Bibtex
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@Select Types{,
Journal = "Band-2",
Title= "Towards a Catalog of Enterprise Architecture Smells",
Author= "Johannes Salentin, Simon Hacks
",
Doi= "https://doi.org/10.30844/wi_2020_y1-salentin",
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= "EA Smells, EA Quality, EA Debt, Prototype, Catalog.",
}
Johannes Salentin, Simon Hacks: Towards a Catalog of Enterprise Architecture Smells. Online: https://doi.org/10.30844/wi_2020_y1-salentin (Abgerufen 20.12.24)
Open Access
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.
EA Smells, EA Quality, EA Debt, Prototype, Catalog.
1. Tom, E., Aurum, A., Vidgen, R.: An exploration of technical debt. Journal of Systems and Software 86, 1498–1516 (2013)
2. Cunningham, W.: The WyCash portfolio management system. ACM SIGPLAN OOPS Messenger 4, 29–30 (1993)
3. Zazworka, N., Seaman, C., Shull, F.: Prioritizing Design Debt Investment Opportunities. Proceeding of the 2nd workshop on Managing technical debt – MTD ’11, 39–42 (2011)
4. Seaman, C., Guo, Y., Zazworka, N., Shull, F., Izurieta, C., Cai, Y., Vetrò Antonio: Using technical debt data in decision making: Potential decision approaches. In: 3rd International Workshop on Managing Technical Debt, MTD 2012 – Proceedings, pp. 45–48 (2012)
5. Guo, Y., Seaman, C.: A portfolio approach to technical debt management. In: Proceeding of the 2nd working on Managing technical debt – MTD ’11, p. 31 (2011)
6. Albarak, M., Bahsoon, R.: Prioritizing technical debt in database normalization using portfolio theory and data quality metrics. In: Proceedings of the 2018 International Conference on Technical Debt – TechDebt ’18, pp. 31–40 (2018)
7. Hacks, S., Höfert, H., Salentin, J., Yeong, Y.C., Lichter, H.: Towards the Definition of Enterprise Architecture Debts. In: Proceedings of the 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop, pp. 9–16 (2019)
8. Booch, G.: Enterprise Architecture and Technical Architecture. IEEE Software 27, 96 (2010)
9. Hacks, S., Lichter, H.: A Probabilistic Enterprise Architecture Model Evolution. In: 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC), pp. 51–57 (2018)
10. Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems 24, 45–77 (2007)
11. Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS quarterly 28, 75–105 (2004)
12. Fowler, M.: Refactoring: improving the design of existing code. Addison-Wesley Professional (2018)
13. Brown, N., Cai, Y., Guo, Y., Kazman, R., Kim, M., Kruchten, P., Lim, E., MacCormack, A., Nord, R., Ozkaya, I., et al.: Managing Technical Debt in Software-reliant Systems. In: Proceedings of the FSE/SDP Workshop on Future of Software Engineering Research, pp. 47–52. ACM, New York, NY, USA (2010)
14. Mäntylä, M.V., Lassenius, C.: Subjective Evaluation of Software Evolvability Using Code Smells: An Empirical Study. Empirical Software Engineering 11, 395–431 (2006)
15. IEEE: IEEE Standard for Software Maintenance. IEEE Std 1219-1998, 1–56 (1998)
16. Suryanarayana, G., Samarthyam, G., Sharma, T.: Refactoring for Software Design Smells: Managing Technical Debt. Morgan Kaufmann Publishers Inc, San Francisco, CA, USA (2014)
17. Král, J., Žemlicka, M.: The Most Important Service-Oriented Antipatterns. In: International Conference on Software Engineering Advances (ICSEA 2007), p. 29 (2007)
18. Bogner, J., Boceck, T., Popp, M., Tschechlov, D., Wagner, S. and Zimmermann, A.: Service-Based Antipatterns, https://xjreb.github.io/service-based-antipatterns/
19. Lippert, M., Roock, S.: Refactoring in large software projects: performing complex restructurings successfully. John Wiley & Sons (2006)
20. Shvets, A.: Refactoring: clean your code, https://refactoring.guru/refactoring
21. IEEE: IEEE Standard Glossary of Software Engineering Terminology. IEEE Std 610.12- 1990 121990, 1–84 (1990)
22. DeLone, W.H., McLean, E.R.: The DeLone and McLean model of information systems success. A ten-year update. J. Manage. Inf. Syst. 19, 9–30 (2003)
23. Lange, M., Mendling, J., Recker, J.: A Comprehensive EA Benefit Realization Model‐An Exploratory Study. In: 2012 45th Hawaii International Conference on System Sciences, pp. 4230–4239 (2012)
