In this pdf, I will walk you through a popular Python coding challenge and provide you with the solution code and detailed explanations. The challenge is called 'Remove Duplicates in an Unsorted Linked List', which involves finding and removing duplicates in an unsorted linked list of integers. I will also discuss the concept of run time complexity and how it relates to your solution.
Reverse a Linked List In Place in PythonKal Bartal
Do you want to learn how to reverse a linked list in place in Python? I recently put out a tutorial on this topic, explaining the problem and walking you through the solution and code step-by-step. I also discuss the time and space complexity of this problem, so you can decide if this is the most efficient solution.
A linked list is a linear data structure where elements are linked using pointers. Each element contains a data field and a pointer to the next node. Linked lists allow for dynamic sizes and easy insertion/deletion. They are less cache friendly than arrays due to non-contiguous memory allocation. Common operations include insertion/deletion at the beginning, middle, or end which have time complexities ranging from O(1) to O(n) depending on the operation and presence of additional pointers. Doubly linked lists contain pointers to both the next and previous nodes, enabling traversal in both directions but using more memory.
This document discusses methods of linked lists, including the start, remove, length, and analysis methods. It provides code examples for initializing the start of a linked list and removing a node. It also analyzes the time and memory efficiency of different linked list operations like add, remove, find, and back compared to arrays. Finally, it introduces doubly linked lists, showing how they allow moving forward and backward easily using next and prev pointers in each node.
2 Important Data Structure Interview QuestionsGeekster
The document discusses different data structures and their operations. It summarizes the common operations available for a stack data structure, including push, pop, peek, isEmpty, isFull, size, clear, and search. It then summarizes different types of linked lists, including singly linked lists, doubly linked lists, circular linked lists, doubly circular linked lists, skip lists, self-adjusting lists, and XOR linked lists.
This document summarizes a massive open online course on Udemy about fundamental data structures and algorithms using the C language. The 15-hour course covers key topics like stacks, queues, linked lists, trees, recursion, and analyzing algorithm efficiency. It aims to help students strengthen programming skills and prepare for technical interviews at top companies. The course consists of 14 sections and includes weekly quizzes on the Udemy platform.
The binary search is faster than the sequential search. The complexity of binary search is O(log n) whereas the complexity of a sequential search is O(n). Stacks are used to evaluate algebraic or arithmetic expressions using prefix or postfix notations. Heap sort involves creating a max heap from the array and then replacing the root with the last element and rebuilding the heap for the remaining elements, repeating this process to sort the entire array.
Master of Computer Application (MCA) – Semester 4 MC0080Aravind NC
This document describes several sorting algorithms and asymptotic analysis techniques. It discusses bubble sort, selection sort, insertion sort, shell sort, heap sort, merge sort, and quick sort as sorting algorithms. It then explains asymptotic notation such as Big-O, Big-Omega, and Theta to describe the time complexity of algorithms. Finally, it asks questions about Fibonacci heaps, binomial heaps, Strassen's matrix multiplication algorithm, and formalizing a greedy algorithm.
Reverse a Linked List In Place in PythonKal Bartal
Do you want to learn how to reverse a linked list in place in Python? I recently put out a tutorial on this topic, explaining the problem and walking you through the solution and code step-by-step. I also discuss the time and space complexity of this problem, so you can decide if this is the most efficient solution.
A linked list is a linear data structure where elements are linked using pointers. Each element contains a data field and a pointer to the next node. Linked lists allow for dynamic sizes and easy insertion/deletion. They are less cache friendly than arrays due to non-contiguous memory allocation. Common operations include insertion/deletion at the beginning, middle, or end which have time complexities ranging from O(1) to O(n) depending on the operation and presence of additional pointers. Doubly linked lists contain pointers to both the next and previous nodes, enabling traversal in both directions but using more memory.
This document discusses methods of linked lists, including the start, remove, length, and analysis methods. It provides code examples for initializing the start of a linked list and removing a node. It also analyzes the time and memory efficiency of different linked list operations like add, remove, find, and back compared to arrays. Finally, it introduces doubly linked lists, showing how they allow moving forward and backward easily using next and prev pointers in each node.
