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This approach involves using a fixed-size array to represent the deque. We'll maintain two indices, front and rear, to manage the current front and last positions in the deque. Operations like insertions and deletions are performed by adjusting these indices while ensuring they wrap around using the modulo operation as necessary to remain within the array bounds.
Time Complexity: O(1) for each operation.
Space Complexity: O(k), where k is the capacity of the deque.
1#include <vector>
2using namespace std;
3
4class MyCircularDeque {
5 vector<int> data;
6 int front;
7 int rear;
8 int size;
9 int capacity;
10
11public:
12 MyCircularDeque(int k) : data(k), front(0), rear(0), size(0), capacity(k) {}
13
14 bool insertFront(int value) {
15 if (isFull()) return false;
16 front = (front - 1 + capacity) % capacity;
17 data[front] = value;
18 size++;
19 return true;
20 }
21
22 bool insertLast(int value) {
23 if (isFull()) return false;
24 data[rear] = value;
25 rear = (rear + 1) % capacity;
26 size++;
27 return true;
28 }
29
30 bool deleteFront() {
31 if (isEmpty()) return false;
32 front = (front + 1) % capacity;
33 size--;
34 return true;
35 }
36
37 bool deleteLast() {
38 if (isEmpty()) return false;
39 rear = (rear - 1 + capacity) % capacity;
40 size--;
41 return true;
42 }
43
44 int getFront() {
45 if (isEmpty()) return -1;
46 return data[front];
47 }
48
49 int getRear() {
50 if (isEmpty()) return -1;
51 return data[(rear - 1 + capacity) % capacity];
52 }
53
54 bool isEmpty() {
55 return size == 0;
56 }
57
58 bool isFull() {
59 return size == capacity;
60 }
61};C++ implementation utilizes a vector for the circular array. All deque operations are facilitated using vector functions. Insertions and deletions adjust the front and rear indices while checking the size for fullness or emptiness.
This approach makes use of a doubly linked list to implement the deque. This is particularly effective because it offers dynamic memory usage which can grow or shrink with the number of elements, instead of relying on a pre-allocated fixed-size structure as with arrays.
Time Complexity: O(1) for all operations.
Space Complexity: O(n), where n is the number of elements currently in the deque (potentially more efficient if n is much less than the initial capacity).
1
Python's linked list approach enables a flexible allocation for deques with nodes connecting backward and forward, simplifying insertions/deletions by just adjusting node pointers. Each operation reacts in constant time, not hindered by array resizing constraints.