Abstraction Concept Analysis Diagram

Core Concept:

  • Abstraction: The process of separating the essential qualities of something from the details you don’t need. In computing, it’s often about simplifying complex reality while retaining the relevant aspects.


  1. Simplification: Reducing complex elements to fundamental parts.
  2. Generalization: Focusing on broad, overarching principles.
  3. Modularity: Breaking down tasks or systems into smaller, manageable parts.
  4. Data Hiding: Encapsulating details that are not necessary for the user to know.


  1. Complexity: Exists when details are too numerous or difficult to understand.
  2. Cognitive Limitation: Human ability to process information is finite.
  3. Need for Efficiency: Simplification can make systems and processes more efficient.


  1. Negative: Over-abstraction can lead to loss of essential details.
  2. Positive: Enables easier understanding, problem-solving, and system design.

Interrelated Concepts:

  1. Problem-Solving: Abstraction aids in breaking down complex problems.
  2. Object-Oriented Programming: Encapsulates complexity through classes and objects.
  3. Mathematics: Uses abstractions like numbers and figures to represent complex realities.


  1. Functional Abstraction: In coding, a way to wrap a sequence of operations under a single name.
  2. Data Abstraction: In databases, a way to simplify complex data structures.
  3. Visual Abstraction: In art, simplifying visual elements to basic shapes and forms.

Critical Components:

  1. Skill in Application: Knowing when and how to abstract effectively.
  2. Context Sensitivity: Understanding the specific scenario where abstraction is to be applied.
  3. Balance: Retaining essential complexity while removing irrelevant details.

Abstraction is a foundational concept in many fields including computing, mathematics, and art. It offers a structured approach to handle complexity, enabling efficiency and improved understanding. Knowing how to apply abstraction is critical for problem-solving and effective communication.

We can use a concept analysis diagram to visually illustrate the process of abstraction:

  • Consider each concrete object as a point at the bottom. These are our observed instances.

  • The attributes of each object are connected with lines to the corresponding objects.

  • As we inspect the objects, we begin grouping them into more general categories based on common attributes.

  • These categories can be visualized as larger circles enclosing the objects.

  • We can repeat this process, continually grouping the concepts into more and more abstract categories.

  • The higher-level categories encompass the details of the lower-level concepts within them.

  • At the top, we have the most abstract, high-level concepts that encapsulate all knowledge of the domain.

  • But the connections remain between the abstract concepts and the concrete objects.

So the diagram shows how concrete objects have attributes, which can be grouped into increasingly abstract concepts and categories, forming a hierarchy from specific to general.

The abstractions at the top summarize all the knowledge from the domain, while retaining the links down to the raw data. This provides an intuitive visualization of the abstraction process.

Here is an example of using the concept analysis template to represent “Abstraction”:

Concept: Abstraction


  • Process of generalization by reducing unnecessary detail
  • Focusing on relevant concepts rather than specific instances
  • Hiding implementation details behind an interface
  • Looking at the bigger, high-level picture rather than specifics


  • Having lower-level detailed examples or representations
  • Needing to understand, communicate or operate at a higher level
  • Seeking to generalize, identify patterns, see the forest not the trees


  • Improved comprehension of concept relationships
  • Reduced complexity
  • Ability to apply knowledge more broadly
  • Loss of specificity and details

Interrelated Concepts:

  • Generalization
  • Modularization
  • Encapsulation
  • Complexity management


  • Abstract classes
  • Abstract methods
  • Abstract data types
  • Abstract interfaces

Computer Science:

  • Using abstraction to reduce complex system details
  • Creating abstract APIs for easier usage
  • Building abstract layers to enable portability
  • Hiding implementation details behind interfaces

This demonstrates using the template to structure knowledge about a concept like abstraction, including key attributes, antecedents, consequences, and related concepts.