University of Southern Denmark
The University of Southern Denmark (Danish: Syddansk Universitet) is with around 30,000 students and 4,000 employees Denmarks third largest university. The university is allocated on six campi with its main campus in Odense.
Within the Maersk Mc-Kinney Moller Institute of the Technical Faculty, Simon Hacks is researching on the conceptualization of EA Debts and EA Smells as well as developing tool support to automatize the analysis.
Recent Publications
Bråtfors, Robin; Hacks, Simon; Bork, Dominik
Historization of Enterprise Architecture Models Via Enterprise Architecture Knowledge Graphs Inproceedings Forthcoming
In: Barn, Balbir S.; Sandkuhl, Kurt (Ed.): The Practice of Enterprise Modeling, Springer International Publishing, Cham, Forthcoming.
@inproceedings{nokey,
title = {Historization of Enterprise Architecture Models Via Enterprise Architecture Knowledge Graphs},
author = {Robin Bråtfors and Simon Hacks and Dominik Bork},
editor = {Balbir S. Barn and Kurt Sandkuhl},
year = {2022},
date = {2022-11-30},
booktitle = {The Practice of Enterprise Modeling},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {nterprise Architecture (EA) is the discipline that aims to provide a holistic view of the enterprise by explicating business and IT alignment from the perspectives of high-level corporate strategy down to daily operations and network infrastructures. EAs are consequently complex as they compose and integrate many aspects on different architecture layers. A recent proposal to cope with this complexity and to make EAs amenable to automated and intuitive visual analysis is the transformation of EA models into EA Knowledge Graphs. A remaining limitation of these approaches is that they perceive the EA to be static, i.e., they represent and analyze EAs at a single point in time. In the paper at hand, we introduce a historization concept, a prototypical implementation, and a performance analysis for how EAs can be represented and processed to enable the analysis of their evolution.},
keywords = {},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
nterprise Architecture (EA) is the discipline that aims to provide a holistic view of the enterprise by explicating business and IT alignment from the perspectives of high-level corporate strategy down to daily operations and network infrastructures. EAs are consequently complex as they compose and integrate many aspects on different architecture layers. A recent proposal to cope with this complexity and to make EAs amenable to automated and intuitive visual analysis is the transformation of EA models into EA Knowledge Graphs. A remaining limitation of these approaches is that they perceive the EA to be static, i.e., they represent and analyze EAs at a single point in time. In the paper at hand, we introduce a historization concept, a prototypical implementation, and a performance analysis for how EAs can be represented and processed to enable the analysis of their evolution.
Hacks, Simon; Smajevic, Muhamed; Bork, Dominik
Using Knowledge Graphs to Detect Enterprise Architecture Smells (Extended Abstract) Inproceedings Forthcoming
In: Leopold, Henrik; Proper, Henderik A. (Ed.): EMISA 2022, Forthcoming.
@inproceedings{nokey,
title = {Using Knowledge Graphs to Detect Enterprise Architecture Smells (Extended Abstract)},
author = {Simon Hacks and Muhamed Smajevic and Dominik Bork},
editor = {Henrik Leopold and Henderik A. Proper},
year = {2022},
date = {2022-06-05},
booktitle = {EMISA 2022},
keywords = {},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
Jung, Jürgen; Hacks, Simon; Gooijer, Thijmen; Kinnunen, Matti; Rehring, Kevin
In: 2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW), pp. 271-278, 2021.