2 Important Data Structure Interview QuestionsGeekster
The document discusses different data structures and their operations. It summarizes the common operations available for a stack data structure, including push, pop, peek, isEmpty, isFull, size, clear, and search. It then summarizes different types of linked lists, including singly linked lists, doubly linked lists, circular linked lists, doubly circular linked lists, skip lists, self-adjusting lists, and XOR linked lists.
This document summarizes a massive open online course on Udemy about fundamental data structures and algorithms using the C language. The 15-hour course covers key topics like stacks, queues, linked lists, trees, recursion, and analyzing algorithm efficiency. It aims to help students strengthen programming skills and prepare for technical interviews at top companies. The course consists of 14 sections and includes weekly quizzes on the Udemy platform.
The binary search is faster than the sequential search. The complexity of binary search is O(log n) whereas the complexity of a sequential search is O(n). Stacks are used to evaluate algebraic or arithmetic expressions using prefix or postfix notations. Heap sort involves creating a max heap from the array and then replacing the root with the last element and rebuilding the heap for the remaining elements, repeating this process to sort the entire array.
Master of Computer Application (MCA) – Semester 4 MC0080Aravind NC
This document describes several sorting algorithms and asymptotic analysis techniques. It discusses bubble sort, selection sort, insertion sort, shell sort, heap sort, merge sort, and quick sort as sorting algorithms. It then explains asymptotic notation such as Big-O, Big-Omega, and Theta to describe the time complexity of algorithms. Finally, it asks questions about Fibonacci heaps, binomial heaps, Strassen's matrix multiplication algorithm, and formalizing a greedy algorithm.
Linked allocation vs. Sequential allocation, Operations on Linked Lists realized in terms of Stacks & Queues with boundary conditions, programming errors & rectifications, Cyclic permutation in Stack push & pop, Partial Ordering, Group Activity, Case Study of Topological Sorting; Characterization, explanation, analysis & applications of Topological Sorting Algorithm, Exercise on Inverting a Linked list, Programs for practice.
The document discusses different types of linked lists including singly linked lists, doubly linked lists, and circularly linked lists. Singly linked lists contain nodes that point to the next node in the list, while doubly linked lists contain nodes that point to both the next and previous nodes. Circularly linked lists form a circle with the last node pointing back to the first node. The document provides code examples for common linked list operations like insertion, removal and traversal for each of the linked list types.
Sort Characters in a Python String AlphabeticallyKal Bartal
This tutorial will explore how to solve the problem of sorting characters in a Python string in alphabetical order. We'll learn about manipulating strings in Python and discuss how to compare various sorting algorithms. Finally, we'll put the pieces together to create a solution using the merge sort algorithm. Problem-solving can be quite challenging, but with the right approach, we can find an efficient solution with minimal time and space complexity.
#Python #Strings #Sorting #Algorithms #MergeSort #TimeComplexity #SpaceComplexity #Coding #Recursion
A data structure is a way of storing data in computer memory so that it can be retrieved and manipulated efficiently. There are two main categories of data structures: linear and non-linear. Linear data structures include arrays, stacks, and queues where elements are stored in a linear order. Non-linear structures include trees and graphs where elements are not necessarily in a linear order. Common operations on data structures include traversing, searching, insertion, deletion, sorting, and merging. Algorithms use data structures to process and solve problems in an efficient manner.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
A linked list is a linear data structure where nodes are linked using pointers. Each node contains a data field for storing elements and a pointer field for linking to the next node. There are different types of linked lists including singly linked lists where each node has a pointer to the next node, doubly linked lists where each node has a pointer to both the next and previous nodes, and circular linked lists where the last node is linked to the first node. Common operations on linked lists include insertion, deletion, traversal, searching, and sorting of nodes. Linked lists have advantages over arrays for dynamic memory allocation and efficient insertion/deletion but have disadvantages for random access and memory usage.
