What you will learn

How the prev pointer collapses several O(N) singly-list operations down to O(1)

Bidirectional traversal: walk head to tail through next, or tail to head through prev

The reversal pattern in both flavours: whole list and any inner segment

The reversal subproblem pattern: apply k-node reversals across consecutive groups

The two pointer pattern, which a singly linked list cannot support

The reorder pattern: split nodes by one rule, merge or concatenate by another

Why this course

Most engineers learn the doubly linked list as "a singly linked list with one extra pointer" and stop there. The shortcut hides what that extra pointer actually buys you: O(1) deletion of a given node, O(1) insertion before any node, O(1) access to the previous element, and a real two-pointer traversal that singly linked lists cannot do at all.

This course rebuilds the data structure from the prev pointer up, then walks you through the four patterns that cover almost every doubly linked list interview question. You finish by implementing a complete DoublyLinkedList class with prepend, append, insert, remove, and search, the same shape as Java's LinkedList and C++'s std::list.

Requirements

The course assumes you have already worked through singly linked lists or have equivalent experience with pointer-based structures.

Comfort writing functions and reading reference or pointer manipulation in any language.
Familiarity with Big-O notation (O(1), O(N)).
Singly linked list fundamentals: head, tail, traversal, and basic insert and delete.

Overview

A doubly linked list is what most languages give you when they expose a generic "linked list" type. Java's LinkedList, C++'s std::list, .NET's LinkedList<T>, and Python's collections.deque are all doubly linked underneath. The reason is that one extra prev pointer per node unlocks O(1) insertion and deletion anywhere in the list, O(1) access to the tail through head.prev, and bidirectional traversal. That same combination is the reason LRU caches, browser history, undo and redo stacks, text editor gap buffers, and music player playlists all sit on top of a doubly linked list.

Representation of a doubly linked list

This course covers both halves of the topic: how the prev pointer reshapes the cost of every operation, and how to recognise which of the four patterns a given problem fits into.

Fundamentals

The course opens with a frank look at what singly linked lists do badly. Deleting a given node, deleting the last node, inserting before a given node, all run in O(N) because the only way to reach the predecessor is to scan from the head. You then see how adding a single prev reference per node makes every one of those operations O(1), which is the whole motivation for the data structure.

From there the course teaches the operation matrix in the order the curriculum follows: defining the node with val, next, and prev; mapping the list structure (head with null prev, tail with null next); bidirectional traversal through next and prev; the five insertion variants (at beginning, at end, after a given node, before a given node, at a position); and the seven deletion variants (first, last, by data, after a node, before a node, given node, at a position). Each operation is taught with its exact complexity, so by the end of the fundamentals you can derive any composite operation's cost without memorising it.

The fundamentals close with a survey of how those three primitives, traversal, insertion, and deletion, compose into everything else the patterns will ask you to do.

Problem solving

After the fundamentals the rest of the course is patterns. Almost every doubly linked list problem you will see in an interview reduces to one of four templates, and once you can recognise the template the solution follows.

The 4 doubly linked list patterns you'll master

Reversal

Swap every node's next and prev pointers in a single pass, running in O(N) time and O(1) space. The same algorithm with start and end parameters handles any inner segment. Reverse A List, Reverse First K Nodes, Reverse Last K Nodes, Reverse The Given Segment.

Reversal subproblem

Decompose the problem into roughly N/k reversals applied across consecutive k-node groups, each handled by the segment reversal primitive. Pairwise Swap, Reverse K Segments, Reverse Increasing Groups, Reverse Alternate Segments.

Two pointers

Walk one pointer forward from head and another backward from tail until they meet, the bidirectional scan a singly linked list cannot do, in O(N) time and O(1) space. Palindrome Number, Two Sum, Duplicate Aware Two Sum, Approximate Three Sum.

Reorder

Split the list by a rule f1 into multiple sublists, then merge or concatenate them with a rule f2, both passes rewiring prev pointers in O(N) time. Relocate Node, Parity Order, Value Partition, Shuffle List.

Each pattern is taught in three layers. An Understanding lesson explains the technique on a problem where the pattern is obvious. An Identifying lesson teaches the markers in a problem statement that flag the template: a request for in-place reordering, a palindrome check, a constraint that rules out forward-only traversal. Then four problems give you progressively harder applications. The course closes with a design capstone where you implement a complete DoublyLinkedList class with size, empty, prepend, append, insert, remove, and search, the structure behind half the data containers in your standard library.

How this course is different

Most doubly linked list material treats the topic as a footnote on singly linked lists. This course gives it the attention the structure deserves.

Most DSA resources

This course

✗Treat the doubly linked list as "singly plus one extra pointer" and skip to problems.

✓Walks through every operation a singly list does badly and shows where prev earns its keep.

✗Skip the operation matrix that shows exactly where the prev pointer changes complexity.