@inproceedings{9626297,
title = {Revealing Common Enterprise Architecture Debts: Conceptualization and Critical Reflection on a Workshop Format Industry Experience Report},
author = {Jürgen Jung and Simon Hacks and Thijmen Gooijer and Matti Kinnunen and Kevin Rehring},
doi = {10.1109/EDOCW52865.2021.00058},
year = {2021},
date = {2021-12-01},
urldate = {2021-01-01},
booktitle = {2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)},
pages = {271-278},
abstract = {The Enterprise Architecture (EA) discipline evolved during the past two decades and is now established in a large number of companies. Architectures in these companies changed over time and are now the result of a long creation and maintenance process. Such architectures still contain processes and services provided by legacy IT systems (e.g., systems, applications) that were reasonable during the time they were created but might now hamper the introduction of better solutions. In order to support handling those legacies, research on the notion of EA debts has been started. The concept of EA debts widens the scope of technical debts to cover also organizational aspects offering a mean for managing EA in dynamic environments. The research encompasses the development of methods for managing debts together with a repository of typical EA debts. Identifying EA debts for the repository is challenging as required knowledge is usually not documented. Therefore, a structured approach is needed to externalize this knowledge. The paper presents a workshop format that is used to identify EA debts in organizations. Corresponding workshops are performed in two distinct companies to support them in understanding certain issues they face. First results from those workshops are presented in the second part of the paper.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Enterprise Architecture (EA) discipline evolved during the past two decades and is now established in a large number of companies. Architectures in these companies changed over time and are now the result of a long creation and maintenance process. Such architectures still contain processes and services provided by legacy IT systems (e.g., systems, applications) that were reasonable during the time they were created but might now hamper the introduction of better solutions. In order to support handling those legacies, research on the notion of EA debts has been started. The concept of EA debts widens the scope of technical debts to cover also organizational aspects offering a mean for managing EA in dynamic environments. The research encompasses the development of methods for managing debts together with a repository of typical EA debts. Identifying EA debts for the repository is challenging as required knowledge is usually not documented. Therefore, a structured approach is needed to externalize this knowledge. The paper presents a workshop format that is used to identify EA debts in organizations. Corresponding workshops are performed in two distinct companies to support them in understanding certain issues they face. First results from those workshops are presented in the second part of the paper.
Smajevic, Muhamed; Hacks, Simon; Bork, Dominik
Using Knowledge Graphs to Detect Enterprise Architecture Smells Inproceedings
In: Serral, Estefanía; Stirna, Janis; Ralyté, Jolita; Grabis, Jānis (Ed.): The Practice of Enterprise Modeling, pp. 48–63, Springer International Publishing, Cham, 2021, ISBN: 978-3-030-91279-6.
@inproceedings{10.1007/978-3-030-91279-6_4,
title = {Using Knowledge Graphs to Detect Enterprise Architecture Smells},
author = {Muhamed Smajevic and Simon Hacks and Dominik Bork},
editor = {Estefanía Serral and Janis Stirna and Jolita Ralyté and Jānis Grabis},
doi = {10.1007/978-3-030-91279-6_4},
isbn = {978-3-030-91279-6},
year = {2021},
date = {2021-11-15},
urldate = {2021-11-15},
booktitle = {The Practice of Enterprise Modeling},
pages = {48--63},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {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 integrate-able 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.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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 integrate-able 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.
Tieu, Benny; Hacks, Simon
Determining Enterprise Architecture Smells from Software Architecture Smells Inproceedings
In: 2021 IEEE 23rd Conference on Business Informatics (CBI), pp. 134-142, IEEE, 2021.
@inproceedings{9610644,
title = {Determining Enterprise Architecture Smells from Software Architecture Smells},
author = {Benny Tieu and Simon Hacks},
doi = {10.1109/CBI52690.2021.10064},
year = {2021},
date = {2021-11-01},
urldate = {2021-11-01},
booktitle = {2021 IEEE 23rd Conference on Business Informatics (CBI)},
volume = {02},
pages = {134-142},
publisher = {IEEE},
abstract = {Software Architectural Smells (SA smells) are design problems in the internal structure and behavior of an SA. These can be seen as a specific category under the umbrella concept of Technical Debt (TD). TD is a central concept in software development projects and having the means to detect and measure the smells is important to understand impairments they may cause. However, TD is only limited to the technical aspects and does not describe smells found on an enterprise level. Enterprise Architecture Debt (EAD) expands the concepts of TD beyond the technical aspects such that it covers the debts that can be found in all layers of an Enterprise Architecture (EA). EA smells give a measurement for EAD, by providing means for detecting the smell, hence enabling a method to quantify the level of debt. The goal of this paper is to find EA smells derived from existing SA smells. This has resulted in three new EA smells that could be used as measurements for the quality of an EA. They can also be used in the future as a basis for automatic EA smell detection.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Software Architectural Smells (SA smells) are design problems in the internal structure and behavior of an SA. These can be seen as a specific category under the umbrella concept of Technical Debt (TD). TD is a central concept in software development projects and having the means to detect and measure the smells is important to understand impairments they may cause. However, TD is only limited to the technical aspects and does not describe smells found on an enterprise level. Enterprise Architecture Debt (EAD) expands the concepts of TD beyond the technical aspects such that it covers the debts that can be found in all layers of an Enterprise Architecture (EA). EA smells give a measurement for EAD, by providing means for detecting the smell, hence enabling a method to quantify the level of debt. The goal of this paper is to find EA smells derived from existing SA smells. This has resulted in three new EA smells that could be used as measurements for the quality of an EA. They can also be used in the future as a basis for automatic EA smell detection.
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