This document discusses the design and performance analysis of a concurrent deterministic skiplist data structure on many-core NUMA nodes. It proposes a 1-2-3-4 skiplist that maintains sorted order and supports concurrent insertion, deletion and search in O(logn) time. The paper also evaluates three concurrent hash table implementations and a lock-free queue, comparing their performance to Intel's TBB library. Experiments were run on the Delta supercomputer to analyze scalability and strategies for reducing memory access costs like page faults.
This document discusses the design and performance analysis of a concurrent deterministic skiplist data structure on many-core NUMA nodes. It proposes a 1-2-3-4 skiplist that maintains sorted order and supports concurrent insertion, deletion and search in O(logn) time. The paper also evaluates three concurrent hash table implementations and a lock-free queue, comparing their performance to Intel's TBB library. It focuses on memory management strategies to reduce cache misses and page faults for these concurrent data structures.
This document provides an overview of key concepts for data science in Python, including popular Python packages like NumPy and Pandas. It introduces Python basics like data types, operators, and functions. It then covers NumPy topics such as arrays, slicing, splitting and reshaping arrays. It discusses Pandas Series and DataFrame data structures. Finally, it covers operations on missing data and combining datasets using merge and join functions.
This is a presentation on Linked Lists, one of the most important topics on Data Structures and algorithms. Anyone who is new to DSA or wants to have a theoretical understanding of the same can refer to it :D
This document provides information on circular linked lists including:
- Circular linked lists have the last element point to the first element, allowing traversal of the list to repeat indefinitely.
- Both singly and doubly linked lists can be made circular. Circular lists are useful for applications that require repeated traversal.
- Types of circular lists include singly circular (one link between nodes) and doubly circular (two links between nodes).
- Operations like insertion, deletion, and display can be performed on circular lists similarly to linear lists with some adjustments for the circular nature.
This document provides information on circular linked lists including:
- Circular linked lists have the last node point to the first node, allowing traversal of the list to repeat indefinitely.
- The key difference from linear linked lists is that circular lists have no NULL pointer at the end, instead the last node points to the first.
- Circular lists can be singly or doubly linked. Common operations like insertion, deletion, and traversal are described along with algorithms to implement them in a circular list. Advantages include easy repetition of traversal and no need for separate start and end pointers.
This document discusses different types of data structures, with a focus on linked lists. It defines a linked list as a linear data structure containing nodes where each node has a data element and a link to the next node. The document outlines the basic operations that can be performed on linked lists, including creation, insertion, deletion, traversal, searching, concatenation, and display. It also discusses different types of linked lists like single linked lists, double linked lists, circular linked lists, and circular double linked lists.
The document provides information on linked lists including:
- Linked lists are a linear data structure where each node contains data and a pointer to the next node.
- They allow for dynamic memory allocation and easier insertion/deletion than arrays.
- Common types include singly linked, doubly linked, circular singly/doubly linked lists.
- The document describes creating linked lists in C using structures, and operations like insertion, deletion, searching.
The document compares and contrasts arrays and linked lists. It states that arrays provide fast random access but fixed size, while linked lists have flexible size but slower sequential access. It also discusses different types of linked lists and their memory usage.
This document provides information on linked lists. Some key points:
- A linked list is a dynamic data structure where elements are linked using pointers. Each element contains a data field and a pointer to the next node.
- There are different types of linked lists including singly linked, doubly linked, circular, and circular doubly linked lists.
- Common linked list operations include insertion, deletion, traversal, searching, and sorting. Algorithms for performing these operations on singly linked lists are presented.
- Linked lists can be used to implement other data structures like stacks, where the top element is tracked using a pointer instead of using array indices. Pseudocode for push and pop operations on a linked list implementation of
The document discusses data structures and linked lists. It defines data structures as logical ways of organizing and storing data in computer memory for efficient use. Linked lists are introduced as a linear data structure where elements are connected via pointers and can grow/shrink dynamically. Algorithms for traversing, inserting, and deleting nodes from singly linked lists using both recursion and iteration are provided with pseudocode.
