Algorithms | AQA GCSE Computer Science (8525)
Algorithms
- 75 questions
- 5 subtopics
- Paper 1
- Paper 1
Algorithms is examined in Paper 1, Computational thinking and programming skills.
It covers algorithms, decomposition and abstraction, pseudo-code, flowcharts and trace tables, efficiency of algorithms, linear search and binary search and bubble sort and merge sort.
Sample questions from Algorithms
Answer each one closed book first, then open the answer.
-
Algorithms, decomposition and abstraction
Why must each step of an algorithm be unambiguous?
Show the answer
A step with only one meaning gives the same result whoever follows it. A computer cannot guess what a vague instruction was meant to say. -
Algorithms, decomposition and abstraction
Why is abstraction useful in programming?
Show the answer
Abstraction makes a problem simpler to understand and to solve. A program that models only the relevant details is quicker to write and to run. -
Pseudo-code, flowcharts and trace tables
What do a rounded rectangle and a plain rectangle show in a flowchart?
Show the answer
A rounded rectangle, called a terminal, marks the start or the end. A plain rectangle shows a process such as a calculation. -
Pseudo-code, flowcharts and trace tables
An algorithm reads side ← USERINPUT, then area ← side * side, then OUTPUT area. Which line is the processing?
Show the answer
The line area ← side * side is the processing. The first line is the input and the last line is the output. -
Efficiency of algorithms
Why does efficiency matter more as the amount of data grows?
Show the answer
A small difference in steps per item becomes a huge difference over millions of items. An inefficient algorithm can become too slow to use on large data sets. -
Efficiency of algorithms
Why is a search that stops as soon as it finds the item more efficient than one that always checks the whole list?
Show the answer
The early-stopping search skips comparisons that cannot change the result. The search carries out fewer steps on average. -
Linear search and binary search
How does a binary search work?
Show the answer
A binary search compares the target with the middle item of a sorted list. The half that cannot contain the target is discarded. The search repeats on the remaining half until the item is found or none are left. -
Linear search and binary search
What are the advantages of a binary search over a linear search?
Show the answer
A binary search is much faster on large lists, because each comparison halves the items left. The time grows very slowly as the list gets longer.
The 5 subtopics
One subtopic is one session. Work down the list.
| Subtopic | What it covers | Questions |
|---|---|---|
| Algorithms, decomposition and abstraction | What an algorithm is and how it differs from a program, why each step must be unambiguous, decomposition and abstraction with worked examples, and the systematic approach to solving a problem. | 14 |
| Pseudo-code, flowcharts and trace tables | Pseudo-code and why programmers design in it, the flowchart symbols for decisions, inputs, outputs and subroutines, trace tables, visual inspection, and short algorithms to trace by hand. | 16 |
| Efficiency of algorithms | What efficiency means, why steps are counted rather than timed, how growing data changes the picture, two ways to sum 1 to 100 or test 101 for prime, and memory as a second measure. | 13 |
| Linear search and binary search | How linear and binary searches work, why a binary search needs a sorted list, choosing the middle item, traced searches through short lists, worst cases, and when each search is the better choice. | 16 |
| Bubble sort and merge sort | How a bubble sort passes through a list and when it stops, how a merge sort splits and merges, traced sorts of short lists, comparison counts, and the strengths of each. | 16 |
How the guide is worked
Answering a question from memory stores it far better than reading the answer again. The guide runs that as a fixed procedure on one subtopic at a time, about twenty minutes a session.
-
Step 1 · Closed book
Cover the answers. Work through one subtopic and write down what you can. Leave blanks where you have nothing.
-
Step 2 · Open book
Go back to the top. Read each printed answer and write it out in full, including the ones you had right.
-
Step 3 · Closed book again
Same questions, same order, from memory. The gap between pass one and pass three is the session result.
Read the full method, the return schedule and the research behind it.
Nearby topics
AQA GCSE Computer Science Active Recall Guide
Every topic, not just this one. 664 questions with their answers.