A2 · Pattern Recognition

Spec reference: Section A - Computational Thinking
Key idea: Identify similarities, trends and repeated structures within problems.

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▶ Pattern Recognition

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Identifying common elements or features

Patterns appear in two ways in computing:

1. Patterns within a single problem

When you look at one problem closely, you often notice the same operation happening repeatedly in different places.

Example: Drawing multiple shapes

If a program needs to draw a square, a triangle, and a pentagon, you notice a pattern:

• Each shape is made of straight lines.
• Each line connects two points.
• Each shape is closed (the last point connects back to the first).

The pattern → you can write one function that draws any polygon rather than separate code for each shape.

2. Patterns across different problems

When you have solved several problems, you recognise that a new problem is similar to one you have already solved.

Example: Login vs booking systems

Login system	Booking system
Get username & password	Get customer ID & date
Validate against database	Check availability in database
Allow or deny access	Confirm or decline booking

The pattern → both systems: take input → check database → respond with success or failure. The same structural solution applies to both.

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Why pattern recognition matters

Recognising patterns lets programmers:

Benefit	Explanation
Reuse code	Write a function once, call it many times
Reduce errors	Fewer lines of unique code means fewer bugs
Save time	Adapting an existing solution is faster than starting from scratch
Create algorithms	Patterns in data often reveal the algorithm needed to process it

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Pattern recognition in data

Sometimes the pattern is in the data itself, not the code structure.

Example: Temperature readings

Mon: 14°C  Tue: 13°C  Wed: 15°C  Thu: 14°C  Fri: 12°C

Pattern → temperatures vary within a small range. A simple averaging algorithm is appropriate. You don't need a complex model.

Example: Exam scores

Student A: 45, 47, 46, 44, 45
Student B: 20, 65, 91, 12, 88

Pattern → Student A's scores are consistent (low variance), Student B's are erratic (high variance). Different reporting logic may be needed for each.

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Pattern recognition and functions

The most direct practical use of pattern recognition in programming is spotting when to write a function. If you find yourself writing the same block of code more than once, that is a pattern - and you should extract it into a reusable function.

# WITHOUT pattern recognition  -  repeated code
print("Hello, Alice")
print("Hello, Bob")
print("Hello, Carol")

# WITH pattern recognition  -  function captures the pattern
def greet(name):
    print("Hello, " + name)

greet("Alice")
greet("Bob")
greet("Carol")

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Exam tip

In the exam, if you are asked to identify patterns in a scenario, look for:

• Steps that repeat with different data.
• Processes that are structurally identical to a previous example.
• Data values that follow a trend or cycle.

State the pattern explicitly: "The same validation process is used for both the username and the postcode fields - in both cases the input is checked against a regular expression pattern."

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Summary

Concept	Meaning
Pattern recognition	Finding repeated elements or similarities in problems
Common features	Shared characteristics across different problems
Code reuse	Using the same solution (e.g. a function) in multiple places
Data patterns	Trends or regularities in data values

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Test Yourself

Question 1 of 5

What is pattern recognition in the context of computational thinking?