设计一个堆栈，使getMinimum（）应该为O（1）

这是面试问题之一。您需要设计一个包含整数值的堆栈，以便getMinimum（）函数应返回堆栈中的最小元素。

例如：考虑以下示例

情况1

5->顶部
1个
4
6
2

调用getMinimum（）时，它应返回1，这是最小元素 
在堆栈中。 

情况＃2

stack.pop（）
stack.pop（）

注意：5和1都从堆栈中弹出。所以之后，堆栈
好像，

4->顶部
6
2

调用getMinimum（）时应返回2，这是 
堆栈。

食用者：

1. getMinimum应该返回O（1）中的最小值
2. 在设计时还必须考虑空间约束，如果使用额外的空间，则它应该是恒定的空间。

编辑：这失败了“恒定空间”约束-它基本上使所需的空间加倍。我非常怀疑是否有一种解决方案不能做到这一点，而不会破坏某个地方的运行时复杂性（例如，使push / pop O（n））。请注意，这不会改变所需空间的复杂性，例如，如果您有一个具有O（n）空间需求的堆栈，那么这将是O（n），只是具有不同的常数因子。

非恒定空间解决方案

保持“重复的”堆栈，其中“堆栈中所有值的最小值都较低”。当您弹出主堆栈时，也要弹出最小堆栈。推入主堆栈时，推入新元素或当前最小值，以较低者为准。getMinimum()然后实现为just minStack.peek()。

因此，使用您的示例，我们将：

Real stack        Min stack

5  --> TOP        1
1                 1
4                 2
6                 2
2                 2

弹出两次后，您会得到：

Real stack        Min stack

4                 2
6                 2
2                 2

如果这还不够，请告诉我。拖拉它很简单，但是一开始可能会有些头疼：)

（当然，缺点是它使空间需求增加了一倍。尽管执行时间并没有受到很大的影响-即它仍然是相同的复杂性。）

编辑：有一个变体，它稍微更有趣，但总体上具有更好的空间。我们仍然有最小堆栈，但是只有从主堆栈中弹出的值等于最小堆栈上的值时才从中弹出。仅当被压入主堆栈的值小于或等于当前最小值时，才压入最小堆栈。这允许重复的最小值。仍然只是一个窥视操作。例如，采用原始版本并再次按1，我们将得到：getMinimum()

Real stack        Min stack

1  --> TOP        1
5                 1
1                 2
4                 
6                 
2                 

从上面弹出会从两个堆栈中弹出，因为1 == 1，从而留下：

Real stack        Min stack

5  --> TOP        1
1                 2
4                 
6                 
2                 

再次弹出只从主堆栈中弹出，因为5> 1：

Real stack        Min stack

1                 1
4                 2
6                 
2                 

再次弹出会同时弹出两个堆栈，因为1 == 1：

Real stack        Min stack

4                 2
6                 
2                 

最终以相同的最坏情况下的空间复杂度（原始堆栈的两倍）结束，但是如果我们很少获得“新的最小值或相等”，则会更好地利用空间。

编辑：这是皮特邪恶计划的实现。我还没有对它进行彻底的测试，但是我认为还可以：)

using System.Collections.Generic;

public class FastMinStack<T>
{
    private readonly Stack<T> stack = new Stack<T>();
    // Could pass this in to the constructor
    private readonly IComparer<T> comparer = Comparer<T>.Default;

    private T currentMin;

    public T Minimum
    {
        get { return currentMin; }
    }

    public void Push(T element)
    {
        if (stack.Count == 0 ||
            comparer.Compare(element, currentMin) <= 0)
        {
            stack.Push(currentMin);
            stack.Push(element);
            currentMin = element;
        }
        else
        {
            stack.Push(element);
        }
    }

    public T Pop()
    {
        T ret = stack.Pop();
        if (comparer.Compare(ret, currentMin) == 0)
        {
            currentMin = stack.Pop();
        }
        return ret;
    }
}

添加一个字段以保存最小值，并在Pop（）和Push（）期间对其进行更新。这样，getMinimum（）将为O（1），但是Pop（）和Push（）将不得不做更多的工作。

如果弹出最小值，则Pop（）将为O（n），否则它们仍将均为O（1）。调整大小时，根据Stack实现，Push（）变为O（n）。

这是一个快速实施

public sealed class MinStack {
    private int MinimumValue;
    private readonly Stack<int> Stack = new Stack<int>();

    public int GetMinimum() {
        if (IsEmpty) {
            throw new InvalidOperationException("Stack is empty");
        }
        return MinimumValue;
    }

    public int Pop() {
        var value = Stack.Pop();
        if (value == MinimumValue) {
            MinimumValue = Stack.Min();
        }
        return value;
    }

    public void Push(int value) {
        if (IsEmpty || value < MinimumValue) {
            MinimumValue = value;
        }
        Stack.Push(value);
    }

    private bool IsEmpty { get { return Stack.Count() == 0; } }
}

public class StackWithMin {
    int min;
    int size;
    int[] data = new int[1024];

    public void push ( int val ) {
        if ( size == 0 ) {
            data[size] = val;
            min = val;
        } else if ( val < min) {
            data[size] = 2 * val - min;
            min = val;

            assert (data[size] < min); 
        } else {
            data[size] = val;
        }

        ++size;

        // check size and grow array
    }

    public int getMin () {
        return min;
    }

    public int pop () {
        --size;

        int val = data[size];

        if ( ( size > 0 ) && ( val < min ) ) {
            int prevMin = min;
            min += min - val;
            return prevMin;
        } else {
            return val;
        }
    }

    public boolean isEmpty () {
        return size == 0;
    }

    public static void main (String...args) {
        StackWithMin stack = new StackWithMin();

        for ( String arg: args ) 
            stack.push( Integer.parseInt( arg ) );

        while ( ! stack.isEmpty() ) {
            int min = stack.getMin();
            int val = stack.pop();

            System.out.println( val + " " + min );
        }

        System.out.println();
    }

}

它显式存储当前的最小值，如果最小值发生变化，则不推压该值，而是推压一个与新最小值最小值相同的差值（如果min = 7并且推5，则推3而不是（5 | 7-5 | = 3）并将min设置为5；如果然后在min为5时弹出3，则会看到弹出的值小于min，因此对新的min取相反的过程以获得7，然后返回上一个分钟）。由于任何不引起更改的值当前最小值都大于当前最小值，因此您可以使用一些东西来区分更改最小值的值和不更改最小值的值。

