How do you solve Design Circular Deque on LeetCode?

Design Circular Deque (LeetCode #641) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(1) time complexity and O(n) space complexity. Key insight: Understanding circular data structures helps in optimizing space and time complexity.

What is the brute force solution for Design Circular Deque?

The brute force approach for Design Circular Deque is Brute Force, with O(n²) time complexity and O(1) space complexity. In a brute-force approach, we can use a simple list to represent the deque and perform operations directly on it. This method is straightforward but inefficient as it doesn't handle the circular nature of the deque well. The optimal Optimal Solution approach improves this to O(1).

What algorithm or data structure is used to solve Design Circular Deque?

Design Circular Deque uses the following concepts: Array, Linked List, Design, Queue. The recommended patterns to study are: Circular Array, Two Pointers.

What are the interview tips for Design Circular Deque?

Clearly explain your thought process and the structure you choose. Consider edge cases, such as inserting into a full deque or deleting from an empty one. Practice implementing both the brute-force and optimal solutions to understand trade-offs.

What are common mistakes when solving Design Circular Deque?

Not properly handling the wrap-around logic for front and rear pointers. Confusing empty and full conditions, leading to incorrect insert/delete operations.

#641

Design Circular Deque

Medium

ArrayLinked ListDesignQueueCircular ArrayTwo Pointers

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(1)
Space	O(1)	O(n)

💡

Intuition

Time O(1)Space O(n)

The optimal approach uses a circular array to efficiently manage the front and rear pointers, allowing O(1) time complexity for all operations. This design takes advantage of modular arithmetic to wrap around the array.

⚙️

Algorithm

3 steps

1Step 1: Initialize an array of size k to represent the deque.
2Step 2: Use two pointers (front and rear) to track the positions for insertion and deletion.
3Step 3: Use modular arithmetic to wrap around the pointers when they reach the end of the array.

solution.py49 lines

1class MyCircularDeque:
2    def __init__(self, k: int):
3        self.deque = [0] * k
4        self.max_size = k
5        self.front = 0
6        self.rear = 0
7        self.size = 0
8
9    def insertFront(self, value: int) -> bool:
10        if self.isFull():
11            return False
12        self.front = (self.front - 1 + self.max_size) % self.max_size
13        self.deque[self.front] = value
14        self.size += 1
15        return True
16
17    def insertLast(self, value: int) -> bool:
18        if self.isFull():
19            return False
20        self.deque[self.rear] = value
21        self.rear = (self.rear + 1) % self.max_size
22        self.size += 1
23        return True
24
25    def deleteFront(self) -> bool:
26        if self.isEmpty():
27            return False
28        self.front = (self.front + 1) % self.max_size
29        self.size -= 1
30        return True
31
32    def deleteLast(self) -> bool:
33        if self.isEmpty():
34            return False
35        self.rear = (self.rear - 1 + self.max_size) % self.max_size
36        self.size -= 1
37        return True
38
39    def getFront(self) -> int:
40        return self.deque[self.front] if not self.isEmpty() else -1
41
42    def getRear(self) -> int:
43        return self.deque[(self.rear - 1 + self.max_size) % self.max_size] if not self.isEmpty() else -1
44
45    def isEmpty(self) -> bool:
46        return self.size == 0
47
48    def isFull(self) -> bool:
49        return self.size == self.max_size

ℹ

Complexity note: The time complexity is O(1) for all operations because we are directly accessing array indices. The space complexity is O(n) due to the storage of elements in the circular array.

1Understanding circular data structures helps in optimizing space and time complexity.
2Using modular arithmetic is crucial for managing indices in circular arrays.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.