Lightweight Metrics for Enterprise Architecture Analysis

Singh, Prince Mayurank; Sinderen, Marten van

doi:10.1007/978-3-319-26762-3_11

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…Österlind et al [29] extend selected ArchiMate concepts with variables that are computed for structural analysis of the EA. Alike, Singh et al [38] develop seven metrics to measure criticality and impact of any element in an EA model. Holschke et al [18] perform failure impact analysis with Bayesian Belief Networks and Buschle et al [7] adapt ArchiMate by fault trees to analyze the availability of EA components.…”

Section: Graph-based Analysis Of Ea Modelsmentioning

confidence: 99%

Using Knowledge Graphs to Detect Enterprise Architecture Smells

Smajevic

Hacks

Bork

2021

Lecture Notes in Business Information Processing

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Hitherto, the concept of Enterprise Architecture (EA) Smells has been proposed to assess quality flaws in EAs and their models. Together with this new concept, a catalog of different EA Smells has been published and a first prototype was developed. However, this prototype is limited to ArchiMate and is not able to assess models adhering to other EA modeling languages. Moreover, the prototype is not integrateable with other EA tools. Therefore, we propose to enhance the extensible Graph-based Enterprise Architecture Analysis (eGEAA) platform that relies on Knowledge Graphs with EA Smell detection capabilities. To align these two approaches, we show in this paper, how ArchiMate models can be transformed into Knowledge Graphs and provide a set of queries on the Knowledge Graph representation that are able to detect EA Smells. This enables enterprise architects to assess EA Smells on all types of EA models as long as there is a Knowledge Graph representation of the model. Finally, we evaluate the Knowledge Graph based EA Smell detection by analyzing a set of 347 EA models.

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Section: Graph-based Analysis Of Ea Modelsmentioning

confidence: 99%

Using Knowledge Graphs to Detect Enterprise Architecture Smells

Smajevic

Hacks

Bork

2021

Lecture Notes in Business Information Processing

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Monitoring ArchiMate Models for DataBio Project

Chaabouni

Bagnato

García-Domínguez

2019

Product-Focused Software Process Improvement

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Towards a Classification Framework for Approaches to Enterprise Architecture Analysis

Lantow

Jugel

Wißotzki

et al. 2016

Lecture Notes in Business Information Processing

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Part 3: Short PapersInternational audienceAnalysis is an important part of the Enterprise Architecture Management Process. Prior to decisions regarding transformation of the Enterprise Architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current Enterprise Architecture Management tools implement analysis functionalities. However, few work has been done structuring and classifying Enterprise Architecture Analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for Enterprise Architecture Analysis classification. For evaluation, a collection of Enterprise Architecture Analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for Enterprise Architecture Analysis classification has been derived and suggestions for further development are drawn

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Lightweight Metrics for Enterprise Architecture Analysis

Cited by 6 publications

References 10 publications

Using Knowledge Graphs to Detect Enterprise Architecture Smells

Using Knowledge Graphs to Detect Enterprise Architecture Smells

Monitoring ArchiMate Models for DataBio Project

Towards a Classification Framework for Approaches to Enterprise Architecture Analysis

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