在使用固定大小整数的语言中，您从值的表示中借用了一些空间，因此它可能会下溢并且断言将失败。但是否则，它是恒定的额外空间，并且所有操作仍为O（1）。

基于链接列表的堆栈还有其他位置，您可以从其他地方借用一点，例如，在C中下一个指针的最低有效位，或者在Java中，链接列表中对象的类型。对于Java，这确实意味着，与连续堆栈相比，使用了更多的空间，因为每个链接都有对象开销：

public class LinkedStackWithMin {
    private static class Link {
        final int value;
        final Link next;

        Link ( int value, Link next ) {
            this.value = value;
            this.next = next;
        }

        int pop ( LinkedStackWithMin stack ) {
            stack.top = next;
            return value;
        }
    }

    private static class MinLink extends Link {
        MinLink ( int value, Link next ) {
            super( value, next );
        }

        int pop ( LinkedStackWithMin stack ) {
            stack.top = next;
            int prevMin = stack.min;
            stack.min = value;
            return prevMin;
        }
    }

    Link top;
    int min;

    public LinkedStackWithMin () {
    }

    public void push ( int val ) {
        if ( ( top == null ) || ( val < min ) ) {
            top = new MinLink(min, top);
            min = val;
        } else {
            top = new Link(val, top);
        }
    }

    public int pop () {
        return top.pop(this);
    }

    public int getMin () {
        return min;
    }

    public boolean isEmpty () {
        return top == null;
    }

在C中，开销不存在，您可以借用下一个指针的lsb：

typedef struct _stack_link stack_with_min;

typedef struct _stack_link stack_link;

struct _stack_link {
    size_t  next;
    int     value;
};

stack_link* get_next ( stack_link* link ) 
{
    return ( stack_link * )( link -> next & ~ ( size_t ) 1 );
}

bool is_min ( stack_link* link )
{
    return ( link -> next & 1 ) ! = 0;
}

void push ( stack_with_min* stack, int value )
{
    stack_link *link = malloc ( sizeof( stack_link ) );

    link -> next = ( size_t ) stack -> next;

    if ( (stack -> next == 0) || ( value == stack -> value ) ) {
        link -> value = stack -> value;
        link -> next |= 1; // mark as min
    } else {
        link -> value = value;
    }

    stack -> next = link;
}

etc.;

但是，这些都不是真正的O（1）。实际上，它们不需要任何空间，因为它们利用了这些语言中的数字，对象或指针表示形式中的漏洞。但是，使用更紧凑表示形式的理论机器将需要在每种情况下向该表示形式添加额外的位。

我找到了一个满足上述所有约束（恒定时间操作）和恒定额外空间的解决方案。

想法是存储最小值和输入数字之间的差，并在最小值不再是最小值时更新最小值。

代码如下：

public class MinStack {
    long min;
    Stack<Long> stack;

    public MinStack(){
        stack = new Stack<>();
    }

    public void push(int x) {
        if (stack.isEmpty()) {
            stack.push(0L);
            min = x;
        } else {
            stack.push(x - min); //Could be negative if min value needs to change
            if (x < min) min = x;
        }
    }

    public int pop() {
        if (stack.isEmpty()) return;

        long pop = stack.pop();

        if (pop < 0) {
            long ret = min
            min = min - pop; //If negative, increase the min value
            return (int)ret;
        }
        return (int)(pop + min);

    }

    public int top() {
        long top = stack.peek();
        if (top < 0) {
            return (int)min;
        } else {
           return (int)(top + min);
        }
    }

    public int getMin() {
        return (int)min;
    }
}

学分至：https : //leetcode.com/discuss/15679/share-my-java-solution-with-only-one-stack

那么，什么是运行制约push和pop？如果不需要使它们恒定，则只需在这两个操作中计算最小值（使它们为O（n））即可。否则，我看不到如何在不断增加空间的情况下完成此操作。

这是我的与O（1）一起运行的代码。当最小元素弹出时，我发布的先前代码有问题。我修改了我的代码。这使用了另一个堆栈，该堆栈保持堆栈中当前推送元素上方的最小元素。

 class StackDemo
{
    int[] stk = new int[100];
    int top;
    public StackDemo()
    {
        top = -1;
    }
    public void Push(int value)
    {
        if (top == 100)
            Console.WriteLine("Stack Overflow");
        else
            stk[++top] = value;
    }
    public bool IsEmpty()
    {
        if (top == -1)
            return true;
        else
            return false;
    }
    public int Pop()
    {
        if (IsEmpty())
        {
            Console.WriteLine("Stack Underflow");
            return 0;
        }
        else
            return stk[top--];
    }
    public void Display()
    {
        for (int i = top; i >= 0; i--)
            Console.WriteLine(stk[i]);
    }
}
class MinStack : StackDemo
{
    int top;
    int[] stack = new int[100];
    StackDemo s1; int min;
    public MinStack()
    {
        top = -1;
        s1 = new StackDemo();
    }
    public void PushElement(int value)
    {
        s1.Push(value);
        if (top == 100)
            Console.WriteLine("Stack Overflow");
        if (top == -1)
        {
            stack[++top] = value;
            stack[++top] = value;   
        }
        else
        {
            //  stack[++top]=value;
            int ele = PopElement();
            stack[++top] = ele;
            int a = MininmumElement(min, value);
              stack[++top] = min;

                stack[++top] = value;
                stack[++top] = a;


        }
    }
    public int PopElement()
    {

        if (top == -1)
            return 1000;
        else
        {
            min = stack[top--];
            return stack[top--];
        }

    }
    public int PopfromStack()
    {
        if (top == -1)
            return 1000;
        else
        {
            s1.Pop();
            return PopElement();
        }
    }
    public int MininmumElement(int a,int b)
    {
        if (a > b)
            return b;
        else
            return a;
    }
    public int StackTop()
    {
        return stack[top];
    }
    public void DisplayMinStack()
    {
        for (int i = top; i >= 0; i--)
            Console.WriteLine(stack[i]);
    }
}
class Program
{
    static void Main(string[] args)
    {
        MinStack ms = new MinStack();
        ms.PushElement(15);
        ms.PushElement(2);
        ms.PushElement(1);
        ms.PushElement(13);
        ms.PushElement(5);
        ms.PushElement(21);
        Console.WriteLine("Min Stack");
        ms.DisplayMinStack();
        Console.WriteLine("Minimum Element:"+ms.StackTop());
        ms.PopfromStack();
        ms.PopfromStack();
        ms.PopfromStack();
        ms.PopfromStack();

