LeetCode #641 — MEDIUM

Design Circular Deque

Move from brute-force thinking to an efficient approach using array strategy.

Solve on LeetCode
The Problem

Problem Statement

Design your implementation of the circular double-ended queue (deque).

Implement the MyCircularDeque class:

  • MyCircularDeque(int k) Initializes the deque with a maximum size of k.
  • boolean insertFront() Adds an item at the front of Deque. Returns true if the operation is successful, or false otherwise.
  • boolean insertLast() Adds an item at the rear of Deque. Returns true if the operation is successful, or false otherwise.
  • boolean deleteFront() Deletes an item from the front of Deque. Returns true if the operation is successful, or false otherwise.
  • boolean deleteLast() Deletes an item from the rear of Deque. Returns true if the operation is successful, or false otherwise.
  • int getFront() Returns the front item from the Deque. Returns -1 if the deque is empty.
  • int getRear() Returns the last item from Deque. Returns -1 if the deque is empty.
  • boolean isEmpty() Returns true if the deque is empty, or false otherwise.
  • boolean isFull() Returns true if the deque is full, or false otherwise.

Example 1:

Input
["MyCircularDeque", "insertLast", "insertLast", "insertFront", "insertFront", "getRear", "isFull", "deleteLast", "insertFront", "getFront"]
[[3], [1], [2], [3], [4], [], [], [], [4], []]
Output
[null, true, true, true, false, 2, true, true, true, 4]

Explanation
MyCircularDeque myCircularDeque = new MyCircularDeque(3);
myCircularDeque.insertLast(1);  // return True
myCircularDeque.insertLast(2);  // return True
myCircularDeque.insertFront(3); // return True
myCircularDeque.insertFront(4); // return False, the queue is full.
myCircularDeque.getRear();      // return 2
myCircularDeque.isFull();       // return True
myCircularDeque.deleteLast();   // return True
myCircularDeque.insertFront(4); // return True
myCircularDeque.getFront();     // return 4

Constraints:

  • 1 <= k <= 1000
  • 0 <= value <= 1000
  • At most 2000 calls will be made to insertFront, insertLast, deleteFront, deleteLast, getFront, getRear, isEmpty, isFull.
Patterns Used

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: Design your implementation of the circular double-ended queue (deque). Implement the MyCircularDeque class: MyCircularDeque(int k) Initializes the deque with a maximum size of k. boolean insertFront() Adds an item at the front of Deque. Returns true if the operation is successful, or false otherwise. boolean insertLast() Adds an item at the rear of Deque. Returns true if the operation is successful, or false otherwise. boolean deleteFront() Deletes an item from the front of Deque. Returns true if the operation is successful, or false otherwise. boolean deleteLast() Deletes an item from the rear of Deque. Returns true if the operation is successful, or false otherwise. int getFront() Returns the front item from the Deque. Returns -1 if the deque is empty. int getRear() Returns the last item from Deque. Returns -1 if the deque is empty. boolean isEmpty() Returns true if the deque is

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Array · Linked List · Design

Example 1

["MyCircularDeque","insertLast","insertLast","insertFront","insertFront","getRear","isFull","deleteLast","insertFront","getFront"]
[[3],[1],[2],[3],[4],[],[],[],[4],[]]

Related Problems

  • Design Circular Queue (design-circular-queue)
  • Design Front Middle Back Queue (design-front-middle-back-queue)
Step 02

Core Insight

What unlocks the optimal approach

  • No official hints in dataset. Start from constraints and look for a monotonic or reusable state.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #641: Design Circular Deque
class MyCircularDeque {
    private int[] q;
    private int front;
    private int size;
    private int capacity;

    /** Initialize your data structure here. Set the size of the deque to be k. */
    public MyCircularDeque(int k) {
        q = new int[k];
        capacity = k;
    }

    /** Adds an item at the front of Deque. Return true if the operation is successful. */
    public boolean insertFront(int value) {
        if (isFull()) {
            return false;
        }
        if (!isEmpty()) {
            front = (front - 1 + capacity) % capacity;
        }
        q[front] = value;
        ++size;
        return true;
    }

    /** Adds an item at the rear of Deque. Return true if the operation is successful. */
    public boolean insertLast(int value) {
        if (isFull()) {
            return false;
        }
        int idx = (front + size) % capacity;
        q[idx] = value;
        ++size;
        return true;
    }

    /** Deletes an item from the front of Deque. Return true if the operation is successful. */
    public boolean deleteFront() {
        if (isEmpty()) {
            return false;
        }
        front = (front + 1) % capacity;
        --size;
        return true;
    }

    /** Deletes an item from the rear of Deque. Return true if the operation is successful. */
    public boolean deleteLast() {
        if (isEmpty()) {
            return false;
        }
        --size;
        return true;
    }

    /** Get the front item from the deque. */
    public int getFront() {
        if (isEmpty()) {
            return -1;
        }
        return q[front];
    }

    /** Get the last item from the deque. */
    public int getRear() {
        if (isEmpty()) {
            return -1;
        }
        int idx = (front + size - 1) % capacity;
        return q[idx];
    }

    /** Checks whether the circular deque is empty or not. */
    public boolean isEmpty() {
        return size == 0;
    }

    /** Checks whether the circular deque is full or not. */
    public boolean isFull() {
        return size == capacity;
    }
}

/**
 * Your MyCircularDeque object will be instantiated and called as such:
 * MyCircularDeque obj = new MyCircularDeque(k);
 * boolean param_1 = obj.insertFront(value);
 * boolean param_2 = obj.insertLast(value);
 * boolean param_3 = obj.deleteFront();
 * boolean param_4 = obj.deleteLast();
 * int param_5 = obj.getFront();
 * int param_6 = obj.getRear();
 * boolean param_7 = obj.isEmpty();
 * boolean param_8 = obj.isFull();
 */
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n)
Space
O(1)

Approach Breakdown

COPY TO ARRAY
O(n) time
O(n) space

Copy all n nodes into an array (O(n) time and space), then use array indexing for random access. Operations like reversal or middle-finding become trivial with indices, but the O(n) extra space defeats the purpose of using a linked list.

IN-PLACE POINTERS
O(n) time
O(1) space

Most linked list operations traverse the list once (O(n)) and re-wire pointers in-place (O(1) extra space). The brute force often copies nodes to an array to enable random access, costing O(n) space. In-place pointer manipulation eliminates that.

Shortcut: Traverse once + re-wire pointers → O(n) time, O(1) space. Dummy head nodes simplify edge cases.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.

Losing head/tail while rewiring

Wrong move: Pointer updates overwrite references before they are saved.

Usually fails on: List becomes disconnected mid-operation.

Fix: Store next pointers first and use a dummy head for safer joins.