System theory glossary

Copyright 2017 Graham Berrisford. One of about 300 papers at Last updated 18/02/2018 21:11



The role of enterprise architects is to observe baseline systems, envisage target systems, and describe both.

So, you might assume their profession uses a controlled vocabulary of system concepts; but not so.

This paper provides such a controlled vocabulary or “domain-specific language”.

The terms are further explained in Introducing General System Theory.

Description theory

Thing: a subdivision of the universe, locatable in space and time, describable as instantiating one or more types.


Natural thing: a thing that emerges from the evolution of matter and energy, regardless of description.


Organism: a natural thing whose form is defined by it genes, and engages in the process of Darwinian evolution.


Designed thing: a thing described by an organism before it is created.


Describer: a thing (organism or machine) that can create and use a description.

The survival of describers depends on their ability to create and use descriptions of reality.


Description: a thing that idealises another thing by recording or expressing some of its properties.

A memory, message, model or view that captures/encodes knowledge of a thing’s properties.

It enables that knowledge to remembered and/or communicated.

It enables some questions about the described thing to be answered.


Set: a collection of things that are similar in so far as they instantiate (embody, exemplify) one type.


Type: an intensional definition, composed of property type(s) that describe a thing.


Instance: an embodiment by one thing of a type, giving values to the properties of that type.


Sign: a name, image or effect of a thing or a type, which describers use in recognising, thinking or communicating about that thing or type.


Token: an appearance of a sign or a type in a memory or message.


Read Introducing Description Theory for more.

Early ideas

System: an overloaded term; a catch-all term used to label passive structures and activity systems.

It can mean either abstract (theoretical) system description or concrete (empirical) systems.

But it is commonly used to mean a concrete activity system.


Passive structure: an element or group of related elements that may be acted in or on, but does not act.

E.g. a garden fence, a telephone directory, a necklace, the Dewey Decimal System, or a data structure.


Activity system: a structure whose elements interact (directly or indirectly) in regular behaviors.

A thing whose regular or repeatable activities act to maintain the state of the thing and/or reach other goals.

E.g. the solar system, an organism, a software system, a choir, a tennis match.


The primacy of behaviour: the principle that system theory is concerned with systems that display regular, repeated or repeatable behaviors.


Atomic element: an element that is not further divided in a description.

Describers decompose a system to the level they regard as atomic elements.

E.g. An organ in the human body, a human in a society, a note in a musical score.

Or any one-person-one-place-one time activity in a human activity system

Atomic system actors may be complex entities in their own right, and may play roles in other systems.


Reductionist view: identifying the parts of a whole, naming or describing parts without considering how the parts are related in the whole.

E.g. listing the organs and limbs of the body without relating them. Or analysing and describing the heart without reference to the lungs.


Holistic view: a description of how parts relate, interact or cooperate in a whole.

E.g. a description of how the muscles of the human heart interact.


Emergent property: a behaviour or structure of a whole that depends on interactions between its parts.

E.g. the forward motion of a cyclist on a bicycle, or the V shape of a flight of geese.

Typically, the property is not found in any one part, or predictable by studying a part in isolation from others.

The exception is systems with homogenous populations, where a subset of the whole may have the same properties as the whole.

Note that emergent properties are the very purpose of system design.


Organicism: the idea that systems are describable at multiple hierarchical levels (as von Bertalanffy named it).

E.g. Consider the decomposition of a human body through organ, cell, organelle and molecule to atom.

Or the decomposition of software application through component, class and operation to executable instruction.

System boundary


System environment: the world outside the system of interest.

Most system design methods separate a system from its wider environment

The environment of one system may be a wider system.


Closed system: a system that does not interact with anything in the wider environment.

All events of interest are internal to the system.

E.g. A System Dynamics model is a closed system of stocks and flows.


Open system: a system that interacts with entities and events in a wider environment.

Inputs can change the state of the system; outputs can change the state of entities in the environment.

Many system design methods scope a system by its inputs and outputs

“Every living organism is essentially an open system. It maintains itself in a continuous inflow and outflow…” Bertalanffy


System boundary: a line (physical or logical) that separates a system from is environment

It encapsulates the system’s internal structures and behaviors.

It defines the system’s input-process-output boundary.

Inputs and outputs can be flows of material, energy or information.


System interface: a description of inputs and outputs that cross the system boundary.

An interface defines the system as it is seen by external observers.

An interface may be defined in a contract defining services provided or required.

In social and software systems, the primary inputs and outputs are information flows..

Systems as conceptualisations

Abstract system description: a description or model of a concrete system.

E.g. a physical model, a narrative, a context diagram, a network diagram, a causal loop diagram, or a combination of such artifacts.

Abstract descriptions do take concrete forms (they are found in mental and documented models).

At the same time, they describe (model, conceptualise, idealise) a physical reality that can be envisaged or actually observed as matching the description.


Concrete system (aka System): a system that runs in reality.

A realization in physical matter and/or energy of an abstract system description.