        Console.WriteLine("Min Stack");
        ms.DisplayMinStack();
        Console.WriteLine("Minimum Element:" + ms.StackTop());
        Thread.Sleep(1000000);
    }
}

我使用了另一种堆栈。这是实现。

//
//  main.cpp
//  Eighth
//
//  Created by chaitanya on 4/11/13.
//  Copyright (c) 2013 cbilgika. All rights reserved.
//

#include <iostream>
#include <limits>
using namespace std;
struct stack
{
    int num;
    int minnum;
}a[100];

void push(int n,int m,int &top)
{

    top++;
    if (top>=100) {
        cout<<"Stack Full";
        cout<<endl;
    }
    else{
        a[top].num = n;
        a[top].minnum = m;
    }


}

void pop(int &top)
{
    if (top<0) {
        cout<<"Stack Empty";
        cout<<endl;
    }
    else{
       top--; 
    }


}
void print(int &top)
{
    cout<<"Stack: "<<endl;
    for (int j = 0; j<=top ; j++) {
        cout<<"("<<a[j].num<<","<<a[j].minnum<<")"<<endl;
    }
}


void get_min(int &top)
{
    if (top < 0)
    {
        cout<<"Empty Stack";
    }
    else{
        cout<<"Minimum element is: "<<a[top].minnum;
    }
    cout<<endl;
}

int main()
{

    int top = -1,min = numeric_limits<int>::min(),num;
    cout<<"Enter the list to push (-1 to stop): ";
    cin>>num;
    while (num!=-1) {
        if (top == -1) {
            min = num;
            push(num, min, top);
        }
        else{
            if (num < min) {
                min = num;
            }
            push(num, min, top);
        }
        cin>>num;
    }
    print(top);
    get_min(top);
    return 0;
}

输出：

Enter the list to push (-1 to stop): 5
1
4
6
2
-1
Stack: 
(5,5)
(1,1)
(4,1)
(6,1)
(2,1)
Minimum element is: 1

试试吧。我认为它回答了这个问题。每对中的第二个元素提供插入该元素时看到的最小值。

我将在此处发布完整代码，以在给定堆栈中找到最小值和最大值。

时间复杂度将为O（1）。

package com.java.util.collection.advance.datastructure;

/**
 * 
 * @author vsinha
 *
 */
public abstract interface Stack<E> {

    /**
     * Placing a data item on the top of the stack is called pushing it
     * @param element
     * 
     */
    public abstract void push(E element);


    /**
     * Removing it from the top of the stack is called popping it
     * @return the top element
     */
    public abstract E pop();

    /**
     * Get it top element from the stack and it 
     * but the item is not removed from the stack, which remains unchanged
     * @return the top element
     */
    public abstract E peek();

    /**
     * Get the current size of the stack.
     * @return
     */
    public abstract int size();


    /**
     * Check whether stack is empty of not.
     * @return true if stack is empty, false if stack is not empty
     */
    public abstract boolean empty();



}



package com.java.util.collection.advance.datastructure;

@SuppressWarnings("hiding")
public abstract interface MinMaxStack<Integer> extends Stack<Integer> {

    public abstract int min();

    public abstract int max();

}


package com.java.util.collection.advance.datastructure;

import java.util.Arrays;

/**
 * 
 * @author vsinha
 *
 * @param <E>
 */
public class MyStack<E> implements Stack<E> {

    private E[] elements =null;
    private int size = 0;
    private int top = -1;
    private final static int DEFAULT_INTIAL_CAPACITY = 10;


    public MyStack(){
        // If you don't specify the size of stack. By default, Stack size will be 10
        this(DEFAULT_INTIAL_CAPACITY);
    }

    @SuppressWarnings("unchecked")
    public MyStack(int intialCapacity){
        if(intialCapacity <=0){
            throw new IllegalArgumentException("initial capacity can't be negative or zero");
        }
        // Can't create generic type array
        elements =(E[]) new Object[intialCapacity];
    }

    @Override
    public void push(E element) {
        ensureCapacity();
        elements[++top] = element;
        ++size;
    }

    @Override
    public E pop() {
        E element = null;
        if(!empty()) {
            element=elements[top];
            // Nullify the reference
            elements[top] =null;
            --top;
            --size;
        }
        return element;
    }

    @Override
    public E peek() {
        E element = null;
        if(!empty()) {
            element=elements[top];
        }
        return element;
    }

    @Override
    public int size() {
        return size;
    }

    @Override
    public boolean empty() {
        return size == 0;
    }

    /**
     * Increases the capacity of this <tt>Stack by double of its current length</tt> instance, 
     * if stack is full 
     */
    private void ensureCapacity() {
        if(size != elements.length) {
            // Don't do anything. Stack has space.
        } else{
            elements = Arrays.copyOf(elements, size *2);
        }
    }

    @Override
    public String toString() {
        return "MyStack [elements=" + Arrays.toString(elements) + ", size="
                + size + ", top=" + top + "]";
    }


}


package com.java.util.collection.advance.datastructure;

/**
 * Time complexity will be O(1) to find min and max in a given stack.
 * @author vsinha
 *
 */
public class MinMaxStackFinder extends MyStack<Integer> implements MinMaxStack<Integer> {

    private MyStack<Integer> minStack;

    private MyStack<Integer> maxStack;

    public MinMaxStackFinder (int intialCapacity){
        super(intialCapacity);
        minStack =new MyStack<Integer>();
        maxStack =new MyStack<Integer>();

    }
    public void push(Integer element) {
        // Current element is lesser or equal than min() value, Push the current element in min stack also.
        if(!minStack.empty()) {
            if(min() >= element) {
                minStack.push(element);
            }
        } else{
            minStack.push(element);
        }
        // Current element is greater or equal than max() value, Push the current element in max stack also.
        if(!maxStack.empty()) {
            if(max() <= element) {
                maxStack.push(element);
            }
        } else{
            maxStack.push(element);
        }
        super.push(element);
    }


    public Integer pop(){
        Integer curr = super.pop();
        if(curr !=null) {
            if(min() == curr) {
                minStack.pop();
            } 

            if(max() == curr){
                maxStack.pop();
            }
        }
        return curr;
    }


    @Override
    public int min() {
        return minStack.peek();
    }

    @Override
    public int max() {
        return maxStack.peek();
    }


    @Override
    public String toString() {
        return super.toString()+"\nMinMaxStackFinder [minStack=" + minStack + "\n maxStack="
                + maxStack + "]" ;
    }




