On the contrary, executable modeling languages are intended to amplify the productivity of skilled programmers, so that they can address more challenging problems, such as parallel computing and distributed systems.
Gellish Formal English is not only suitable to express knowledge, requirements and dictionaries, taxonomies and ontologies, but also information about individual things.
All that information is expressed in one language and therefore it can all be integrated, independent of the question whether it is stored in central or distributed or in federated databases.
For example, a geographic information model might consist of a number of Gellish Formal English expressions, such as: whereas information requirements and knowledge can be expressed for example as follows: Such Gellish Formal English expressions use names of concepts (such as "city") and phrases that represent relation types (such as ⟨is located in⟩ and ⟨is classified as a⟩) that should be selected from the Gellish English Dictionary-Taxonomy (or of your own domain dictionary).
The Gellish English Dictionary-Taxonomy enables the creation of semantically rich information models, because the dictionary contains more than 600 standard relation types and contains definitions of more than 40000 concepts.
Algebraic Modeling Languages (AML) are high-level programming languages for describing and solving high complexity problems for large scale mathematical computation (i.e. large scale optimization type problems).
One particular advantage of AMLs like AIMMS, AMPL, GAMS, Gekko, Mosel, OPL, MiniZinc, and OptimJ is the similarity of its syntax to the mathematical notation of optimization problems.
This allows for a very concise and readable definition of problems in the domain of optimization, which is supported by certain language elements like sets, indices, algebraic expressions, powerful sparse index and data handling variables, constraints with arbitrary names.
These languages focus on the description of key concepts such as: concurrency, nondeterminism, synchronization, and communication.
A discipline-specific modeling (DspM) language is focused on deliverables affiliated with a specific software development life cycle stage.
Therefore, such language offers a distinct vocabulary, syntax, and notation for each stage, such as discovery, analysis, design, architecture, contraction, etc.
In addition, the discipline-specific modeling language best practices does not preclude practitioners from combining the various notations in a single diagram.
Informal diagramming techniques applied with drawing tools are expected to produce useful pictorial representations of system requirements, structures and behaviors, which can be useful for communication, design, and problem solving but cannot be used programmatically.
[5]: 539 Executable modeling languages applied with proper tool support, however, are expected to automate system verification and validation, simulation and code generation from the same representations.
To evaluate the participant appropriateness we try to identify how well the language expresses the knowledge held by the stakeholders.
Comprehensibility appropriateness makes sure that the social actors understand the model due to a consistent use of the language.