Merge Sort (AQA GCSE Computer Science)

Revision Note

Test yourself
James Woodhouse

Written by: James Woodhouse

Reviewed by: Lucy Kirkham

What is a sorting algorithm?

  • Sorting algorithms are precise step-by-step instructions that a computer can follow to efficiently sort data in massive datasets

  • Two common sorting algorithms are:

    • Bubble sort

    • Merge sort

Merge Sort

What is a merge sort?

  • A merge sort is a sorting algorithm that uses the 'divide and conquer' strategy of dividing a dataset into smaller sub-datasets and merging them back together in the correct order

How do you perform a merge sort?

Table detailing three steps for dataset processing: 1. Divide dataset repeatedly in half. 2. Merge pairs of sub-datasets by comparing first values. 3. Repeat step 2 until one dataset.

Example

  • Perform a merge sort on the following dataset

Table showing the merge sort algorithm. The dataset [7, 4, 1, 2, 6, 3, 8, 5] is repeatedly divided, then merged back together by comparing values, resulting in a sorted array.

Examiner Tips and Tricks

In the exam, the divide stage could already be done for you and you would only need to demonstrate the conquer stage!

A Merge Sort in Python

# List of numbers to perform merge sort on

numbers = [7, 4, 1, 2, 6, 3, 8, 5]


# Merge function to merge two sorted lists

def merge(left, right):

    merged = []

    left_index, right_index = 0, 0


    # Merge the two sorted lists

    while left_index < len(left) and right_index < len(right):

        if left[left_index] < right[right_index]:

            merged.append(left[left_index])

            left_index += 1

    else:

        merged.append(right[right_index])

        right_index += 1


    # Append remaining elements from left or right sublist if there are any remaining elements in the left sublist

    while left_index < len(left):

        merged.append(left[left_index])

        left_index += 1


    # If there are any remaining elements in the right sublist

    while right_index < len(right):

        merged.append(right[right_index])

        right_index += 1

   
    return merged


# Merge sort implementation without using a separate function

def merge_sort(arr):


    # Checks to see if the list has 1 or 0 elements, it's already sorted

    if len(arr) <= 1:

        return arr


    # Split the list into two halves

    mid = len(arr) // 2

    left_half = merge_sort(arr[:mid])  # Split and recursively sort left half

    right_half = merge_sort(arr[mid:])  # Split and recursively sort right half


    # Merge the sorted halves

    return merge(left_half, right_half)


# Perform merge sort

sorted_numbers = merge_sort(numbers)

print("Sorted numbers:", sorted_numbers)

Last updated:

You've read 0 of your 10 free revision notes

Unlock more, it's free!

Join the 100,000+ Students that ❤️ Save My Exams

the (exam) results speak for themselves:

Did this page help you?

James Woodhouse

Author: James Woodhouse

Expertise: Computer Science

James graduated from the University of Sunderland with a degree in ICT and Computing education. He has over 14 years of experience both teaching and leading in Computer Science, specialising in teaching GCSE and A-level. James has held various leadership roles, including Head of Computer Science and coordinator positions for Key Stage 3 and Key Stage 4. James has a keen interest in networking security and technologies aimed at preventing security breaches.

Lucy Kirkham

Author: Lucy Kirkham

Expertise: Head of STEM

Lucy has been a passionate Maths teacher for over 12 years, teaching maths across the UK and abroad helping to engage, interest and develop confidence in the subject at all levels.Working as a Head of Department and then Director of Maths, Lucy has advised schools and academy trusts in both Scotland and the East Midlands, where her role was to support and coach teachers to improve Maths teaching for all.