}

// You can use the below program to execute it.

package com.java.util.collection.advance.datastructure;

import java.util.Random;

public class MinMaxStackFinderApp {

    public static void main(String[] args) {
        MinMaxStack<Integer> stack =new MinMaxStackFinder(10);
        Random random =new Random();
        for(int i =0; i< 10; i++){
            stack.push(random.nextInt(100));
        }
        System.out.println(stack);
        System.out.println("MAX :"+stack.max());
        System.out.println("MIN :"+stack.min());

        stack.pop();
        stack.pop();
        stack.pop();
        stack.pop();
        stack.pop();

        System.out.println(stack);
        System.out.println("MAX :"+stack.max());
        System.out.println("MIN :"+stack.min());
    }
}

让我知道您是否遇到任何问题

谢谢，Vikash

您可以扩展您的原始堆栈类，然后向其添加最小跟踪。让原始的父类照常处理其他所有事情。

public class StackWithMin extends Stack<Integer> {  

    private Stack<Integer> min;

    public StackWithMin() {
        min = new Stack<>();
    }

    public void push(int num) {
        if (super.isEmpty()) {
            min.push(num);
        } else if (num <= min.peek()) {
            min.push(num);
        }
        super.push(num);
    }

    public int min() {
        return min.peek();
    }

    public Integer pop() {
        if (super.peek() == min.peek()) {
            min.pop();
        }
        return super.pop();
    }   
}

这是我在Java中使用喜欢列表的解决方案。

class Stack{
    int min;
    Node top;
    static class Node{
        private int data;
        private Node next;
        private int min;

        Node(int data, int min){
           this.data = data;
           this.min = min;
           this.next = null; 
    }
}

  void push(int data){
        Node temp;
        if(top == null){
            temp = new Node(data,data);
            top = temp;
            top.min = data;
        }
        if(top.min > data){
            temp = new Node(data,data);
            temp.next = top;
            top = temp;
        } else {
            temp = new Node(data, top.min);
            temp.next = top;
            top = temp;
        }
  }

  void pop(){
    if(top != null){
        top = top.next;
    }
  }

  int min(){
    return top.min;
  }

}

假设我们要处理的堆栈是这样的：

6 , minvalue=2
2 , minvalue=2
5 , minvalue=3
3 , minvalue=3
9 , minvalue=7
7 , minvalue=7
8 , minvalue=8

在上面的表示中，堆栈仅由左值构成，而右值的[minvalue]仅出于说明目的而编写，将存储在一个变量中。

实际的问题是，当最小值被取走时，如何在不迭代堆栈的情况下知道下一个最小元素是什么。

例如，在我们的堆栈中，当弹出6个get时，我们知道，这不是最小元素，因为最小元素是2，所以我们可以安全地删除它而无需更新最小值。

但是当我们弹出2时，我们可以看到最小值现在是2，如果弹出该弹出框，则需要将最小值更新为3。

第一点：

现在，如果您仔细观察，我们需要从此特定状态[2，minvalue = 2]生成minvalue = 3。或者，如果您在堆栈中使用depper，我们需要从此特定状态[3，minvalue = 3]生成minvalue = 7；或者，如果您在堆栈中使用更多depper，则需要从该特定状态[min7]中生成minvalue = 8 = 7]

您是否注意到上述三种情况的共同点，我们需要生成的值取决于两个相等的变量。正确。发生这种情况的原因是，当我们将某个元素推入比当前最小值还小的值时，我们基本上会将这个元素推入堆栈，并在minvalue中也更新了相同的数字。

第二点：

因此，我们基本上是将相同数量的副本存储在堆栈中，一次存储在minvalue变量中。我们需要集中精力避免这种重复，并在堆栈或最小值中存储一些有用的数据以生成先前的最小值，如上面的案例所示。

让我们集中讨论当要存储在push中的值小于minmumvalue时应该存储在堆栈中的内容。让我们将这个变量命名为y，那么现在我们的堆栈将如下所示：

6 , minvalue=2
y1 , minvalue=2
5 , minvalue=3
y2 , minvalue=3
9 , minvalue=7
y3 , minvalue=7
8 , minvalue=8

我已将它们重命名为y1，y2，y3，以避免造成混淆，因为它们将具有相同的值。

第三点：

现在，让我们尝试查找y1，y2和y3上的一些约束。您还记得只有在我们弹出等于最小值的元素时，才需要在执行pop（）时更新最小值吗？如果我们弹出大于最小值的东西，那么我们就不必更新最小值。因此，要触发最小值更新，y1，y2＆y3应该小于相应的最小值。[我们正在避免相等，以避免重复[Point2]]，因此约束为[y <minValue]。

现在让我们返回以填充y，我们需要生成一些值并将y放入push时，记住。让我们将推入的值设为x，它小于prevMinvalue，而我们将实际推入堆栈的值设为y。因此很明显，newMinValue = x，并且y <newMinvalue。

现在我们需要在prevMinvalue和x（newMinvalue）的帮助下计算y（记住y可以是小于newMinValue（x）的任何数字，因此我们需要找到一些可以满足约束的数字）。

Let's do the math:
    x < prevMinvalue [Given]
    x - prevMinvalue < 0 
    x - prevMinValue + x < 0 + x [Add x on both side]
    2*x - prevMinValue < x      
this is the y which we were looking for less than x(newMinValue).
y = 2*x - prevMinValue. 'or' y = 2*newMinValue - prevMinValue 'or' y = 2*curMinValue - prevMinValue [taking curMinValue=newMinValue].

