Introduction: Part 1 - Understanding Differences - CSU1051

Introduction

Union	Structure
A union is a user-defined data type that allows multiple data types to be stored in the same memory location.	A structure is a user-defined data type that allows a collection of variables to be grouped together under a single name.
In a union, only one member can be accessed at a time. Accessing one member overwrites the other members.	In a structure, all members can be accessed individually.
The size of a union is determined by the largest member in the union.	The size of a structure is determined by the sum of the sizes of all its members.
Unions are typically used when the memory needs to be conserved or when we want to interpret a piece of memory in different ways.	Structures are typically used when we want to group together related data items.
Unions are less commonly used compared to structures.	Structures are more commonly used compared to unions.

Primitive Data Structure	Non-Primitive Data Structure
Primitive data structures are basic data types that can be directly operated upon by the machine.	Non-primitive data structures are derived data types that are created by combining or aggregating primitive data types.
Primitive data structures have a fixed size in memory.	Non-primitive data structures can have a variable size in memory.
Primitive data structures are usually not dynamic, meaning that their size cannot be changed during runtime.	Non-primitive data structures are often dynamic, meaning that their size can be changed during runtime.
Primitive data structures are passed by value, which means that the actual data value is copied to a new location in memory.	Non-primitive data structures are passed by reference, which means that only the memory address of the data is passed to a new location.
Examples of primitive data structures include integers, floating-point numbers, characters, and boolean values.	Examples of non-primitive data structures include arrays, lists, trees, graphs, and objects.

#	Linear Data Structure	Non-Linear Data Structure
1	A linear data structure is a data structure where data elements are arranged sequentially or linearly, and each element has a predecessor and a successor except the first and last elements.	A non-linear data structure is a data structure where data elements are not arranged sequentially or linearly, and each element may have zero, one or many predecessors and successors.
2	Linear data structures are easy to traverse and search, and are suitable for many applications such as arrays, stacks, queues, and linked lists.	Non-linear data structures are more complex to traverse and search, and are suitable for applications such as trees, graphs, and hash tables.
3	Examples of linear data structures include arrays, stacks, queues, and linked lists.	Examples of non-linear data structures include trees, graphs, and hash tables.
4	Linear data structures can be easily represented using arrays or linked lists.	Non-linear data structures require more complex representations such as trees, graphs, or hash tables.
5	Linear data structures have a linear space complexity, which means that the amount of memory used is directly proportional to the number of data elements.	Non-linear data structures can have a non-linear space complexity, which means that the amount of memory used may not be directly proportional to the number of data elements.