24. Timm, F., Hacks, S., Thiede, F., Hintzpeter, D.: Towards a Quality Framework for Enterprise Architecture Models. In: Lichter, H., Anwar, T., Sunetnanta, T. (eds.) Proceedings of the 5th International Workshop on Quantitative Approaches to Software Quality (QuASoQ 2017) co-located with APSEC 2017, pp. 10–17. CEUR-WS.org (2017)
25. Becker, J., Probandt, W., Vering, O.: Grundsätze ordnungsmäßiger Modellierung. Konzeption und Praxisbeispiel für ein effizientes Prozessmanagement. Springer Berlin Heidelberg, Berlin Heidelberg (2012)
26. Pitschke, J.: Gute Modelle‐Wie die Qualität von Unternehmensmodellen definiert und gemessen werden kann, https://www.enterprise-design.eu/files/images/downloadswissen/ modelqualitaet_v2.0.pdf
27. Koschmider, A., Laue, R., Fellmann, M.: Business Process Model anti-Patterns: a Bibliography and Taxonomy of published Work. In: ECIS (2019)
28. Fontana, F.A., Ferme, V., Marino, A., Walter, B., Martenka, P.: Investigating the Impact of Code Smells on System’s Quality: An Empirical Study on Systems of Different Application Domains. In: 2013 IEEE International Conference on Software Maintenance, pp. 260–269 (2013)
29. Sharma, T., Fragkoulis, M., Spinellis, D.: Does Your Configuration Code Smell? In: 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR), pp. 189– 200 (2016)
30. Schwarz, J., Steffens, A., Lichter, H.: Code Smells in Infrastructure as Code. In: 2018 11th International Conference on the Quality of Information and Communications Technology (QUATIC), pp. 220–228 (2018)
31. van der Bent, E., Hage, J., Visser, J., Gousios, G.: How good is your puppet? An empirically defined and validated quality model for puppet. In: 2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 164–174 (2018)
32. Rahman, A., Williams, L.: Characterizing Defective Configuration Scripts Used for Continuous Deployment. In: 2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST), pp. 34–45 (2018)
33. Cito, J., Schermann, G., Wittern, J.E., Leitner, P., Zumberi, S., Gall, H.C.: An Empirical Analysis of the Docker Container Ecosystem on GitHub. In: 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR), pp. 323–333 (2017)
34. Jha, A.K., Lee, S., Lee, W.J.: Developer Mistakes in Writing Android Manifests: An Empirical Study of Configuration Errors. In: 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR), pp. 25–36 (2017)
35. Bogner, J., Boceck, T., Popp, M., Tschechlov, D., Wagner, S., Zimmermann, A.: Towards a Collaborative Repository for the Documentation of Service-Based Antipatterns and Bad Smells. In: (2019)
36. Sabir, F., Palma, F., Rasool, G., Guéhéneuc, Y.-G., Moha, N.: A systematic literature review on the detection of smells and their evolution in object-oriented and service-oriented systems. Software: Practice and Experience 49, 3–39 (2019)
37. Alexander, C.: A pattern language: towns, buildings, construction. Oxford university press (1977)
38. Wake, W.C.: Refactoring Workbook. Addison-Wesley Longman Publishing Co., Inc, Boston, MA, USA (2003)
39. Shvets, A., Frey, G. and Pavlova, M.: AntiPatterns, https://sourcemaking.com/antipatterns
40. Kerievsky, J.: Refactoring to Patterns. Pearson Higher Education (2004)
41. The Open Group: ArchiMate Model Exchange File Format. Version 2 (2015)
42. Greefhorst, D., Proper, E.: Architecture principles: the cornerstones of enterprise architecture. Springer Science & Business Media (2011)
43. Stelzer, D.: Enterprise Architecture Principles: Literature Review and Research Directions. In: Dan, A., Gittler, F., Toumani, F. (eds.) Service-Oriented Computing. ICSOC/ServiceWave 2009 Workshops, pp. 12–21. Springer Berlin Heidelberg, Berlin, Heidelberg (2010)
44. Hacks, S., Steffens, A., Hansen, P., Rajashekar, N.: A Continuous Delivery Pipeline for EA Model Evolution. In: Reinhartz-Berger, I., Zdravkovic, J., Gulden, J., Schmidt, R. (eds.) Enterprise, Business-Process and Information Systems Modeling. BPMDS 2019, EMMSAD 2019, pp. 141–155. Springer International Publishing (2019)