Linked allocation vs. Sequential allocation, Operations on Linked Lists realized in terms of Stacks & Queues with boundary conditions, programming errors & rectifications, Cyclic permutation in Stack push & pop, Partial Ordering, Group Activity, Case Study of Topological Sorting; Characterization, explanation, analysis & applications of Topological Sorting Algorithm, Exercise on Inverting a Linked list, Programs for practice.
The document discusses different types of linked lists including singly linked lists, doubly linked lists, and circularly linked lists. Singly linked lists contain nodes that point to the next node in the list, while doubly linked lists contain nodes that point to both the next and previous nodes. Circularly linked lists form a circle with the last node pointing back to the first node. The document provides code examples for common linked list operations like insertion, removal and traversal for each of the linked list types.
Sort Characters in a Python String AlphabeticallyKal Bartal
This tutorial will explore how to solve the problem of sorting characters in a Python string in alphabetical order. We'll learn about manipulating strings in Python and discuss how to compare various sorting algorithms. Finally, we'll put the pieces together to create a solution using the merge sort algorithm. Problem-solving can be quite challenging, but with the right approach, we can find an efficient solution with minimal time and space complexity.
#Python #Strings #Sorting #Algorithms #MergeSort #TimeComplexity #SpaceComplexity #Coding #Recursion
A data structure is a way of storing data in computer memory so that it can be retrieved and manipulated efficiently. There are two main categories of data structures: linear and non-linear. Linear data structures include arrays, stacks, and queues where elements are stored in a linear order. Non-linear structures include trees and graphs where elements are not necessarily in a linear order. Common operations on data structures include traversing, searching, insertion, deletion, sorting, and merging. Algorithms use data structures to process and solve problems in an efficient manner.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
This document discusses data structures and linked lists. It begins by describing the objectives and limitations of arrays that motivate the use of linked lists. Linked lists overcome the limitations of arrays by storing data non-contiguously in memory using nodes that point to the next node. The document then covers the concepts of singly and doubly linked lists. It discusses the advantages of linked lists over arrays and defines nodes as the basic units of linked lists. Finally, it examines linked list operations like insertion and deletion of nodes and provides an example implementation of linked lists using node objects in Java.
A linked list is a linear data structure where nodes are linked using pointers. Each node contains a data field for storing elements and a pointer field for linking to the next node. There are different types of linked lists including singly linked lists where each node has a pointer to the next node, doubly linked lists where each node has a pointer to both the next and previous nodes, and circular linked lists where the last node is linked to the first node. Common operations on linked lists include insertion, deletion, traversal, searching, and sorting of nodes. Linked lists have advantages over arrays for dynamic memory allocation and efficient insertion/deletion but have disadvantages for random access and memory usage.
This document discusses the design and performance analysis of a concurrent deterministic skiplist data structure on many-core NUMA nodes. It proposes a 1-2-3-4 skiplist that maintains sorted order and supports concurrent insertion, deletion and search in O(logn) time. The paper also evaluates three concurrent hash table implementations and a lock-free queue, comparing their performance to Intel's TBB library. Experiments were run on the Delta supercomputer to analyze scalability and strategies for reducing memory access costs like page faults.
This document discusses the design and performance analysis of a concurrent deterministic skiplist data structure on many-core NUMA nodes. It proposes a 1-2-3-4 skiplist that maintains sorted order and supports concurrent insertion, deletion and search in O(logn) time. The paper also evaluates three concurrent hash table implementations and a lock-free queue, comparing their performance to Intel's TBB library. It focuses on memory management strategies to reduce cache misses and page faults for these concurrent data structures.
This document provides an overview of key concepts for data science in Python, including popular Python packages like NumPy and Pandas. It introduces Python basics like data types, operators, and functions. It then covers NumPy topics such as arrays, slicing, splitting and reshaping arrays. It discusses Pandas Series and DataFrame data structures. Finally, it covers operations on missing data and combining datasets using merge and join functions.