因此，在推送x时，如果它小于prevMinvalue，则我们推送y [2 * x-prevMinValue]并更新newMinValue = x。

并且在弹出时，如果堆栈包含的内容小于minValue，那么这就是我们更新minVAlue的触发器。我们必须根据curMinValue和y计算prevMinValue。y = 2 * curMinValue-prevMinValue [已验证] prevMinVAlue = 2 * curMinvalue-y。

2 * curMinValue-y是我们现在需要更新为prevMinValue的数字。

下面以O（1）时间和O（1）空间复杂度共享同一逻辑的代码。

// C++ program to implement a stack that supports 
// getMinimum() in O(1) time and O(1) extra space. 
#include <bits/stdc++.h> 
using namespace std; 

// A user defined stack that supports getMin() in 
// addition to push() and pop() 
struct MyStack 
{ 
    stack<int> s; 
    int minEle; 

    // Prints minimum element of MyStack 
    void getMin() 
    { 
        if (s.empty()) 
            cout << "Stack is empty\n"; 

        // variable minEle stores the minimum element 
        // in the stack. 
        else
            cout <<"Minimum Element in the stack is: "
                 << minEle << "\n"; 
    } 

    // Prints top element of MyStack 
    void peek() 
    { 
        if (s.empty()) 
        { 
            cout << "Stack is empty "; 
            return; 
        } 

        int t = s.top(); // Top element. 

        cout << "Top Most Element is: "; 

        // If t < minEle means minEle stores 
        // value of t. 
        (t < minEle)? cout << minEle: cout << t; 
    } 

    // Remove the top element from MyStack 
    void pop() 
    { 
        if (s.empty()) 
        { 
            cout << "Stack is empty\n"; 
            return; 
        } 

        cout << "Top Most Element Removed: "; 
        int t = s.top(); 
        s.pop(); 

        // Minimum will change as the minimum element 
        // of the stack is being removed. 
        if (t < minEle) 
        { 
            cout << minEle << "\n"; 
            minEle = 2*minEle - t; 
        } 

        else
            cout << t << "\n"; 
    } 

    // Removes top element from MyStack 
    void push(int x) 
    { 
        // Insert new number into the stack 
        if (s.empty()) 
        { 
            minEle = x; 
            s.push(x); 
            cout <<  "Number Inserted: " << x << "\n"; 
            return; 
        } 

        // If new number is less than minEle 
        if (x < minEle) 
        { 
            s.push(2*x - minEle); 
            minEle = x; 
        } 

        else
           s.push(x); 

        cout <<  "Number Inserted: " << x << "\n"; 
    } 
}; 

// Driver Code 
int main() 
{ 
    MyStack s; 
    s.push(3); 
    s.push(5); 
    s.getMin(); 
    s.push(2); 
    s.push(1); 
    s.getMin(); 
    s.pop(); 
    s.getMin(); 
    s.pop(); 
    s.peek(); 

    return 0; 
} 

这是我的实施版本。

 struct MyStack {
    int元素
    int * CurrentMiniAddress;
 };

 无效Push（int值）
 {
    //创建您的结构并填充值
    MyStack S =新的MyStack（）;
    S->元素=值;

    如果（Stack.Empty（））
    {    
        //由于堆栈为空，因此将CurrentMiniAddress指向自身
        S-> CurrentMiniAddress = S;

    }
    其他
    {
         //堆栈不为空

         //检索顶部元素。没有Pop（）
         MyStack * TopElement = Stack.Top（）;

         //记住总是TOP元素指向
         //整个堆栈中的最小元素
         如果（S-> element CurrentMiniAddress-> element）
         {
            //如果当前值是整个堆栈中的最小值
            //然后S指向自身
            S-> CurrentMiniAddress = S;
         }
             其他
             {
                 //所以这不是整个堆栈中的最小值
                 //不用担心，TOP拥有最小的元素
                 S-> CurrentMiniAddress = TopElement-> CurrentMiniAddress;
             }

    }
        Stack.Add（S）;
 }

 无效Pop（）
 {
     if（！Stack.Empty（））
     {
        Stack.Pop（）;
     }  
 }

 int GetMinimum（堆栈和堆栈）
 {
       if（！stack.Empty（））
       {
            MyStack * Top = stack.top（）;
            //顶部始终指向最小值
            返回Top-> CurrentMiniAddress-> element;
        }
 }

#include<stdio.h>
struct stack
{
    int data;
    int mindata;
}a[100];

void push(int *tos,int input)
{
    if (*tos > 100)
    {
        printf("overflow");
        return;
    }
    (*tos)++;
    a[(*tos)].data=input;
    if (0 == *tos)
        a[*tos].mindata=input;
    else if (a[*tos -1].mindata < input)
        a[*tos].mindata=a[*tos -1].mindata;
    else
        a[*tos].mindata=input;
}

int pop(int * tos)
{
    if (*tos <= -1)
    {
        printf("underflow");
        return -1;
    }
    return(a[(*tos)--].data);
}
void display(int tos)
{
    while (tos > -1)
    {
        printf("%d:%d\t",a[tos].data,a[tos].mindata);
        tos--;
    }    
}

int min(int tos)
{
   return(a[tos].mindata);
}
int main()
{
int tos=-1,x,choice;
while(1)
{
    printf("press 1-push,2-pop,3-mindata,4-display,5-exit ");
    scanf("%d",&choice);
    switch(choice)
    {
    case 1: printf("enter data to push");
            scanf("%d",&x);
            push(&tos,x);
            break;
    case 2: printf("the poped out data=%d ",pop(&tos));
            break;
    case 3: printf("The min peeped data:%d",min(tos));
            break;
    case 4: printf("The elements of stack \n");
            display(tos);
            break;
    default: exit(0);
}
}

我在这里找到了这个解决方案

struct StackGetMin {
  void push(int x) {
    elements.push(x);
    if (minStack.empty() || x <= minStack.top())
      minStack.push(x);
  }
  bool pop() {
    if (elements.empty()) return false;
    if (elements.top() == minStack.top())
      minStack.pop();
    elements.pop();
    return true;
  }
  bool getMin(int &min) {
    if (minStack.empty()) {
      return false;
    } else {
      min = minStack.top();
      return true;
    }
  }
  stack<int> elements;
  stack<int> minStack;
};

struct Node {
    let data: Int
    init(_ d:Int){
        data = d
    }
}

struct Stack {
    private var backingStore = [Node]()
    private var minArray = [Int]()

    mutating func push(n:Node) {
        backingStore.append(n)
        minArray.append(n.data)
        minArray.sort(>)
        minArray
    }

    mutating func pop() -> Node? {
        if(backingStore.isEmpty){
            return nil
        }

        let n = backingStore.removeLast()

        var found = false
        minArray = minArray.filter{
            if (!found && $0 == n.data) {
                found = true
                return false
            }
            return true
        }
        return n
    }

    func min() -> Int? {
        return minArray.last
    }
}

 class MyStackImplementation{
private final int capacity = 4;
int min;
int arr[] = new int[capacity];
int top = -1;

public void push ( int val ) {
top++;
if(top <= capacity-1){
    if(top == 0){
min = val;
arr[top] = val;
}
else if(val < min){
arr[top] = arr[top]+min;
min = arr[top]-min;
arr[top] = arr[top]-min;
}
else {
arr[top] = val;
}
System.out.println("element is pushed");
}
else System.out.println("stack is full");

