Data Structure Deletion

Introduction

Data structures are the way data is organized and stored in memory, so as to provide access to its members in an efficient manner. Though insert, search are important operations deletion is also required. Deletion of the Data Structure Deletion entails removing an element from the existing data structure.

We delete in real life, too. Whether it be a contact on your phone, a file on the computer or a student record within a database. Similarly, computer programs need to remove data when it has served its purpose.

Deletion is very crucial for exams, interviews and building real world applications. Data Structures Delete operations are done differently on data structures. In this article Data Structure Deletion is going to be described in a very easy way for beginners.

What is deletion in data structure?

Deletion in data structures is the process of removing a node from a structure, like an array, linked list or tree.

After deletion:

There should be NO data.

Memory may be freed

The middle elements still need to be kept in order

Deletion should be performed cautiously to reduce:

Data loss

Memory errors

Program crashes

Why Deletion is Important?

• Deletion is crucial for many reasons:
• Eliminates wasted space to save memory and make room for new memories.
• Keeps data structures updated
• Improves performance
• Prevents data duplication
• It is prompted in databases and files systems.

Without deletion, data structures would simply continue to grow and be a waste or excess of memory.

Deletion in Array

• An array will store its elements in contiguous memory locations.
• How array deletion works:
• First find element to delete:
• Remove that element
• Move all the rest of the elements up to fill up that gap.
• Reduce the size of the array
• Example:
• If an array contains:
• 10, 20, 30, 40
• Deleting 20 will result in:
• 10, 30, 40
• Important points:
• Deletion is more expensive, since a shift (move) is needed.
• Not efficient for large arrays
• Time complexity is high

Deletion in Linked List

A linked list holds data elements in nodes which are joined by reference fields.

Types of linked lists:

Singly linked list

Doubly linked list

Circular linked list

Deletion cases:

• Leaf node deletion
• Node with one child
• Node with two children

In two-child case, the inorder successor is used

Advantages:

No shifting required

Efficient deletion

Better than arrays

Deletion in Stack

• Stack works on LIFO (Last In First Out) principle.
• Deletion in stack is called:
• Pop operation
• How pop works:
• Removes the top element
• Decreases the stack pointer
• Important rules:
• No other element is there to pop
• If the stack is empty, underflow occurs.
• Deleting a stack is easy and takes no time at all.

Deletion in Queue

• Queue works on the principle of FIFO (Fist in First Out).
• Deletion in queue is called:
• Dequeue operation
• How dequeue works:
• Removes element from the front
• Front pointer moves forward
• Conditions:
• If queue is empty → underflow
• Deletion happens only from front

Deletion in Binary Tree

• Deletion in trees is asymmetric.
• Steps involved:
• Find the node to be deleted
• Check number of child nodes
• Possible cases:
• Node with no child
• Node with one child
• Node with two children
• Deletion must maintain tree structure.

BST Deletion (with an Investigation of H1 in Appendix)

• BST follows a specific order:
• Left subtree Root
• Deletion cases:
• Leaf node deletion
• Node with one child
• Node with two children
• In case of two children, we use inorder successor.

Common Problems in Deletion

• Some of the common problems which occurs while trying to delete:
• Memory leakage
• Dangling pointers
• Incorrect links
• Data inconsistency
• To prevent these issues, deletion logic must be right.

Advantages of Deletion Operation

• Reduces memory usage
• Keeps data relevant
• Improves efficiency
• Supports dynamic data handling
• Deletion to keep the data structures clean and optimized.

Disadvantages of Deletion Operation

• Complex in some structures
• Time-consuming in arrays
• Error-prone if not handled properly
• Despite challenges, deletion is unavoidable.

Time Complexity of Deletion

• Time complexity, however depends on the data structure:
• Array: High
• Linked List: Medium
• Stack and Queue: Low
• Tree: Depends on structure
• It’s all about complexity when it comes to understanding for exams.

Real-Time Applications of Deletion

• Database record removal
• File systems
• Undo operations
• Memory management
• Task scheduling
• System efficiency is heavily dependent on deletion.

Conclusion

Generation of data structure Deletion is an essential operation in computer science. It enables programs to eliminate unnecessary and outdated data and use memory optimally. Deletion is managed differently in various data-structures, and it has its own pros & cons.