This is a presentation on Linked Lists, one of the most important topics on Data Structures and algorithms. Anyone who is new to DSA or wants to have a theoretical understanding of the same can refer to it :D
This document provides information on circular linked lists including:
- Circular linked lists have the last element point to the first element, allowing traversal of the list to repeat indefinitely.
- Both singly and doubly linked lists can be made circular. Circular lists are useful for applications that require repeated traversal.
- Types of circular lists include singly circular (one link between nodes) and doubly circular (two links between nodes).
- Operations like insertion, deletion, and display can be performed on circular lists similarly to linear lists with some adjustments for the circular nature.
This document provides information on circular linked lists including:
- Circular linked lists have the last node point to the first node, allowing traversal of the list to repeat indefinitely.
- The key difference from linear linked lists is that circular lists have no NULL pointer at the end, instead the last node points to the first.
- Circular lists can be singly or doubly linked. Common operations like insertion, deletion, and traversal are described along with algorithms to implement them in a circular list. Advantages include easy repetition of traversal and no need for separate start and end pointers.
This document discusses different types of data structures, with a focus on linked lists. It defines a linked list as a linear data structure containing nodes where each node has a data element and a link to the next node. The document outlines the basic operations that can be performed on linked lists, including creation, insertion, deletion, traversal, searching, concatenation, and display. It also discusses different types of linked lists like single linked lists, double linked lists, circular linked lists, and circular double linked lists.
The document provides information on linked lists including:
- Linked lists are a linear data structure where each node contains data and a pointer to the next node.
- They allow for dynamic memory allocation and easier insertion/deletion than arrays.
- Common types include singly linked, doubly linked, circular singly/doubly linked lists.
- The document describes creating linked lists in C using structures, and operations like insertion, deletion, searching.
The document compares and contrasts arrays and linked lists. It states that arrays provide fast random access but fixed size, while linked lists have flexible size but slower sequential access. It also discusses different types of linked lists and their memory usage.
This document provides information on linked lists. Some key points:
- A linked list is a dynamic data structure where elements are linked using pointers. Each element contains a data field and a pointer to the next node.
- There are different types of linked lists including singly linked, doubly linked, circular, and circular doubly linked lists.
- Common linked list operations include insertion, deletion, traversal, searching, and sorting. Algorithms for performing these operations on singly linked lists are presented.
- Linked lists can be used to implement other data structures like stacks, where the top element is tracked using a pointer instead of using array indices. Pseudocode for push and pop operations on a linked list implementation of
The document discusses data structures and linked lists. It defines data structures as logical ways of organizing and storing data in computer memory for efficient use. Linked lists are introduced as a linear data structure where elements are connected via pointers and can grow/shrink dynamically. Algorithms for traversing, inserting, and deleting nodes from singly linked lists using both recursion and iteration are provided with pseudocode.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
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This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
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Remove Duplicates in an Unsorted Linked List in Python
1. Python Coding Challenges Python Link List Challenges
Remove Duplicates in an Unsorted Linked
List in Python
written by Kal Bartal February 6, 2023
Click to watch video tutorial on Removing Duplicates in an Unsorted Linked List in Python
Problem:
Given an unsorted linked list of integers, remove any duplicated nodes and return a reference to
the head of the updated linked list.
Constraints:
The linked list should not be sorted in place, and you are not allowed to allocate extra memory.
Your algorithm should have a run time complexity of O(n).
Example:
Input:
[1, 7, 3, 2, 3, 7, 1]
Output:
[1, 7, 3, 2]
Understanding the problem
This problem requires you to find and remove any duplicate elements in an unsorted linked list.
The linked list should not be sorted in place and you are not allowed to allocate extra memory.
Therefore, you will need to come up with an algorithm that scans the linked list, detects any
duplicates, and then removes them from the list.
2. For example, given the following input of [1, 7, 3, 2, 3, 7, 1], the expected output should be [1, 7, 3,
2]. Notice that any duplication of 1 or 7 has been removed, resulting in the unique elements of the
list being returned as the output.
