Description

In SW engineering, code metrics tell something abou the complexity of a programme. Various metrics exist, ranging form simple ones line the number of lines of code, to advance ones like cyclomatic complexity.

Code metrics can tell something abou the code quality. This is extremely important: good code is easy to maintain, refactor,
and port. Bad code costs time and money and frustration.

However, for software models, few of such metrics exist, even though that such metrics could be equally useful for models as for code. Thus, the idea of this project is to come up with model metrics and evaluate if they make sense. 

Note that various models could be studied: finite state automata, UML models, fault trees, etc. 

Even though no company is involved, this is relevant for industry; we can involve companies later

TASKS

- Study the state-of-the-art

- Define model metrics

- Evaluate on relevant case studies or examples: do these metrics really tell us what we want?