SESep 8, 2014

Model Evolution and Management

arXiv:1409.2361v134 citations
Originality Synthesis-oriented
AI Analysis

This work tackles model management challenges for software engineers and developers, but it is incremental as it reviews existing state-of-the-art without introducing new methods.

The chapter addresses the need for managing and evolving models in software development, similar to how software is handled, by discussing current practices and identifying gaps to make models as practical and widely used as software.

As complex software and systems development projects need models as an important planning, structuring and development technique, models now face issues resolved for software earlier: models need to be versioned, differences captured, syntactic and semantic correctness checked as early as possible, documented, presented in easily accessible forms, etc. Quality management needs to be established for models as well as their relationship to other models, to code and to requirement documents precisely clarified and tracked. Business and product requirements, product technologies as well as development tools evolve. This also means we need evolutionary technologies both for models within a language and if the language evolves also for an upgrade of the models. This chapter discusses the state of the art in model management and evolution and sketches what is still necessary for models to become as usable and used as software.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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