Managed Evolution

Murer, Stephan; Worms, Carl; Furrer, Frank J.

doi:10.1007/s00287-008-0290-9

Cited by 14 publications

(1 citation statement)

References 5 publications

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“…More and more software systems rely on models to easily reference, refine, and validate aspects of a business domain in a cost-effective way [32]. With current software systems increasing in complexity and rate of change [28], these models become more complex and change continuously, too. While maintaining and refining complex models is possible with state-of-the-art tools [22], their continuous evaluation and validation still poses problems for large complex models.…”

Section: Introductionmentioning

confidence: 99%

Continuous model validation using reference attribute grammars

Mey

Schöne

Hedin

et al. 2018

Proceedings of the 11th ACM SIGPLAN International Conference on Software Language Engineering

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Just like current software systems, models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated and validated. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform an incremental analysis efficiently using dynamic dependency tracking. However, not all features used in conceptual modelling are directly available in RAGs. In particular, support for non-containment model relations is only available through manual implementation. We present an approach to directly model uni-and bidirectional non-containment relations in RAGs and provide efficient means for navigating and editing them. This approach is evaluated using a scalable benchmark for incremental model editing and the JastAdd RAG system. Our work demonstrates the suitability of RAGs for validating complex and continuously changing models of current software systems. CCS Concepts • Theory of computation → Grammars and context-free languages; • Software and its engineering → System description languages; • Computing methodologies → Model verification and validation;

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Section: Introductionmentioning

confidence: 99%

Continuous model validation using reference attribute grammars

Mey

Schöne

Hedin

et al. 2018

Proceedings of the 11th ACM SIGPLAN International Conference on Software Language Engineering

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Complexity Levels of Representing Dynamics in EA Planning

Aier

Gleichauf

Saat

et al. 2009

Lecture Notes in Business Information Processing

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Enterprise Architecture (EA) models provide information on the fundamental as-is structure of a company or governmental agency and thus serve as an informational basis for informed decisions in enterprise transformation projects. At the same time EA models provide a means to develop and visualize to-be states in the EA planning process. Results of a literature review and implications from industry practices show that existing EA planning processes do not sufficiently cover dynamic aspects in EA planning. This paper conceptualizes seven levels of complexity for structuring EA planning dynamics by a system of interrelated as-is and to-be models. While level 1 represents the lowest complexity with non-connected as-is and to-be models, level 7 covers a multiperiod planning process also taking plan deviations during transformation phases into account. Based on these complexity levels, a multi-stage evolution of EA planning processes is proposed which develops non-dynamic as-is EA modeling into full-scale EA planning.

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Anwendungslandschaften von Versicherungsunternehmen

Uzquiano

2010

Informationsverarbeitung in Versicherungsunternehmen

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Managed Evolution

Cited by 14 publications

References 5 publications

Continuous model validation using reference attribute grammars

Continuous model validation using reference attribute grammars

Complexity Levels of Representing Dynamics in EA Planning

Anwendungslandschaften von Versicherungsunternehmen

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