Learning objective
Automation: Understand that automation requires putting models (abstraction of real world objects/ phenomena) into action to solve problems. This is achieved by: • creating algorithms • implementing the algorithms in program code (instructions) • implementing the models in data structures • executing the code. Computer science is about building clean abstract models (abstractions) of messy, noisy, real world objects or phenomena. Computer scientists have to choose what to include in models and what to discard, to determine the minimum amount of detail necessary to model in order to solve a given problem to the required degree of accuracy. Computer science deals with putting the models into action to solve problems. This involves creating algorithms for performing actions on, and with, the data that has been modelled.
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Topic
Abstraction and automation
Subtopic
Automation
Aqa A Level Computer ScienceTheory of computation
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Quick explanation
Automation: Understand that automation requires putting models (abstraction of real world objects/ phenomena) into action to solve problems. This is achieved by: • creating algorithms • implementing the algorithms in program code (instructions) • implementing the models in data structures • executing the code. Computer science is about building clean abstract models (abstractions) of messy, noisy, real world objects or phenomena. Computer scientists have to choose what to include in models and what to discard, to determine the minimum amount of detail necessary to model in order to solve a given problem to the required degree of accuracy. Computer science deals with putting the models into action to solve problems. This involves creating algorithms for performing actions on, and with, the data that has been modelled
- This point belongs to Abstraction and automation, especially Automation.
- You need to be able to automation: Understand that automation requires putting models (abstraction of real world objects/ phenomena) into action to solve problems. This is achieved by: • creating algorithms • implementing the algorithms in program code (instructions) • implementing the models in data structures • executing the code. Computer science is about building clean abstract models (abstractions) of messy, noisy, real world objects or phenomena. Computer scientists have to choose what to include in models and what to discard, to determine the minimum amount of detail necessary to model in order to solve a given problem to the required degree of accuracy. Computer science deals with putting the models into action to solve problems. This involves creating algorithms for performing actions on, and with, the data that has been modelled.
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Why it matters
This objective helps connect Automation to exam-style questions, flashcards, and revision notes for Abstraction and automation.
Quick student answer
Which sequence best describes how automation uses an abstract model to solve a problem?
Direct answer
Create algorithms, implement them in program code, represent the model in data structures, and execute the code
Key terms
- Abstraction: The process of choosing what to include in a model of a real-world object or phenomenon and what to discard, keeping the minimum detail needed for the required solution and accuracy.
- Model: An abstraction of a real-world object or phenomenon that can be implemented and used to help solve a problem.
Common trap
Confusing the model with the algorithm: The model represents selected real-world data, whereas the algorithm describes the actions performed on or with that data.
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Related learning objectives
- Problem-solving: Be able to develop solutions to simple logic problems. Be able to check solutions to simple logic problems.
Problem-solving
- Following and writing algorithms: Understand the term algorithm. A sequence of steps that can be followed to complete a task and that always terminates. Be able to express the solution to a simple problem as an algorithm using pseudo-code, with the standard constructs: • sequence • assignment • selection • iteration. Be able to hand-trace algorithms. Be able to convert an algorithm from pseudo- code into high level language program code. 54 Be able to articulate how a program works, arguing for its correctness and its efficiency using logical reasoning, test data and user feedback.
Following and writing algorithms
- Abstraction: Be familiar with the concept of abstraction as used in computations and know that: • representational abstraction is a representation arrived at by removing unnecessary details • abstraction by generalisation or categorisation is a grouping by common characteristics to arrive at a hierarchical relationship of the 'is a kind of' type.
Abstraction
- Information hiding: Be familiar with the process of hiding all details of an object that do not contribute to its essential characteristics.
Information hiding
- Procedural abstraction: Know that procedural abstraction represents a computational method. The result of abstracting away the actual values used in any particular computation is a computational pattern or computational method - a procedure.
Procedural abstraction