SESep 22, 2014

Scaling-Up Model-Based-Development for Large Heterogeneous Systems with Compositional Modeling

arXiv:1409.6586v130 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of scaling model-based development for complex software systems, but it appears incremental as it builds on existing MDA approaches.

The paper identifies why Model-Driven Architecture (MDA) has failed to effectively support large, heterogeneous systems due to inadequate tools and methodologies, and proposes improvements to make it suitable for ultra-large, distributed systems.

Model-based development and in particular MDA [1], [2] have promised to be especially suited for the development of complex, heterogeneous, and large software systems. However, so far MDA has failed to fulfill this promise to a larger extent because of tool support being inadequate and clumsy and methodologies not being appropriate for an effective development. This article discusses what went wrong in current MDA approaches and what needs to be done to make MDA suited for ultra-large, distributed systems.

Foundations

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

Your Notes