OCR A-level Computer Science: Data Structures – Arrays, Lists, Stacks, and Queues

OCR A-Level Computer Science: Data Structures - Arrays, Lists, Stacks, and Queues

This tutorial introduces fundamental data structures: arrays, lists, stacks, and queues. We'll explore their characteristics, how they're implemented, and their applications in various programming scenarios.

1. Arrays

Definition: An array is a collection of elements of the same data type stored in contiguous memory locations.

Characteristics: - Fixed size: Once declared, the size of an array cannot be changed. - Direct access: Elements can be accessed directly using their index, providing constant time access. - Sequential allocation: Elements are stored consecutively in memory.

Example: An array storing 5 integers:

[10, 25, 30, 5, 1]

Applications: - Storing collections of data with predictable sizes. - Implementing simple sorting algorithms. - Creating lookup tables.

2. Lists

Definition: A list is a dynamic data structure that allows elements of varying data types to be stored in a linear sequence.

Characteristics: - Dynamic size: Lists can grow or shrink dynamically as needed. - Sequential access: Elements are accessed by traversing the list from the beginning. - Data type flexibility: Can store different data types.

Example: A list storing a mix of strings and integers:

["Apple", 10, "Banana", 25]

Applications: - Implementing stacks and queues. - Building dynamic collections of data. - Creating linked lists (discussed below).

3. Linked Lists

Definition: A linked list is a dynamic data structure where each element (node) stores a pointer to the next element in the sequence.

Characteristics: - Dynamic size: Linked lists can expand or shrink as needed. - Sequential access: Elements are accessed by traversing the list from the beginning. - Flexible memory allocation: Nodes can be scattered across memory.

Types of Linked Lists: - Singly Linked List: Each node points to the next node only. - Doubly Linked List: Each node points to both the next and previous nodes.

Example: A singly linked list storing integers:

Node 1 (10) -> Node 2 (25) -> Node 3 (30) -> NULL

Applications: - Implementing dynamic stacks and queues. - Creating efficient data structures like hash tables. - Building graph data structures.

4. Stacks

Definition: A stack is a linear data structure that follows the Last-In, First-Out (LIFO) principle.

Characteristics: - LIFO access: The last element added to the stack is the first one to be removed. - Limited access: Elements can be accessed only from the top of the stack.

Operations: - Push: Adds an element to the top of the stack. - Pop: Removes the top element from the stack. - Peek: Returns the value of the top element without removing it.

Example: A stack of plates, where only the top plate can be accessed.

Applications: - Function call management in programming languages. - Undo/Redo functionality in software applications. - Evaluating mathematical expressions.

5. Queues

Definition: A queue is a linear data structure that follows the First-In, First-Out (FIFO) principle.

Characteristics: - FIFO access: The first element added to the queue is the first one to be removed. - Restricted access: Elements can be added to the rear and removed from the front.

Operations: - Enqueue: Adds an element to the rear of the queue. - Dequeue: Removes the element from the front of the queue. - Peek: Returns the value of the front element without removing it.

Example: A queue of people waiting in line at a ticket counter.

Applications: - Handling requests in a server-client system. - Implementing task scheduling in operating systems. - Breadth-first search algorithms in graph theory.

Next Steps:

This tutorial has provided an overview of arrays, lists, stacks, and queues. Explore their implementation details and applications in your chosen programming language. Understanding these fundamental data structures is crucial for building efficient and effective software solutions.