Taxonomy/2. Methodology/Quality of models

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Taxonomy
of Computer Science
Hanno Wupper
Hans Meijer
Angelika Mader
Stijn Hoppenbrouwers
Mieke Boon


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Seven things we want to know about a model

  1. Purpose
    • of model
      • artefacts
        • design
        • verification
        • support maintainability and evolvabiloity
        • exploring (creativity, seeing new options)
        • optimisation
      • anything
        • understanding
        • explain
        • teaching
        • knowledge integration
        • simulation
        • control, steer
    • of modelling process
      • find justification arguments for design decisions
      • find errors
      • unterstand
  2. Pragmatics
    • model
      • How much may it cost to make the model?
      • How long is the model needed?
      • Must it be maintained?
        • How long?
        • By whom?
        • What is that allowed to cost?
    • modelling process
      • e.g. follow organisational structures of enterprise?
  3. Epistemic criteria
    • model
      • truthful
      • complete
      • simple
      • understandable
      • tracable
        • fault in model can be traced back to fault in thing
        • which parts of the artefact are reflected at which point in the model
    • modelling process
      • efficiently constructable and maintainable
  4. Focus
    • fragment of reality
    • environment
    • view (timing, liveness, safety, security, ...)
    • levels: how many? (e.g. embedded systems)
    • granularity
  5. Structure
  6. Mathematical domain
  7. Simplifications and idealisations
    • Simplification: regard negligible quantities as zero; mass points
    • Idealisations: infinite word length; linear approx. of trigonometrical functions, height-independent air pressure