Lesson T1.2.3

T1.2.3 Comparing the utility of algorithms Quiz: KS3 Computing, Unit 1

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

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Lesson T1.2.3, Comparing the utility of algorithms: 20 multiple choice questions for the KS3 Computing (National Curriculum), Unit 1: Computational thinking and algorithms, written with Revision Ninja.

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The 20 questions

  1. Why compare two algorithms that solve the same problem?

    • To check that they both use the same number of lines
    • To decide which one has the most attractive name
    • To make sure the programmer can avoid writing any code
    • To judge which one is faster or uses fewer steps

  2. Which measure is commonly used to judge an algorithm?

    • The number of steps or comparisons it needs
    • The size of the font used in the code
    • The colour of the screen it is shown on
    • The name of the person who wrote it

  3. Binary search and linear search both search a sorted list of 1000 items. Which needs fewer checks in the worst case?

    • Binary search
    • Linear search
    • Neither can search a sorted list
    • They always need exactly the same number

  4. Which sort makes the fewest swaps in general?

    • Neither sort ever changes the order of items
    • Both always make exactly the same number of swaps
    • Selection sort, which makes at most one swap per pass
    • Bubble sort, which swaps every neighbouring pair

  5. Algorithm A takes 5 seconds and algorithm B takes 2 seconds to do the same task. Which is more efficient?

    • Algorithm B
    • They are equally efficient
    • Neither can be judged from times
    • Algorithm A

  6. Two algorithms always give the correct answer. Why might one still be preferred?

    • It uses less time or less memory
    • It uses more lines of code to look impressive
    • It has a longer name in the programming book
    • It needs a bigger screen to display its output

  7. Which of these is NOT a reason to choose one algorithm over another?

    • How much memory it needs
    • The colour of the screen it is displayed on
    • How reliably it gives the right answer
    • How quickly it finishes

  8. Linear search on 50 items takes about 25 checks on average. About how many checks does binary search need on 50 sorted items?

    • About 6
    • About 25
    • About 1
    • About 50

  9. Why is worst-case behaviour used when comparing algorithms?

    • It shows the most steps the algorithm could possibly need
    • It shows the fewest steps the algorithm could ever need
    • It shows how many people have used the algorithm
    • It shows how long the programmer spent writing it

  10. What does 'the utility of an algorithm' mean?

    • How often it is printed in textbooks
    • How many pages of documentation it has
    • How many different programming languages it can be written in
    • How useful it is for a particular problem, judged with evidence

  11. One sort uses 10 comparisons to sort 5 items and another uses 4. Which uses fewer comparisons?

    • The one that used 4 comparisons
    • The one that used 10 comparisons
    • Neither can be counted
    • Both used the same number of comparisons

  12. Algorithm X only works on sorted lists. Algorithm Y works on any list. For an unsorted list used once, which is more useful?

    • Algorithm X
    • Neither is useful for lists
    • Both are equally useful
    • Algorithm Y

  13. Why should logical reasoning be used to compare algorithms?

    • To avoid testing the algorithms on real data
    • To prove that every algorithm is equally good
    • To make the algorithms look more complicated to others
    • To justify a choice with clear evidence rather than guesswork

  14. Binary search runs on the sorted list [2, 4, 6, 8, 10]. Which item is checked first?

    • 6
    • 8
    • 4
    • 2

  15. Algorithm P needs 3 times n steps and algorithm Q needs n times n steps. For n equal to 10, which is quicker?

    • Algorithm P, with 30 steps against 100 steps
    • Neither can finish for n equal to 10
    • Algorithm Q, with 30 steps against 100 steps
    • Both need exactly 100 steps

  16. Why would bubble sort be a poor choice for a list of a million items?

    • It cannot sort any list containing more than five items
    • It makes very many comparisons and swaps, so it becomes very slow
    • It can only sort lists that contain words
    • It always changes the values stored in the list

  17. An algorithm is correct but takes a long time. How is it best described?

    • Incorrect and therefore useless
    • Efficient but unable to finish
    • Correct but less efficient
    • Fast but always wrong

  18. Insertion sort is run on a list that is already sorted. How many swaps does it need?

    • About half of the items
    • None
    • One for each item in the list
    • All of the items

  19. An app searches a large sorted database many times. How should a developer choose between two algorithms?

    • Pick whichever algorithm uses the most lines of code, since it looks more thorough
    • Compare their steps on realistic data sizes and pick the faster one
    • Pick at random so that the choice is fair to every algorithm being considered
    • Pick whichever algorithm was written first, since older methods are more reliable

  20. Which method is generally best for finding an item in a sorted list of a million items?

    • Checking from a random starting point
    • Binary search
    • Linear search
    • Reading the list backwards by hand

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