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GCSE Computer Science

Fundamentals of Algorithms

113 questions11 subtopicsAQAOCREdexcelEduqas
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What's covered

Pseudo-code, Flowcharts and Program Code14
Bubble Sort13
Efficiency of Algorithms: Comparing Alternatives12
Trace Tables and Algorithm Walkthroughs12
Merge Sort11
Comparing Linear and Binary Search10
Binary Search9
Linear Search9
Representing Algorithms: Decomposition and Abstraction9
Comparing Bubble Sort and Merge Sort6
Insertion Sort6

Key facts

1

Binary Search

For 1,024 sorted items the worst case is 11 comparisons (floor(log₂ 1024) + 1).

2

Bubble Sort

Bubble sort [3, 1, 2] ascending after one full pass: compare 3,1 swap → [1,3,2]; compare 3,2 swap → [1,2,3]. Already-sorted.

3

Comparing Bubble Sort and Merge Sort

Both bubble sort and merge sort produce the same sorted output for the same input: they differ only in process and efficiency, not correctness.

4

Comparing Linear and Binary Search

For a sorted list of 8 items the worst case for binary search is 4 comparisons: 8, then 4, 2 and finally 1 remaining item (floor(log₂ n) + 1).

5

Efficiency of Algorithms: Comparing Alternatives

An algorithm's efficiency is judged by the time (number of steps) and memory it needs and how these grow with input size; who wrote it is irrelevant.

6

Insertion Sort

Unlike bubble sort, insertion sort does not guarantee the largest item reaches the end after the first pass; the largest item may be inserted last.

7

Linear Search

On average, in a random list of n items with the target present, linear search examines about n/2 items.

8

Merge Sort

Merge sort of [4, 2, 7, 1] first splits into two pairs: [4, 2] and [7, 1].

9

Pseudo-code, Flowcharts and Program Code

An algorithm is a sequence (an ordered set) of steps to complete a task: "a set of instructions" is too vague because order matters. An algorithm is not the same as a program; a program is one implementation of an algorithm.

10

Representing Algorithms: Decomposition and Abstraction

Abstraction means removing or hiding detail that isn't needed to solve the problem at hand, focusing only on the essential information.

Practice questions with answers

A taste of the 113 questions in this topic, answers marked. Sign up to practise the full set with spaced repetition.

1Binary Search

What must be true of a list before a binary search can be used on it?

  • •It must be a very short list
  • •It must be left unsorted
  • ✓It must be sorted into order first
  • •It must contain only numbers
2Bubble Sort

An algorithm repeatedly compares adjacent items and swaps them if out of order. Which sort is it?

  • •Binary search
  • ✓Bubble sort
  • •Linear search
  • •Merge sort
3Comparing Bubble Sort and Merge Sort

Which is the main advantage of bubble sort over merge sort?

  • •It always sorts large data sets more quickly
  • •It is faster on every possible input list
  • ✓It is simpler and uses less extra memory
  • •It uses divide and conquer to split data
4Comparing Linear and Binary Search

Which is faster on large sorted data sets?

  • ✓Binary search is faster than linear search
  • •Both algorithms take the same time
  • •Linear search is faster than binary search
  • •Speed depends only on the input data type
5Efficiency of Algorithms: Comparing Alternatives

Why might one algorithm be preferred over another solving the same problem?

  • ✓It is more efficient
  • •It produces a different result
  • •It requires sorted input data
  • •It uses more memory
6Insertion Sort

Which description matches how insertion sort works?

  • ✓Inserts each item into its correct place in a sorted section
  • •Picks a middle item and splits the list around it
  • •Splits the list into single items then merges them back
  • •Swaps neighbouring items repeatedly until no swaps are made

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