Your algorithm should have a run time complexity of O(n) – which means that it should be able to
work through the list of elements quickly, rapidly detect any duplicates, and then efficiently
remove them.
Solving this problem
To solve this problem, you must have a basic knowledge of linked lists and their associated
operations. You will also need to familiarise yourself with the concept of run time complexity and
how it relates to your solution.
While you are not allowed to allocate extra memory, you will need to understand the logic of how
to utilise the existing memory of a linked list in order to detect duplicates. Also, the algorithm
should be efficient and have a run time complexity of O(n).
Associated Operations on Linked Lists
Linked lists are data structures comprising of a sequence of interconnected nodes. Each node
stores a value, and additionally has a pointer pointing to the node containing the next value. The
nodes in a linked list are internally connected through these pointers.
The associated operations are the set of operations that can be performed on linked lists, given
their structure. These operations can include:
▪ Inserting a node
▪ Removing a node
▪ Finding a node with a given value
▪ Traversing the list to access individual nodes
For example, if you had a linked list of the numbers [1, 2, 3], each node would contain a single
value and a pointer pointing to the following node. This sequence of nodes and their respective
pointers would internally connect them together.
If you wanted to add the number 4 to this list, you could utilise the insert operation and add the
node containing 4 after the node containing 3. This would result in the new linked list of [1, 2, 3,
4].
As you can see, the operations of a linked list are useful in manipulating the order and content of
the individual nodes.
Examples:
▪ Inserting a node
▪ Removing a node
▪ Finding a node with a given value
▪ Traversing the list to access individual nodes
3. Run Time Complexity
▪ Efficiency of an algorithm and duration of task completion
▪ Time to process input (O notation)
▪ Linear time with increasing elements (O(n))
Run time complexity refers to how efficient an algorithm is and how long it takes for the
algorithm to complete its task. It is measured by the amount of time needed for the algorithm to
process its input, and is commonly represented in the Big-O notation.
For instance, if an algorithm takes 10 seconds to process 10 elements, it would have a run time
complexity of O(10), meaning it takes 10 seconds to process 10 elements. On the other hand, an
algorithm with a run time complexity of O(n) would take linear time as the amount of elements
increase, i.e. if an algorithm takes 10 seconds to process 10 elements, it would take 20 seconds
to process 20 elements.
For this particular problem, you are expected to develop an algorithm with a run time complexity
of O(n), or linear time. This means that no matter how many elements are in the linked list, the
algorithm should take linear time to detect duplicates and remove them.
Detecting Duplicates in a Linked List
▪ Track existing memory of the linked list
▪ Compare each node’s value to the values of the nodes that follow it
▪ Modify pointer of node before duplicate to remove it from the list
The logic of utilising the existing memory of a linked list to detect duplicates is to keep track of
each node’s value and pointer. As you traverse the list, compare each node’s value to the values
of the nodes that come after it. If a duplicate is found, you can remove it by modifying the node’s
pointer before it.
For example, if the linked list you are traversing contains the elements [1, 7, 4, 5, 4], then you
would go through each node and compare the subsequent nodes to the node you are currently
at. In this case, when you reach the node containing the number 4, you would compare the next
node’s value to see if it is a duplicate. In this case, the subsequent node does contain the same
value of 4 so it can be identified as a duplicate.
Now, you can simply modify the pointer of the node containing the number 4 so that it points to
the node containing the number 5, instead of the duplicate node containing 4. This therefore
removes the duplicate from the linked list, leaving you with [1, 7, 4, 5] as the output.
