Developing Measurements for Data-Flow Anti-Patterns in the Domain of Enterprise Architecture Debts

Background

Technical debt is a metaphor that describes the tradeoff often made between short-term solutions in a software system and the long-term development of it. These kinds of trade-offs can create issues that makes it harder to modify and develop a software system further. This aspect becomes increasingly important as businesses must stay competitive in a changing environment, while aligning IT and business is something that must be addressed continuously. While doing so, businesses that build up on technical debt will meet negative consequences such as increased software development cost, low product quality, decreased maintainability, and slower development.

Since technical debt so far only has been limited to technical aspects, researchers at the Division of Network and Systems Engineering at KTH, have recently proposed a definition to the metaphor “Enterprise Architecture debt (EAD)” to give a more holistic view when addressing technical debt from an enterprise perspective.

Researchers have now taken the firsts steps towards measuring EADs and this degree project will be carried out to elaborate further on such measurements to create a set of measurements for EAD. These could be derived from mapping existing measurements for bad behavior in different domains of Enterprise Architecture (business, data, application, and technical layer).

An example of such bad behavior measurements are code smells and anti-patterns, which aim to describe bad practices such that they can get recognized and dealt with. This project aims to focus on anti-patterns that have been defined to discover data-flow errors. The plan is to map these definitions to suit a more holistic view of EA and further contribute to the management of EADs.

Research Question

What corresponding EA anti-patterns can be defined on the existing data-flow anti-patterns?

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 Inproceedings

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.

Abstract | Links | BibTeX

Salentin, Johannes; Hacks, Simon

Towards a Catalog of Enterprise Architecture Smells Incollection

Gronau, Norbert; Heine, Moreen; Poustcchi, K; Krasnova, H (Ed.): WI2020 Community Tracks, pp. 276–290, GITO Verlag, 2020, ISBN: 9783955453367.

Abstract | Links | BibTeX

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