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232, Implement Queue using Stacks

MikeAbout 2 minstack/queueeasystackqueuedesign

I Problem

Implement a first in first out (FIFO) queue using only two stacks. The implemented queue should support all the functions of a normal queue (push, peek, pop, and empty).

Implement the MyQueue class:

  • void push(int x) Pushes element x to the back of the queue.
  • int pop() Removes the element from the front of the queue and returns it.
  • int peek() Returns the element at the front of the queue.
  • boolean empty() Returns true if the queue is empty, false otherwise.

Notes:

  • You must use only standard operations of a stack, which means only push to top, peek/pop from top, size, and is empty operations are valid.
  • Depending on your language, the stack may not be supported natively. You may simulate a stack using a list or deque (double-ended queue) as long as you use only a stack's standard operations.

Example 1
Input:
["MyQueue", "push", "push", "peek", "pop", "empty"]
[[], [1], [2], [], [], []]
Output:
[null, null, null, 1, 1, false]
Explanation:

MyQueue myQueue = new MyQueue();
myQueue.push(1); // queue is: [1]
myQueue.push(2); // queue is: [1, 2] (leftmost is front of the queue)
myQueue.peek();  // return 1
myQueue.pop();   // return 1, queue is [2]
myQueue.empty(); // return false

Constraints

  • 1 <= x <= 9
  • At most 100 calls will be made to push, pop, peek, and empty.
  • All the calls to pop and peek are valid.

Follow up
Can you implement the queue such that each operation is amortizedopen in new window O(1) time complexity? In other words, performing n operations will take overall O(n) time even if one of those operations may take longer.

Related Topics

  • Stack
  • Design
  • Queue

II Solution

pub struct MyQueue {
    s1: Vec<i32>,
    s2: Vec<i32>,
}

impl MyQueue {
    pub fn new() -> Self {
        MyQueue {
            s1: vec![],
            s2: vec![],
        }
    }
}

Approach 1: Two Stacks

impl MyQueue {
    /// Time Complexity: O(n)
    ///
    /// Space Complexity: O(n)
    pub fn push(&mut self, x: i32) {
        while let Some(val) = self.s1.pop() {
            self.s2.push(val);
        }
        self.s1.push(x);
        while let Some(val) = self.s2.pop() {
            self.s1.push(val);
        }
    }

    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(1)
    pub fn pop(&mut self) -> i32 {
        self.s1.pop().unwrap()
    }

    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(1)
    pub fn peek(&mut self) -> i32 {
        *self.s1.last().unwrap()
    }

    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(1)
    pub fn empty(&self) -> bool {
        self.s1.is_empty()
    }
}

Approach 2: Optimize Two Stacks

impl MyQueue {
    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(n)
    pub fn push(&mut self, x: i32) {
        self.s1.push(x);
    }

    /// Time Complexity: Amortized O(1), Worst-case O(n)
    ///
    /// Space Complexity: O(1)
    pub fn pop(&mut self) -> i32 {
        if self.s2.is_empty() {
            while let Some(val) = self.s1.pop() {
                self.s2.push(val);
            }
        }
        self.s2.pop().unwrap()
    }

    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(1)
    pub fn peek(&mut self) -> i32 {
        if self.s2.is_empty() {
            *self.s1.first().unwrap()
        } else {
            *self.s2.last().unwrap()
        }
    }

    /// Time Complexity: O(1)
    ///
    /// Space Complexity: O(1)
    pub fn empty(&self) -> bool {
        self.s1.is_empty() && self.s2.is_empty()
    }
}