The big idea: Decomposition, pattern recognition, abstraction and algorithmic design are not a programming method.
They are how any hard problem in computer science gets made solvable — and you have already used all four in this course.
You have met them already: Normalising a database was decomposition. An ERD was abstraction. A truth table was pattern recognition.
This micro names what you were doing, so you can do it deliberately.
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Database design
Data analysis
Machine learning
Network security
Why this matters for the exam: Paper 2 sets a question on algorithmic thinking with no code to read or write.
It is testing exactly this: can you take a problem in words and make it solvable, without reaching for a programming language.
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A method for unfamiliar problems: When a question describes something unfamiliar, the four concepts are a procedure, not a topic.
Apply them in order and an unfamiliar problem becomes several familiar ones.
1 — What are the pieces?
2 — What repeats?
3 — What can I ignore?
4 — What are the steps?
The trace is not optional: Working a small example by hand is what turns a plausible-looking algorithm into one you know is right.
It is also, very often, exactly what the exam asks you to do.
How this is tested — you must apply the concepts to an unfamiliar problem and show the thinking, not write code. It comes up two ways:
Paper 2 — working with code
- Explain how the concepts solve a described problem, 4-6 marks
- Break an unfamiliar problem into parts
- Justify what you chose to ignore
Paper 2 — the algorithmic-thinking question
- The algorithmic-thinking question is set here deliberately
- No code to read or write — the reasoning is the answer
The classic trap: Jumping to a solution. The marks are for the route — the pieces you identified, the pattern you spotted, what you left out and why. A right answer with no reasoning scores poorly here.
A city wants to know which of its 400 bus stops should get a shelter first. Explain how computational thinking would be applied. No code is required.
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