2.1.1

Computational Thinking

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Abstraction

Abstraction is a key concept to computer science and allows us to simplify a given problem.

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Abstraction

  • Abstraction is a technique that simplifies a problem by removing unnecessary detail so that you can focus on the important parts that are relevant to the problem.
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Examples of abstraction

  • Maps are a classic example of abstraction.
  • They leave out many details in order to focus on the important information, such as roads and landmarks.
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Examples of abstraction

  • Money is an abstract concept.
  • Money has no real value (it's just a piece of paper!) in itself, but it represents the value of goods and services.

Decomposition

Decomposition is a key concept in computer science, which helps us to solve problems.

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Decomposition

  • Decomposition means breaking a complex problem into smaller, more manageable sub-problems.
  • Each smaller part can then be solved individually, before all the sub-solutions are combined to solve the original problem.
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Advantage of decomposition

  • Decomposition allows large teams to each take a part of a problem and work on it.
  • Decomposition allows seemingly impossible problems to be solved by splitting them into simple tasks.
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Structure charts

  • Structure charts are used to visually represent breaking a large problem down into the smaller parts that make it up.
  • Each box represents a smaller problem to be solved.
  • Lines show which bigger problem the box is a part of.

Jump to other topics

1Computer Systems

1.1Systems Architecture

1.2Memory & Storage

1.3Computer Networks, Connections & Protocols

1.4Network Security

1.5Systems Software

1.6Ethical, Legal, Cultural & Environmental Concern

2Computational Thinking, Algorithms and Programming

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