155. Min Stack

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155. Min Stack

Easy

Design a stack that supports push, pop, top, and retrieving the minimum element in constant time.

Implement the MinStack class:

  • MinStack() initializes the stack object.
  • void push(val) pushes the element val onto the stack.
  • void pop() removes the element on the top of the stack.
  • int top() gets the top element of the stack.
  • int getMin() retrieves the minimum element in the stack.

Example 1:

Input
["MinStack","push","push","push","getMin","pop","top","getMin"]
[[],[-2],[0],[-3],[],[],[],[]]

Output
[null,null,null,null,-3,null,0,-2]

Explanation
MinStack minStack = new MinStack();
minStack.push(-2);
minStack.push(0);
minStack.push(-3);
minStack.getMin(); // return -3
minStack.pop();
minStack.top();    // return 0
minStack.getMin(); // return -2

Constraints:

  • -2^31 <= val <= 2^31 - 1
  • Methods pop, top and getMin operations will always be called on non-empty stacks.
  • At most 3 * 10^4 calls will be made to push, pop, top, and getMin.

思路

用一个栈 data 存放数据，同时记录当前全局最小的元素 current_min，同时维护一个栈 min 存放每个位置的最小元素。两个栈保持高度相同。

当新数据 push 入data 栈时，更新全局最小元素 current_min，并将其压入 min。

当 data 栈 pop 时，同步 pop min，并更新 current_min 为 min 栈顶元素。若 min 为空，则将 current_min 重置为 INT_MAX。

class MinStack {
private:
    stack<int> data;
    stack<int> min;
    int current_min = INT_MAX;
public:
    /** initialize your data structure here. */
    MinStack() {
    }
    
    void push(int val) {
        data.push(val);
        if (val < current_min) {
            current_min = val;
        }
        min.push(current_min);
    }
    
    void pop() {
        data.pop();
        min.pop();
        if (!min.empty()) current_min = min.top();
        else current_min = INT_MAX;
    }
    
    int top() {
        return data.top();
    }
    
    int getMin() {
        return min.top();
    }
};

Runtime: 16 ms, faster than 96.78% of C++ online submissions for Min Stack.

Memory Usage: 16.2 MB, less than 22.25% of C++ online submissions for Min Stack.

（考虑到 min 栈中的元素大多是连续重复值，后续可以将其改进为计数的形式进行压缩优化。）

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