprise architecture (EA). The model thereof sustains the development and management of the EA. Nevertheless, the quality of such models tends to degrade over time due to, e.g. improper modeling practices or ineffective evaluation. In this regard, the knowledge of relevant modeling anti-patterns can help identify, mitigate, and prevent the occurrence of sub-optimal or adverse constructs in the model. In the field of business process modeling (BPM), a plethora of BPM anti-patterns has been defined and compiled in various taxonomies. However, these BPM anti-patterns mostly focus on technical issues, which thus are applicable for evaluating workflows but not EA-level processes. We strongly argue that the concept of process anti-pattern in EA domain can facilitate EA analyses on process-related issues. To address this gap, this paper presents a catalogue of 18 EA process modeling anti-patterns, which we derived from the existing BPM anti-patterns. Our result should serve as food for thought and motivation for future research in this context.
Salentin, Johannes; Hacks, Simon
Towards a Catalog of Enterprise Architecture Smells Book Section
In: Gronau, Norbert; Heine, Moreen; Poustcchi, K; Krasnova, H (Ed.): WI2020 Community Tracks, pp. 276–290, GITO Verlag, 2020, ISBN: 9783955453367.
@incollection{Salentin.2020,
title = {Towards a Catalog of Enterprise Architecture Smells},
author = {Johannes Salentin and Simon Hacks},
editor = {Norbert Gronau and Moreen Heine and K Poustcchi and H Krasnova},
url = {https://dx.doi.org/10.30844/wi_2020_y1-salentin},
doi = {10.30844/wi_2020_y1-salentin},
isbn = {9783955453367},
year = {2020},
date = {2020-03-23},
booktitle = {WI2020 Community Tracks},
pages = {276--290},
publisher = {GITO Verlag},
abstract = {Code Smells are well known in the domain of Technical Debt (TD). They hint at common bad habits that impair the quality of the software system. By detecting those smells it is possible to suggest a better solution or, at least, make the developers aware of possible drawbacks. However, in terms of Enterprise Architecture (EA), which is a more holistic view of an enterprise including TD, there does not exist such a concept of EA Smells.
Such EA Smells can be a component of EA Debt, working like a metric to rate the quality of data and estimate parts of the EA Debt in an EA Repository. The main goal of this work is to start the development of a catalog to facilitate future design and development of EAs. This catalog should be expanded and serve as food for thought to create a corresponding tool for the detection of smells.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Code Smells are well known in the domain of Technical Debt (TD). They hint at common bad habits that impair the quality of the software system. By detecting those smells it is possible to suggest a better solution or, at least, make the developers aware of possible drawbacks. However, in terms of Enterprise Architecture (EA), which is a more holistic view of an enterprise including TD, there does not exist such a concept of EA Smells.
Such EA Smells can be a component of EA Debt, working like a metric to rate the quality of data and estimate parts of the EA Debt in an EA Repository. The main goal of this work is to start the development of a catalog to facilitate future design and development of EAs. This catalog should be expanded and serve as food for thought to create a corresponding tool for the detection of smells.
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