A real world entity that can be tested as meeting an abstract system description – well enough.

Note that one real world entity can realise many different abstract systems.


A concrete activity system need not match an abstract system description perfectly; it need only pass system testing well enough.

However, software systems are perfect in the sense that, at run time, they can do only what is described in their code.

System structure and behavior

The structure/behaviour dichotomy:.the distinction between structures addressable space and behaviors that happen over time.


Structure: passive structures and actors in space

Behavior: atomic actions and processes over time

Structures that are shaped or directed by behaviors.

Entities that are created, changed and destroyed by Events.

Stocks that are incremented and decremented by Flows.

Components that perform Processes and deliver Services.

Behaviors that are performed by active structures.

Events that create, change and destroy Entities.

Flows that increment and decrement Stocks.

Processes performed and Services delivered by Components.

Structure - along the lines defined in UML

Behavior - along the lines defined in UML

A structural entity may be an active actor (with a thread of control) or a passive object.

Actors respond to messages generated by actors performing communication actions.

All behavior is triggered by and composed of actions performed by actors.

An actor instantiates an entity type/role by performing the behaviors of that type/role.

An action is the atomic unit in the specification of behaviour.

An action converts a set of inputs and into a set of outputs.

Repeatable behaviors are often modelled as discrete event-driven processes.

The time between events can small enough to simulate continuous behaviors.


State: the current structure of a thing, as described in the current values of its variable properties.

An entity’s concrete state is directly observable in the values of its physical position, energy and material variables.

E.g. the location, temperature, colour, and matter state (solid/liquid/gas) of a thing you see in front of you.

Information state is found in the values of descriptive variables held in a memory or database of some kind.


Event: a discrete input that triggers a process that changes a system’s state, depending on the current state.

Note: this is the basis of modelling a system using discrete event dynamics and system dynamics.

Note: information systems also consume enquiry events that report current state.


Process: one or more state changes over time, or the logic that determines which state changes lead to which other state changes.

A concrete process may be directly observed in changes to the state of the world.

An abstract process is a description or specification of discrete or continuous state change.

See the footnote on processes.


Stochastic: the quality of a system that means its next or future state is not predictable, and appears random.


Hysteresis: the process by which a system’s information state can be derived by replaying all events that have so far crossed the system boundary.

Read Determinism and hysteresis for more.


Information: a meaning created or found by an actor in any physical form that acts as a signal.

Any description or direction that has been encoded in a signal or decoded from it by an actor.


Signal: any structure of matter or energy flow in which an actor creates or finds information.

In human communications, the physical forms include brain waves and sound waves.

In digital information systems, the physical form is a data structure in a binary code – in matter or energy.


Information flow (aka message): physically, a signal passed from sender to receiver, logically, a communication.


Information state (aka memory): see “state”.


Information quality: an attribute of information flow or state, such as speed, throughput, availability, security, monetary value.


Information feedback loop: the circular fashion in which system inputs influence future outputs and vice-versa.


Read Communication theory and Information feedback loops for more.

System change

Deterministic: the quality of a system that means its next state is predictable from its current state and input event.

A deterministic system, in a given state, will respond to a particular stimulus by acting in a predictable way.

Paradoxically, as a result of processing a series of events, a system may change in an unpredictable, chaotic or non-linear fashion.

Read Determinism and hysteresis for more


Linear change: progress or change over time that is represented in a graph as a straight line (or else a regular shape).


Non-linear change: progress or change over time that is represented in a graph as a curve (or else an irregular shape).


System state change a change to the state of a system, which changes the value of at least one variable.


System mutation: a change to the nature of a system, which changes the type of at least one variable or behavior.


Meta system: a system that defines a system or transforms it from one generation to the next.

Meta systems include biological evolution, which depends on the process of sexual reproduction and DNA to define and change an organic system.

And those human actors who perform processes (as in an analysis and design methodology) to define and change a designed system.

Read System stability and change for more.


Linear descriptions may be realised as a non-linear realities

Some interpret linear differently from above; to mean merely “sequential”.

The sequential process for making a hamburger might be called linear.

All we say or write must be presented sequentially; but the reality we describe may not be sequential.

The US constitution is a linear document; the reality it describes is a complex network of government bodies.

Natural systems and designed systems

Natural system: a system that runs before it is described by man.

Its repeated behaviors evolved without externally-defined drivers or goals.

E.g. a solar system, weather system or biological organism.


Designed system: a system described by man before it runs.

Its reproducible behaviors are defined in response to externally-defined drivers or goals.

E.g, a cuckoo clock, a motor car, an accounting system, a choir, a tennis match.

Social systems, social entities and social cells

Social system: a system in which animate actors play roles in regular, repeatable processes.


Social entity: a group of actors who may chose their own behaviors, and may interact to reach agreed aims.

Since the roles and rules of a social entity are adhoc and in flux, it cannot be described or tested as matching a description.


