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Learning JavaScript Data Structures and Algorithms

You're reading from   Learning JavaScript Data Structures and Algorithms Enhance your problem-solving skills in JavaScript and TypeScript

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Product type Paperback
Published in Jul 2026
Last Updated in Sep 2025
Publisher Packt
ISBN-13 9781836205395
Length 615 pages
Edition 4th Edition
Languages
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Author (1):
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Loiane Groner Loiane Groner
Author Profile Icon Loiane Groner
Loiane Groner
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Table of Contents (9) Chapters Close

Learning JavaScript Data Structures and Algorithms, Fourth Edition: Enhance your problem-solving skills in JavaScript and TypeScript
1 Introducing Data Structures and Algorithms in JavaScript FREE CHAPTER 2 Big O notation 3 Arrays 4 Stacks 5 Queues and Deques 6 Linked Lists 7 Sets 8 Dictionaries and Hashes

Reviewing the efficiency of the linked lists

Let's review the efficiency of each method by review the Big O notation in terms of time of execution:

Method Singly Doubly Circular Explanation
append O(n) O(1) O(n) In singly and circular lists, we must traverse to the end to append. Doubly lists have a tail reference for constant time append.
prepend O(1) O(1) O(n) All lists can add a new node as the head directly. However, in circular lists, we must update the last node's next pointer to the new head.
insert O(n) O(n) O(n) For all types, we need to traverse to the position to insert.
removeAt O(n) O(n) O(n) Similar to insertion, traversal to the position is required. Doubly lists have an optimization when removing the tail ( O(1) ), but this is less common than removing from an arbitrary position.
remove O(n) O(n) O(n) Searching for the data takes O(n) in all cases, then removal itself is either O(1) (if the node is found at the head) or O(n) (traversing to the node...
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