}

 public void pop () {
top--;
   if(top > -1){ 

   min = arr[top];
}
else {min=0; System.out.println("stack is under flow");}

}
public int min(){
return min;
}

 public boolean isEmpty () {
    return top == 0;
}

public static void main(String...s){
MyStackImplementation msi = new MyStackImplementation();
msi.push(1);
msi.push(4);
msi.push(2);
msi.push(10);
System.out.println(msi.min);
msi.pop();
msi.pop();
msi.pop();
msi.pop();
msi.pop();
System.out.println(msi.min);

}
}

class FastStack {

    private static class StackNode {
        private Integer data;
        private StackNode nextMin;

        public StackNode(Integer data) {
            this.data = data;
        }

        public Integer getData() {
            return data;
        }

        public void setData(Integer data) {
            this.data = data;
        }

        public StackNode getNextMin() {
            return nextMin;
        }

        public void setNextMin(StackNode nextMin) {
            this.nextMin = nextMin;
        }

    }

    private LinkedList<StackNode> stack = new LinkedList<>();

    private StackNode currentMin = null;

    public void push(Integer item) {
        StackNode node = new StackNode(item);
        if (currentMin == null) {
            currentMin = node;
            node.setNextMin(null);
        } else if (item < currentMin.getData()) {
            StackNode oldMinNode = currentMin;
            node.setNextMin(oldMinNode);
            currentMin = node;
        }

        stack.addFirst(node);
    }

    public Integer pop() {
        if (stack.isEmpty()) {
            throw new EmptyStackException();
        }
        StackNode node = stack.peek();
        if (currentMin == node) {
            currentMin = node.getNextMin();
        }
        stack.removeFirst();
        return node.getData();
    }

    public Integer getMinimum() {
        if (stack.isEmpty()) {
            throw new NoSuchElementException("Stack is empty");
        }
        return currentMin.getData();
    }
}

这是我的与O（1）一起运行的代码。在这里，我使用了向量对，其中包含推入的值，并且还包含直至此推入值的最小值。

这是我的C ++实现版本。

vector<pair<int,int> >A;
int sz=0; // to keep track of the size of vector

class MinStack
{
public:
    MinStack()
    {
        A.clear();
        sz=0;
    }

    void push(int x)
    {
        int mn=(sz==0)?x: min(A[sz-1].second,x); //find the minimum value upto this pushed value
        A.push_back(make_pair(x,mn));
        sz++; // increment the size
    }

    void pop()
    {
        if(sz==0) return;
        A.pop_back(); // pop the last inserted element
        sz--;  // decrement size
    }

    int top()
    {
        if(sz==0)   return -1;  // if stack empty return -1
        return A[sz-1].first;  // return the top element
    }

    int getMin()
    {
        if(sz==0) return -1;
        return A[sz-1].second; // return the minimum value at sz-1 
    }
};

    **The task can be acheived by creating two stacks:**



import java.util.Stack;
    /*
     * 
     * Find min in stack using O(n) Space Complexity
     */
    public class DeleteMinFromStack {

        void createStack(Stack<Integer> primary, Stack<Integer> minStack, int[] arr) {
    /* Create main Stack and in parallel create the stack which contains the minimum seen so far while creating main Stack */
            primary.push(arr[0]);
            minStack.push(arr[0]);

            for (int i = 1; i < arr.length; i++) {
                primary.push(arr[i]);
                if (arr[i] <= minStack.peek())// Condition to check to push the value in minimum stack only when this urrent value is less than value seen at top of this stack */
                    minStack.push(arr[i]);
            }

        }

        int findMin(Stack<Integer> secStack) {
            return secStack.peek();
        }

        public static void main(String args[]) {

            Stack<Integer> primaryStack = new Stack<Integer>();
            Stack<Integer> minStack = new Stack<Integer>();

            DeleteMinFromStack deleteMinFromStack = new DeleteMinFromStack();

            int[] arr = { 5, 5, 6, 8, 13, 1, 11, 6, 12 };
            deleteMinFromStack.createStack(primaryStack, minStack, arr);
            int mimElement = deleteMinFromStack.findMin(primaryStack, minStack);
    /** This check for algorithm when the main Stack Shrinks by size say i as in loop below */
            for (int i = 0; i < 2; i++) {
                primaryStack.pop();
            }

            System.out.println(" Minimum element is " + mimElement);
        }

    }
/*
here in have tried to add for loop wherin the main tack can be shrinked/expaned so we can check the algorithm */

一种在用户设计的对象堆栈中查找最小值的实用实现，名为：School

堆栈将根据在特定区域分配给学校的等级将堆栈中的学校存储在堆栈中，例如，findMin（）为学校提供了最大的招生申请数量，而该数量又由招生定义。比较器使用上一赛季与学校相关的等级。

The Code for same is below:


   package com.practical;

import java.util.Collections;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Stack;

public class CognitaStack {

    public School findMin(Stack<School> stack, Stack<School> minStack) {

        if (!stack.empty() && !minStack.isEmpty())
            return (School) minStack.peek();
        return null;
    }

    public School removeSchool(Stack<School> stack, Stack<School> minStack) {

        if (stack.isEmpty())
            return null;
        School temp = stack.peek();
        if (temp != null) {
            // if(temp.compare(stack.peek(), minStack.peek())<0){
            stack.pop();
            minStack.pop();
            // }

            // stack.pop();
        }
        return stack.peek();
    }

    public static void main(String args[]) {

        Stack<School> stack = new Stack<School>();
        Stack<School> minStack = new Stack<School>();

        List<School> lst = new LinkedList<School>();

        School s1 = new School("Polam School", "London", 3);
        School s2 = new School("AKELEY WOOD SENIOR SCHOOL", "BUCKINGHAM", 4);
        School s3 = new School("QUINTON HOUSE SCHOOL", "NORTHAMPTON", 2);
        School s4 = new School("OAKLEIGH HOUSE SCHOOL", " SWANSEA", 5);
        School s5 = new School("OAKLEIGH-OAK HIGH SCHOOL", "Devon", 1);
        School s6 = new School("BritishInter2", "Devon", 7);

        lst.add(s1);
        lst.add(s2);
        lst.add(s3);
        lst.add(s4);
        lst.add(s5);
        lst.add(s6);

        Iterator<School> itr = lst.iterator();
        while (itr.hasNext()) {
            School temp = itr.next();
            if ((minStack.isEmpty()) || (temp.compare(temp, minStack.peek()) < 0)) { // minStack.peek().equals(temp)
                stack.push(temp);
                minStack.push(temp);
            } else {
                minStack.push(minStack.peek());
                stack.push(temp);
            }