Social cell: a social system whose roles reward the actors of a social entity sufficiently well to ensure the actors voluntarily perpetuate the system.

Read Social cells for discussion of a social cell as mutually beneficial, or insidious, or even as a parasite on society.

Discrete v continuous system dynamics

System Dynamics: a tool for system observers to describe system behaviors in terms of stocks and flows.

A stock is a dynamic set of things – it has a number of members - a quantity - a stock level.

A flow between two stocks represents events that change stock levels over time.


Natural systems and analogue designed systems are continuous; time is not divided into units.

Most business systems are discrete event-driven, meaning that every process is triggered by an event.

The event may carry some input data, or may be only a trigger; it can be a time unit event.


Enterprise: has several meanings; usually implies a business led by executive managers/directors, or a segment thereof.


Organization: generally, a structure in which elements are related; here, a structure in which human roles of enterprise are related; it usually implies lines of command and control.


Management system: generally, a system that monitors and directs an entity; here, one that monitors and directs the operational systems of an enterprise.


Team: generally, a group of actors who interact; sometimes a node in an organisation structure; sometimes a group dedicated to the completion of a behaviour (a project or task).

Questionable concepts and principles


Read Hierarchical and network organisations for discussion.


Inexorable progress?

Read Marxism, system theory and EA for discussion.


Goal directedness?

Read Goal-directedness for discussion.



The term implies complicated in some way, but there no agreed measure of complexity.

Bertalanffy said system elements are discrete, can be classified into kinds, can be counted, and the relationships between them can be described.

“In dealing with complexes of 'elements', three different kinds of distinction may be made: according to their number; their species; the relations of elements.” von Bertalanffy

To measure complexity, should we measure the concrete system or its abstract system description?


The only way to measure the complexity of a system is by reference to a description of it structures and behaviors.

Suppose we were able to count element kinds and relationships in an abstract system description

How to combine those numbers into an overall complexity measure?

Scores of complexity measures have been proposed.

E.g. my own: complexity = the number of event/state combinations * the average procedural complexity of the rules applied to them.


The term complex is sometimes used to mean a non-linear or stochastic system.

But simple deterministic systems can behave in non-linear or stochastic ways.


So, a complex entity may be seen as a simple system.

Every hamburger is infinitely complex; but the recipe for a hamburger is a relatively simple abstract system description.

Every real-world US government is infinitely complex; but the US constitution is relatively simple abstract system description.

A US government can be called a system where and in so far as it realises the US constitution.

But most of the time, government actors are choosing and performing activities in ad hoc ways not explicitly described in the constitution.

As a social entity, the US government is infinitely complex; as a system it is relatively simple.

Read Complexity for more.


In systems thinking discussions, the following pairs of terms are often confused; but strictly, each pair represents two distinct concepts.


Holistic versus Systemic

Holistic: considering how the parts of a whole are related; taking a view that addresses how parts cooperate to the benefit of the whole.

See also:

Systemic: relating to the whole rather than a part; reaching throughout the whole, pervasive throughout a system.

(E.g. A systemic drug or disease that reaches and has an effect on the whole of a body.)

See also:

To be holistic isn’t the same as being pervasive throughout a system.


Reductionism versus Analysis

Reductionist view: identifying the parts of a whole, naming or describing parts, without considering how the parts are related in the whole.

Analysis: dividing a whole into parts, which can at the same time reveal how the parts are related in the whole.


Analytic(al) versus Systematic

Analytic (aka analytical): using or skilled in using analysis; separating a whole (description or reality) into parts or basic principles.

See also:

Systematic: methodical, acting according to a fixed process or system.

See also:

You may be analytical in a systematic way; but you may be systematic without analysing anything.

Footnote: on processes

A concrete process may be directly observed in changes to the state of the world.

E.g. an apple falls from a tree; a cash payment is handed by one actor to another.


An abstract process is a description or specification of discrete or continuous state change.

E.g. a flow chart showing the control logic governing event-triggered activities that result in discrete state changes.

E.g. mathematics describing the continuous change to the position of a planet in its orbit.


The universe may be viewed as ever-unfolding processes.

And the structures within it viewed as results of those processes.

E.g. Stars and planets can be seen as side effects of gravitational forces.


A biological entity maintains itself cyclically by what is called autopoiesis.

The processes are performed by structural elements.

The structural elements are manufactured and maintained by processes.


A designed activity system may be viewed as a set of designed processes.

And some structures within it may be manufactured by those processes.

However, we must hire or build active structures (actors/components) to perform designed processes.

E.g. hire musicians to perform the parts in a symphony.


It is wrong to think of people (hired to play roles) as parts of a designed system.

The parts are performances of system roles by people.

The people live outside of any system they play a role in, and are much more than any role they play.


In practical systems analysis and design it is normal to distinguish processes from systems.

A system has persistent structure (describable in a network or data flow diagram) in which actors perform processes in parallel.

A process is an event-triggered behaviour (describable in simple flow chart) that runs from start to end over time.



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