Examples:
▪ If list is [1, 7, 4, 5, 4], compare the 4th node’s value to the subsequent one (the ‘4’)
▪ Modify pointer of 4th node so it points to the 5th instead of the duplicate node
Removing Duplicates in an Unsorted Linked List in
Python
Here is a Python solution to this problem which has a run time complexity of O(n)
4. # Definition for singly-linked list
class Node:
def __init__(self, val=0, next=None):
self.val = val
self.next = next
# Function to remove duplicates
def removeDuplicates(head):
# Check if the linked list is empty
if head is None:
return head
# Set the current node to the head of the list
current_node = head
# Loop through the linked list and compare each node to the subsequent node
while current_node is not None:
# Set the subsequent node to the node after the current node
subsequent_node = current_node.next
# Store the reference of the current node
previous_node = current_node
# Loop through subsequent nodes and compare the value to the current node
while subsequent_node is not None:
# If a duplicate is found
if current_node.val == subsequent_node.val:
# Store the reference of the subsequent node
temp = subsequent_node
# Point the previous node to the node after the duplicate
previous_node.next = temp.next
# Move the subsequent node one position forward
subsequent_node = temp.next
# If no duplicate is found, move the previous and subsequent node one position forward
else:
previous_node = subsequent_node
subsequent_node = subsequent_node.next
# Set the current node to the node one position ahead
current_node = current_node.next
# Return the reference to the head of the updated linked list
return head
We define a simple Node class which contains a value and a reference to the subsequent node.
We then create a function to remove duplicates which takes in the head of the linked list as a
parameter.
First, we check if the linked list is empty, and if it is, return the head.
5. We then set the current node to the head of the list and begin looping through the linked list. We
set the subsequent node to the node after the current node, and also store the reference of the
current node as the previous node.
Once we have these references set, we begin looping through the subsequent nodes and
compare their values to the value of the current node.
If we find a duplicate, we store the reference of the subsequent node, remove the duplicate by
modifying the pointer of the current node, and then move the subsequent node one position
forward.
If no duplicate is found, we move the previous and subsequent node one position forward and
start comparing the next node.
Once the comparison is done, we set the current node to the node one position ahead and begin
looping through the list again until we reach the end.
Finally, we return the reference to the head of the updated linked list.
Analysis of Time Complexity
▪ O(n): Takes linear time to complete task
▪ Double loop: Look at nodes/subsequent nodes, inner loop runs n times
▪ Checks for duplicates, removes/moves subsequent node
The time complexity of this code is O(n). This means that it takes linear time to complete the
task – no matter how many elements there are in the linked list, the algorithm will take the same
amount of time to complete its task.
Specifically, this algorithm uses a double loop iterating through the linked list in order to detect
any duplicates and then remove them. The outer loop looks at each node in the linked list, and
the inner loop looks at the subsequent nodes for comparisons.
The inner loop then runs for a total of n times, where n is the number of elements in the linked
list. During each iteration, the algorithm checks if there is a duplicate and either removes it or
moves the subsequent node forward.
Therefore, the time complexity of this algorithm is O(n). The total number of operations it takes
to complete the task depends on the number of elements in the linked list, and increases linearly
as the number of elements increases.
O(1) Space Complexity
▪ Space complexity is O(1)
▪ No extra memory needed
▪ Memory consumption is constant
The space complexity of this code is O(1). This means that the algorithm requires a fixed amount
of memory in order to complete its task.
Specifically, this algorithm does not allocate any extra memory for it to execute. All it does is to
iterate through the existing linked list and modify the references of the nodes to either detect
6. duplicates or delete them. This means that the total memory consumption is constant regardless
of the number of elements in the list.
Therefore, the space complexity of this algorithm is O(1).
Final Thoughts
Requirements for Removing Duplicates in a Linked List:
▪ Understand linked list structure
▪ Concept of run time complexity
▪ Algorithm efficiency
This challenge requires you to come up with an algorithm to remove duplicates in an unsorted
linked list while keeping run time complexity and memory consumption to a minimum. It is a
great problem to work on to get a deeper understanding of linked lists, the concept of run time
complexity, and the importance of algorithm efficiency.
Also, you have to think carefully about how to structure your code and how to utilise the existing
memory of a linked list in order to detect duplicates. It is certainly a fun and challenging problem
that can help you to hone your coding skills.