← Computer Science syllabus

EnglandComputer Science

Component 1: Programming and System Development

6 dot points across 6 inquiry questions. Click any dot point for a focused answer with worked past exam questions where available.

How are arrays, records and other static data structures laid out in memory, and when should you choose each one?

Static data structures: one- and multi-dimensional arrays, records (structs), tuples and sets, how they are stored contiguously in memory, address calculation for array elements, and choosing the appropriate structure for a task.
An Eduqas Component 1 answer on static data structures: one- and multi-dimensional arrays, records, tuples and sets, how they are stored contiguously in memory, calculating the address of an array element, and choosing the right structure for a problem.
13 min answer →

What makes an algorithm recursive, and how does Big-O notation measure how efficiently an algorithm scales?

Recursion and algorithmic complexity: the base case and recursive case, how recursion uses the call stack, and Big-O notation for the time and space complexity of algorithms (constant, logarithmic, linear, polynomial and exponential).
An Eduqas Component 1 answer on recursion and complexity: the base case and recursive case, how recursion uses the call stack and can cause stack overflow, and Big-O notation for measuring how an algorithm's time and space scale with input size.
14 min answer →

How do linear and binary search work, how do graph traversals explore data, and how efficient is each?

Searching and traversal algorithms: linear search and binary search with their conditions and efficiency, and the breadth-first and depth-first traversals of trees and graphs.
An Eduqas Component 1 answer on searching: how linear search and binary search work, the precondition that binary search needs sorted data, their time complexities, and how breadth-first and depth-first traversals explore trees and graphs.
14 min answer →

How do bubble, insertion, merge and quick sort work, and which is most efficient?

Sorting algorithms: bubble sort and insertion sort and their quadratic efficiency, merge sort and quick sort and their use of divide and conquer, and comparing sorting algorithms by time complexity and stability.
An Eduqas Component 1 answer on sorting: how bubble and insertion sort work and why they are quadratic, how merge sort and quick sort use divide and conquer to reach n log n, and comparing the algorithms by time complexity.
14 min answer →

How do stacks, queues and linked lists work, and how are they implemented and used?

Dynamic data structures: stacks (LIFO) and queues (FIFO) with their push, pop, enqueue and dequeue operations and pointer management, linear and circular queues, and singly and doubly linked lists with insertion and deletion.
An Eduqas Component 1 answer on stacks, queues and linked lists: LIFO and FIFO behaviour, push, pop, enqueue and dequeue with pointer management, the wrap-around in a circular queue, and inserting and deleting nodes in a linked list.
14 min answer →

How do trees, graphs and hash tables organise data, and what are they used for?

Trees, graphs and hash tables: binary search trees and their traversals (in-order, pre-order, post-order), graphs as adjacency matrices and adjacency lists, and hashing for direct-access tables including collision handling.
An Eduqas Component 1 answer on trees, graphs and hash tables: binary search trees and in-order, pre-order and post-order traversals, representing graphs with an adjacency matrix or adjacency list, and hashing for fast direct access with collision handling.
14 min answer →