LO 1 - Computational Thinking

Pattern generalisation and abstraction

Why is abstraction important?

Abstraction enables us to remove all unnecessary detail from our problem and then solve the problem using a model.

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In software engineering and computer science, abstraction is a technique for arranging complexity of computer systems. It works by establishing a level of complexity on which a person interacts with the system, suppressing the more complex details below the current level. The programmer works with an idealized interface (usually well defined) and can add additional levels of functionality that would otherwise be too complex to handle.

To summarise abstraction is the gathering of the general characteristics we need and the filtering out of the details and characteristics that we do not need..

See also:

Abstraction principle (computer programming)
Abstraction inversion for an anti-pattern of one danger in abstraction
Abstract data type for an abstract description of a set of data
Algorithm for an abstract description of a computational procedure
Bracket abstraction for making a term into a function of a variable
Data modeling for structuring data independent of the processes that use it
Encapsulation for abstractions that hide implementation details
Greenspun's Tenth Rule for an aphorism about an (the?) optimum point in the space of abstractions
Higher-order function for abstraction where functions produce or consume other functions
Lambda abstraction for making a term into a function of some variable
List of abstractions (computer science)
Refinement for the opposite of abstraction in computing