System Modelling

3 min read Last updated Tue Jun 09 2026 03:05:56 GMT+0000 (Coordinated Universal Time)

The process of creating abstract representations (named models) of a system. Each model shows a different perspective. UML is used to illustrate the model. Models help clarify system functionality and communicate design to stakeholders.

Models serve 2 roles:

  • Analysis
    Clarifying what the system must do.
  • Design
    Specifying how the system will be structured and behave.

No model is fully accurate. Each is a selective simplification. Omitted details may be critical.

Perspectives

  • External
    Shows system context.
  • Interaction
    Shows interactions between system components or external entities.
  • Structural
    Shows system organization and data structure.
  • Behavioral
    Shows system behavior over time.

Context Modeling

Describes the environment in which a system operates. Shows system boundaries, external actors and relationships.

Often represented using system context diagrams.

System Boundary

Defines what is inside the system and what lies outside it.

  • Show other systems that interact with the system.
  • Influence system requirements.
  • Boundary decisions may involve organizational or political considerations.

Interaction Modeling

Describes how users or system components interact with the system. Illustrated using use case diagrams and sequence diagrams.

Used to:

  • Identify user requirements.
  • Detect communication issues between systems.
  • Evaluate system structure performance.

Structural Modeling

Models class relationships in object-oriented systems.

Generalization

A modeling technique where common features of multiple classes are abstracted into a superclass.

  • Implements inheritance in object-oriented systems.
  • Subclasses inherit attributes and methods from the superclass.

Aggregation

Represents a whole-part relationship between classes.

  • Shows that a class is composed of other classes.
  • Similar to part-of relationship in semantic models.

Behavioral Modeling

Models system behavior driven by data or events.

Data-Driven Modeling

Represents systems where processing is controlled mainly by incoming data.

  • Focus on data processing workflows.
  • Represent end-to-end processing.

Event-Driven Modeling

Describes systems where internal or external events trigger state changes. Used in real-time and embedded systems.

State Machine Models

Represent system behavior using states and transitions triggered by events.

  • States
    System conditions.
  • Transitions
    Changes triggered by events.

Complementary Models

No single model is sufficient. Each excludes some aspect of reality:

  • Context models exclude internal behaviour.
  • Use case models exclude non-functional properties.
  • Class diagrams exclude time and concurrency.
  • Sequence diagrams exclude exceptional flows.
  • Architectural diagrams exclude platform specifics.
  • State models exclude cross-object concurrency.

Effective practice requires multiple complementary models at each lifecycle stage. Gaps between models are where defects most commonly reside.

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