SEJun 7, 2016

Evidences of the mismatch between industry and academy on modelling language quality evaluation

arXiv:1606.02025v17 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of inconsistent quality evaluation in model-driven engineering for practitioners and researchers, but it is incremental as it reports on existing evidence rather than proposing new solutions.

The paper identifies quality issues in modeling languages and models by analyzing evidence from industrial and academic contexts, highlighting a mismatch in how quality is conceived between these domains.

Quality is an implicit property of models and modelling languages by their condition of engineering artifacts. However, the quality property is affected by the diversity of conceptions around the model-driven paradigm. In this document is presented a report of quality issues on modelling languages and models. These issues result from an analysis about quality evidences obtained from industrial and academic/scientific contexts.

Foundations

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

Your Notes