SEJun 20, 2012

Modeling Languages: metrics and assessing tools

arXiv:1206.4477v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for quality assessment in software engineering, particularly for modeling languages, but is incremental as it builds on existing metrics and tools.

The paper tackles the problem of assessing the quality of models in software development, focusing on UML as the most popular modeling language, and presents metrics and tools through a case study.

Any traditional engineering field has metrics to rigorously assess the quality of their products. Engineers know that the output must satisfy the requirements, must comply with the production and market rules, and must be competitive. Professionals in the new field of software engineering started a few years ago to define metrics to appraise their product: individual programs and software systems. This concern motivates the need to assess not only the outcome but also the process and tools employed in its development. In this context, assessing the quality of programming languages is a legitimate objective; in a similar way, it makes sense to be concerned with models and modeling approaches, as more and more people start the software development process by a modeling phase. In this paper we introduce and motivate the assessment of models quality in the Software Development cycle. After the general discussion of this topic, we focus the attention on the most popular modeling language -- the UML -- presenting metrics. Through a Case-Study, we present and explore two tools. To conclude we identify what is still lacking in the tools side.

Foundations

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

Your Notes