        }

        CognitaStack cogStack = new CognitaStack();
        System.out.println(" Minimum in Stack is " + cogStack.findMin(stack, minStack).name);
        cogStack.removeSchool(stack, minStack);
        cogStack.removeSchool(stack, minStack);

        System.out.println(" Minimum in Stack is "
                + ((cogStack.findMin(stack, minStack) != null) ? cogStack.findMin(stack, minStack).name : "Empty"));
    }

}

另外，学校对象如下：

package com.practical;

import java.util.Comparator;

public class School implements Comparator<School> {

    String name;
    String location;
    int rank;

    public School(String name, String location, int rank) {
        super();
        this.name = name;
        this.location = location;
        this.rank = rank;
    }

    @Override
    public int hashCode() {
        final int prime = 31;
        int result = 1;
        result = prime * result + ((location == null) ? 0 : location.hashCode());
        result = prime * result + ((name == null) ? 0 : name.hashCode());
        result = prime * result + rank;
        return result;
    }

    @Override
    public boolean equals(Object obj) {
        if (this == obj)
            return true;
        if (obj == null)
            return false;
        if (getClass() != obj.getClass())
            return false;
        School other = (School) obj;
        if (location == null) {
            if (other.location != null)
                return false;
        } else if (!location.equals(other.location))
            return false;
        if (name == null) {
            if (other.name != null)
                return false;
        } else if (!name.equals(other.name))
            return false;
        if (rank != other.rank)
            return false;
        return true;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public String getLocation() {
        return location;
    }

    public void setLocation(String location) {
        this.location = location;
    }

    public int getRank() {
        return rank;
    }

    public void setRank(int rank) {
        this.rank = rank;
    }

    public int compare(School o1, School o2) {
        // TODO Auto-generated method stub
        return o1.rank - o2.rank;
    }

}

class SchoolComparator implements Comparator<School> {

    public int compare(School o1, School o2) {
        return o1.rank - o2.rank;
    }

}

此示例涵盖以下内容：1.用户定义对象的堆栈的实现（此处为学校）2.使用要比较的对象的所有字段的hashcode（）和equals（）方法的实现3.针对场景的实际实现rqeuire获取堆栈包含操作的顺序为O（1）

这是Jon Skeet的答案中解释的PHP实现，它是获得O（1）中最大堆栈的空间复杂性稍好一些的实现。

<?php

/**
 * An ordinary stack implementation.
 *
 * In real life we could just extend the built-in "SplStack" class.
 */
class BaseIntegerStack
{
    /**
     * Stack main storage.
     *
     * @var array
     */
    private $storage = [];

    // ------------------------------------------------------------------------
    // Public API
    // ------------------------------------------------------------------------

    /**
     * Pushes to stack.
     *
     * @param  int $value New item.
     *
     * @return bool
     */
    public function push($value)
    {
        return is_integer($value)
            ? (bool) array_push($this->storage, $value)
            : false;
    }

    /**
     * Pops an element off the stack.
     *
     * @return int
     */
    public function pop()
    {
        return array_pop($this->storage);
    }

    /**
     * See what's on top of the stack.
     *
     * @return int|bool
     */
    public function top()
    {
        return empty($this->storage)
            ? false
            : end($this->storage);
    }

    // ------------------------------------------------------------------------
    // Magic methods
    // ------------------------------------------------------------------------

    /**
     * String representation of the stack.
     *
     * @return string
     */
    public function __toString()
    {
        return implode('|', $this->storage);
    }
} // End of BaseIntegerStack class

/**
 * The stack implementation with getMax() method in O(1).
 */
class Stack extends BaseIntegerStack
{
    /**
     * Internal stack to keep track of main stack max values.
     *
     * @var BaseIntegerStack
     */
    private $maxStack;

    /**
     * Stack class constructor.
     *
     * Dependencies are injected.
     *
     * @param BaseIntegerStack $stack Internal stack.
     *
     * @return void
     */
    public function __construct(BaseIntegerStack $stack)
    {
        $this->maxStack = $stack;
    }

    // ------------------------------------------------------------------------
    // Public API
    // ------------------------------------------------------------------------

    /**
     * Prepends an item into the stack maintaining max values.
     *
     * @param  int $value New item to push to the stack.
     *
     * @return bool
     */
    public function push($value)
    {
        if ($this->isNewMax($value)) {
            $this->maxStack->push($value);
        }

        parent::push($value);
    }

    /**
     * Pops an element off the stack maintaining max values.
     *
     * @return int
     */
    public function pop()
    {
        $popped = parent::pop();

        if ($popped == $this->maxStack->top()) {
            $this->maxStack->pop();
        }

        return $popped;
    }

    /**
     * Finds the maximum of stack in O(1).
     *
     * @return int
     * @see push()
     */
    public function getMax()
    {
        return $this->maxStack->top();
    }

    // ------------------------------------------------------------------------
    // Internal helpers
    // ------------------------------------------------------------------------

    /**
     * Checks that passing value is a new stack max or not.
     *
     * @param  int $new New integer to check.
     *
     * @return boolean
     */
    private function isNewMax($new)
    {
        return empty($this->maxStack) OR $new > $this->maxStack->top();
    }

} // End of Stack class

// ------------------------------------------------------------------------
// Stack Consumption and Test
// ------------------------------------------------------------------------
$stack = new Stack(
    new BaseIntegerStack
);

$stack->push(9);
$stack->push(4);
$stack->push(237);
$stack->push(5);
$stack->push(556);
$stack->push(15);

print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n\n";

print "Pop: {$stack->pop()}\n";
print "Pop: {$stack->pop()}\n\n";

print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n\n";

print "Pop: {$stack->pop()}\n";
print "Pop: {$stack->pop()}\n\n";

print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n";

// Here's the sample output:
//
// Stack: 9|4|237|5|556|15
// Max: 556
//
// Pop: 15
// Pop: 556
//
// Stack: 9|4|237|5
// Max: 237
//
// Pop: 5
// Pop: 237
//
// Stack: 9|4
// Max: 9

