Eduqas A-Level Computer Science A500QS
Data Structures: Arrays, Records and Hash Tables
Stacks, Queues, Linked Lists and Trees
Boolean Logic and Simplification
Algorithms, Pseudo-Code and Programming Constructs
Variables, Scope, Parameters and Identifiers
Recursion and Modular Programming
Sorting Algorithms
Searching and Shortest-Path Algorithms
Big O Notation and Algorithm Efficiency
Validation, Verification and Testing
Data Compression
Programming Paradigms and Computer Languages
Systems Analysis, Maintenance and Documentation
System Design and Human-Computer Interaction
Software Engineering Tools and Translators
Computing, Society and the Law
Computer Architecture, the Processor and Assembly Language
Input, Output and Secondary Storage
Networks, Protocols and the Internet
Data Transmission and Network Performance
Number Systems and Binary Arithmetic
Data Types, Characters and Floating Point
Files, Records and File Organisation
Databases, Normalisation and Entity Modelling
SQL, Big Data and Distributed Systems
The Operating System and Its Modes
Interrupts, Memory Management and Scheduling
Types of Software System
Data Security, Cryptography and Attack
Big O Notation and Algorithm Efficiency
What Big O notation measures
- 3 things to know
- Component 1
Overview
Time complexity, space complexity and worst case of an algorithm.
What you need to know
Answer each one before you reveal it.
What does the letter n stand for in an expression such as O(n)?
Why does Big O ignore constant factors?
Questions from this subtopic
Each one with the model answer underneath.
- 1
What does Big O notation describe?
Model answer
Big O notation describes how the resource an algorithm needs grows as the size of its input grows. The measure is the shape of that growth, not an exact count of operations.
- 2
What does the letter n stand for in an expression such as O(n)?
Model answer
The letter n stands for the size of the input, such as the number of items in a list. Complexity is always stated in terms of that size.
- 3
Why does Big O ignore constant factors?
Model answer
A constant factor does not change the shape of the growth. An algorithm taking 3n steps and one taking 100n steps are both written O(n).
- 4
Why are lower-order terms dropped from a Big O expression?
Model answer
The highest-order term dominates the total once n is large. An algorithm taking n² + 5n + 20 steps is written O(n²).
- 5
Define time complexity.
Model answer
Time complexity is the way the number of operations an algorithm performs grows with the size of its input.
- 6
Define space complexity.
Model answer
Space complexity is the way the extra memory an algorithm needs grows with the size of its input.
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