✓Teaches all twelve operation variants (5 insert, 7 delete) with their exact O(1) or O(N) cost.

✗Teach reversal as a special case without showing how the segment variant generalises.

✓Treats reversal as one algorithm with two flavours (whole list and segment) feeding the subproblem pattern.

✗Cover two pointers as a generic trick without explaining why it fails on singly lists.

✓Shows two pointers from first principles, why bidirectional walking only works once you have prev.

✗Stop at problems and never have you implement the structure end to end.

✓Ends with a full DoublyLinkedList design capstone matching the shape of Java's LinkedList.

Who this course is for

The course suits anyone who has touched a linked list before and wants to understand the doubly linked variant properly.

Engineers who finished a singly linked list course and want to extend the mental model with prev.
Bootcamp graduates who can write an LRU cache from a tutorial but cannot explain why a doubly linked list is the right backbone.
Working developers who reach for Java LinkedList, C++ std::list, or Python deque without knowing the structure underneath.
Engineers preparing for FAANG and Big Tech interviews where segment-reversal and palindrome-style linked list problems show up regularly.
Returning engineers who learned linked lists in a CS class and want a clean, problem-driven refresher.
Anyone who wants the data structure behind LRU caches, browser history, undo stacks, and text editor gap buffers.

Continue your DSA journey

Doubly linked lists sit at the intersection of pointer-based structures, queue-like containers, and a few cache-flavoured system design problems. After this course these are the natural next steps.

Array: The clearest contrast in all of data structures: contiguous indexed memory versus pointer-chased nodes. Understanding both is what lets you justify which one to reach for in a real interview answer.
Singly linked list: The natural prerequisite if you have not already taken it. Most patterns in this course (reversal, reversal subproblem, reorder) are taught first on the singly variant and then adapted with prev rewiring here. Take this course before you tackle two pointers on a doubly linked list.
Hash table: The LRU cache, one of the most asked system design and coding interview questions, is a hash table whose values are pointers into a doubly linked list. You need both structures to implement it. This course gives you the linked list half.
Stack: Browser back and forward, undo and redo, both rely on either a pair of stacks or a doubly linked list with a cursor. The stack course teaches the alternative; this course teaches the structure that lets you walk both directions.
Queue: Python's deque and Java's ArrayDeque are deques implemented over a doubly linked list (or a ring buffer). The O(1) push and pop at both ends you saw in this course is exactly what makes a deque possible.
Recursion: Linked list reversal, the centrepiece pattern of this course, has an elegant recursive form alongside the iterative one taught here. Recursion is also where you build the call stack intuition that makes pointer rewiring easier to reason about.

Frequently asked questions

Code examples use Python for readability, but every concept (the prev pointer, bidirectional traversal, segment reversal) is language-agnostic. The same algorithms map directly onto a Java LinkedList, a C++ std::list, or a custom struct in Go or Rust.

Yes. The first section is a deliberate bridge from singly to doubly: it shows exactly which singly-list operations cost O(N) and how adding a prev pointer collapses them to O(1). If you can implement a singly linked list, you have the right starting point.

There are around 25 lessons and 33 problems across 4 patterns plus a design capstone. Most learners finish the lessons in 8 to 12 hours and need another 12 to 20 hours to solve the problems, depending on how comfortable they already are with linked lists.

The patterns covered here (reversal, segment reversal, two pointers, reorder) account for almost every doubly linked list question that shows up in onsite loops. The design capstone is also the linked-list half of the classic LRU cache problem, which appears regularly at top tech companies.

LeetCode shows you problems one at a time with no taxonomy. This course teaches the four templates first, then drills four problems per pattern so you build template recognition. You learn the segment reversal primitive once, then see it reused across pairwise swap, k-segment reversal, increasing-group reversal, and alternate-segment reversal.

To unlink a node you have to update its predecessor's next pointer. On a singly linked list there is no way to reach the predecessor except by scanning from the head, which takes O(N). A doubly linked list stores the predecessor directly in node.prev, so you read it in O(1) and rewire the surrounding prev and next pointers without any traversal at all.

A singly linked list node holds val and next. A doubly linked list node holds val, next, and prev. The extra pointer doubles the per-node memory overhead, but in return you get O(1) delete-given-node, O(1) delete-last (if you keep a tail reference), O(1) insert-before-a-node, and bidirectional traversal. Most language standard libraries (Java LinkedList, C++ std::list, .NET LinkedList) pick the doubly variant precisely for those wins.

Yes. Once you finish all lessons and the design capstone, codeintuition issues a shareable certificate you can post to LinkedIn or attach to a job application.

Start Learning →

1. Array

2. Singly Linked List

3. Doubly Linked List

4. Hash Table

5. Stack

6. Queue

7. Binary Tree

8. Binary Search Tree

9. Heap

10. Graph

Doubly Linked List