The quality of modelling languages

Why evaluate language quality

A review of modeling languages is essential to be able to assign which languages are appropriate for different modelling settings. In the term settings we include stakeholders, domain and the knowledge connected. Assessing the language quality is a mean to achieve better models.

Framework for evaluation

Here language quality is stated in accordance with the framework for quality of models developed by Krogstie, Sindre and Lindland (2003). since this is a framework that connects the language quality to a framework for general model quality. Five areas are used in this framework to describe language quality and these are supposed to express both the conceptual as well as the visual notation of the language (see Fig. 1). We will not go into a thoroughly explanation of the underlying quality framework of models but concentrate on the areas used to explain the language quality framework.

Domain appropriateness

The framework states the ability to represent the domain as domain appropriateness. The statement "appropriateness" can be a bit vague, but in this particular context it means "able to express". You should ideally only be able to express things that are in the domain but be powerful enough to include everything that is in the domain. This requirement might seem a bit strict, but the aim is to get a visually expressed model which includes everything relevant to the domain and excludes everything not appropriate for the domain. To achieve this, the language has to have a good distinction of which notations and syntaxes that are advantageous to present.

Participant appropriateness

To evaluate the participant appropriateness we try to identify how well the language expresses the knowledge held by the stakeholders. This involves challenges since a stakeholder's knowledge is subjective. The knowledge of the stakeholder is both tacit and explicit. Both types of knowledge are of dynamic character. In this framework only the explicit type of knowledge is taken into account. The language should to a large extent express all the explicit knowledge of the stakeholders relevant to the domain.

Modeller appropriateness

Last paragraph stated that knowledge of the stakeholders should be presented in a good way. In addition it is imperative that the language should be able to express all possible explicit knowledge of the stakeholders. No knowledge should be left unexpressed due to lacks in the language.

Comprehensibility appropriateness

Comprehensibility appropriateness makes sure that the social actors understand the model due to a consistent use of the language. To achieve this the framework includes a set of criteria. The general importance that these express is that the language should be flexible, easy to organize and easy to distinguish different parts of the language internally as well as from other languages. In addition to this, the goal should be as simple as possible and that each symbol in the language has a unique representation.

Tool appropriateness

To ensure that the domain actually modeled is usable for analyzing and further processing, the language has to ensure that it is possible to reason in an automatic way. To achieve this it has to include formal syntax and semantics. Another advantage by formalizing is the ability to discover errors in an early stage. It is not always that the language best fitted for the technical actors is the same as for the social actors.

Organizational appropriateness

The language used is appropriate for the organizational context, e.g. that the language is standardized within the organization, or that it is supported by tools that are chosen as standard in the organization

Sources

As base for this article we have used the following sources:

* Evaluating UML using a generic quality framework – John Krogstie – SINTEF Telecom andInformatics and IDI, NTNU, Norway
* Assessing business processing modeling languages using a generic quality framework – Anna Gunhild Nysetvold and John Krogstie –Institute of computer and information sciences.
* Information Systems Engineering: Conceptual Modeling in a Quality Perspective – Krogstie and Sølvsberg – Institute of computer and information sciences.