UNIT 1

Data Structure

• it is considered as a backbone of a simple or complex system (Alheraki, 2024)

• it is also a part of the fundamentals of any programming language as it enables us to store, organize and manipulate efficiently

• it also affects the speed and memory of the software that we develop.

Primitive Data Types

are considered most basic forms (building blocks) data that cannot be broken down further

Non-Primitive Data Types

are advanced in a way that is used to handle more complex programming tasks.

Primitive Data Types

These data types are the most basic data due to its structure. They are the building blocks used to help programmer understand the fundamentals of a programming language and produce a complex system. It is also used for assigning values for data manipulation.

Integers

It represents whole numbers with no fractional or decimal point from negative infinity to infinity.

Float

It stands for “floating point number”. It represent numbers with fractional parts and precise decimal point.

String

It is a sequence of characters that is used to represent text. It is one of the most common used data structure in programming for storing or holding a value. It can be declared using letters, numbers, symbols and whitespace.

Boolean

It is often referred to as bool, it is used for performing logical operations and control flow decisions such as “true” or “false”.

Non-Primitive Data Types

These structures are far more complex data built using primitive data types as foundation. This allow programmers to organize and manipulate larger and complicated sets of data efficiently. Unlike Primitive Data Types, it has two sub-categories which are Linear and Non-Linear Data Structures.

Linear Data Structures

It refers to the data elements which are arranged sequentially or “linearly”, where each element is connected to its previous and next adjacent elements. Data can be accessed in order one after another following a straight-line arrangement.

Sequential Access Pattern

access data in order

Single-Level Structure

each element is connected to one another’s predecessor and successor except for first and last.

Memory Utilization

Often use memory in a contiguous manner, which may be efficient for access but may also cause wasted space if not managed properly

Array

It is a data structure that stores a fixed-size sequential collection of elements of the same type. It is one of the simplest and most widely used data structures in computer programming. The elements in here are stored in contiguous memory locations and can be accessed randomly using indices.

Stack

It is a linear data structure that follows a particular order in which operations are performed. The order may be LIFO (Last In First Out) or FILO (First In Last Out). In a stack, the most recently added element is the first one to be removed

Queue

It is a collection of elements that follows the principle of First in, First out (FIFO). The first element that will be added to the queue will be the first one to be removed from the sequence. This ensures a fair system where everyone gets served in the sequence they arrived.

Linked-List

It is a data structure in programming consisting of a sequence of elements called nodes that contains data and a reference (pointer) to the next node. It is most commonly used for moving data in the middle efficiently.

Tuple

It is a data structure with a fixed-size collection of heterogeneous values. Unlike array and linked-list, it can handle store data with different data types. Once an array and ____ is created, its sizes cannot be changed.

Dictionary

It is an unordered collection of key-value pairs. Each key is unique and it maps to a value, which can be accessed, modified, or deleted. This makes maps particularly useful for tasks that require efficient searching, such as implementing lookup tables, caching, and storing configurations

Non-Linear Data Structures

These are where data elements are not arranged in sequential manner they are arranged in a hierarchical or interconnected fashion, allowing for more complex relationships between the elements.

Trees and Graph

The most common non-linear data structures are

Trees

hierarchical data structures with a root node and child nodes. Each node can have multiple child nodes, forming a tree-like structure.

Graphs

non-linear data structures that consist of nodes (vertices) and edges connecting these nodes.

Hash Tables

data structures that use a hash function to map keys to array indices, allowing efficient key-value pair lookups.

Algorithm

It is a step-by-step process that you follow to solve a problem or complete a task. An efficient algorithm helps lessen space and time consumed in completing a task. In accomplishing a conflict, a user can generate multiple algorithm to process it, however it is crucial to ensure to use the most fitting one,

Algorithm Analysis

The best algorithm has a fine balance between time taken and memory consumed. It is tested this, to understand it better and search for improvements

Sorting Algorithms

It is used to arrange data in a particular/specific order (ascending or descending).

Examples include Quick Sort, Merge Sort, and Bubble Sort.

Search Algorithms

It is used to find specific data within a structure.

Examples include Binary Search and Linear Search that are applicable for linear data structures.

Graph Algorithms

It is used to solve problems related to graph theory, such as finding the shortest path or detecting cycles.

Examples include Depth-First Search (DFS), Breadth-First Search (BFS), and Dijkstra’s Algorithm.