这是Jon Skeets Answer的C ++实现。它可能不是实现它的最佳方法，但它确实可以实现预期的效果。

class Stack {
private:
    struct stack_node {
        int val;
        stack_node *next;
    };
    stack_node *top;
    stack_node *min_top;
public:
    Stack() {
        top = nullptr;
        min_top = nullptr;
    }    
    void push(int num) {
        stack_node *new_node = nullptr;
        new_node = new stack_node;
        new_node->val = num;

        if (is_empty()) {
            top = new_node;
            new_node->next = nullptr;

            min_top = new_node;
            new_node->next = nullptr;
        } else {
            new_node->next = top;
            top = new_node;

            if (new_node->val <= min_top->val) {
                new_node->next = min_top;
                min_top = new_node;
            }
        }
    }

    void pop(int &num) {
        stack_node *tmp_node = nullptr;
        stack_node *min_tmp = nullptr;

        if (is_empty()) {
            std::cout << "It's empty\n";
        } else {
            num = top->val;
            if (top->val == min_top->val) {
                min_tmp = min_top->next;
                delete min_top;
                min_top = min_tmp;
            }
            tmp_node = top->next;
            delete top;
            top = tmp_node;
        }
    }

    bool is_empty() const {
        return !top;
    }

    void get_min(int &item) {
        item = min_top->val;
    }
};

这是该班的司机

int main() {
    int pop, min_el;
    Stack my_stack;

    my_stack.push(4);
    my_stack.push(6);
    my_stack.push(88);
    my_stack.push(1);
    my_stack.push(234);
    my_stack.push(2);

    my_stack.get_min(min_el);
    cout << "Min: " << min_el << endl;

    my_stack.pop(pop);
    cout << "Popped stock element: " << pop << endl;

    my_stack.pop(pop);
    cout << "Popped stock element: " << pop << endl;

    my_stack.pop(pop);
    cout << "Popped stock element: " << pop << endl;

    my_stack.get_min(min_el);
    cout << "Min: " << min_el << endl;

    return 0;
}

输出：

Min: 1
Popped stock element: 2
Popped stock element: 234
Popped stock element: 1
Min: 4

我们可以在O（n）时间和O（1）空间复杂度中做到这一点，如下所示：

class MinStackOptimized:
  def __init__(self):
      self.stack = []
      self.min = None

  def push(self, x): 
      if not self.stack:
          # stack is empty therefore directly add
          self.stack.append(x)
          self.min = x 
      else:
          """
          Directly add (x-self.min) to the stack. This also ensures anytime we have a 
          negative number on the stack is when x was less than existing minimum
          recorded thus far.
          """
          self.stack.append(x-self.min)
          if x < self.min:
              # Update x to new min
              self.min = x 

  def pop(self):
      x = self.stack.pop()
      if x < 0:
          """ 
          if popped element was negative therefore this was the minimum
          element, whose actual value is in self.min but stored value is what
          contributes to get the next min. (this is one of the trick we use to ensure
          we are able to get old minimum once current minimum gets popped proof is given
          below in pop method), value stored during push was:
          (x - self.old_min) and self.min = x therefore we need to backtrack
          these steps self.min(current) - stack_value(x) actually implies to
              x (self.min) - (x - self.old_min)
          which therefore gives old_min back and therefore can now be set
          back as current self.min.
          """
          self.min = self.min - x 

  def top(self):
      x = self.stack[-1]
      if x < 0:
          """ 
          As discussed above anytime there is a negative value on stack, this
          is the min value so far and therefore actual value is in self.min,
          current stack value is just for getting the next min at the time
          this gets popped.
          """
          return self.min
      else:
          """ 
          if top element of the stack was positive then it's simple, it was
          not the minimum at the time of pushing it and therefore what we did
          was x(actual) - self.min(min element at current stage) let's say `y`
          therefore we just need to reverse the process to get the actual
          value. Therefore self.min + y, which would translate to
              self.min + x(actual) - self.min, thereby giving x(actual) back
          as desired.
          """
          return x + self.min

  def getMin(self):
      # Always self.min variable holds the minimum so for so easy peezy.
      return self.min

我认为您可以在堆栈实现中简单地使用LinkedList。

第一次输入值时，将此值作为链表头。

那么每当您推送一个值时，如果新值<head.data，请执行预装操作（这意味着head变为新值）

如果不是，则执行追加操作。

制作pop（）时，请检查是否min == linkedlist.head.data，如果是，则检查head = head.next;。

这是我的代码。

public class Stack {

int[] elements;
int top;
Linkedlists min;

public Stack(int n) {
    elements = new int[n];
    top = 0;
    min = new Linkedlists();
}

public void realloc(int n) {
    int[] tab = new int[n];
    for (int i = 0; i < top; i++) {
        tab[i] = elements[i];
    }

    elements = tab;
}

public void push(int x) {
    if (top == elements.length) {
        realloc(elements.length * 2);
    }
    if (top == 0) {
        min.pre(x);
    } else if (x < min.head.data) {
        min.pre(x);
    } else {
        min.app(x);
    }
    elements[top++] = x;
}

public int pop() {

    int x = elements[--top];
    if (top == 0) {

    }
    if (this.getMin() == x) {
        min.head = min.head.next;
    }
    elements[top] = 0;
    if (4 * top < elements.length) {
        realloc((elements.length + 1) / 2);
    }

    return x;
}

public void display() {
    for (Object x : elements) {
        System.out.print(x + " ");
    }

}

public int getMin() {
    if (top == 0) {
        return 0;
    }
    return this.min.head.data;
}

public static void main(String[] args) {
    Stack stack = new Stack(4);
    stack.push(2);
    stack.push(3);
    stack.push(1);
    stack.push(4);
    stack.push(5);
    stack.pop();
    stack.pop();
    stack.pop();
    stack.push(1);
    stack.pop();
    stack.pop();
    stack.pop();
    stack.push(2);
    System.out.println(stack.getMin());
    stack.display();

}

 }

public class MinStack<E>{

    private final LinkedList<E> mainStack = new LinkedList<E>();
    private final LinkedList<E> minStack = new LinkedList<E>();
    private final Comparator<E> comparator;

    public MinStack(Comparator<E> comparator) 
    {
        this.comparator = comparator;
    }

    /**
     * Pushes an element onto the stack.
     *
     *
     * @param e the element to push
     */
    public void push(E e) {
        mainStack.push(e);
        if(minStack.isEmpty())
        {
            minStack.push(e);
        }
        else if(comparator.compare(e, minStack.peek())<=0)
        {
            minStack.push(e);
        }
        else
        {
            minStack.push(minStack.peek());
        }
    }

    /**
     * Pops an element from the stack.
     *
     *
     * @throws NoSuchElementException if this stack is empty
     */
    public E pop() {
       minStack.pop();
       return  mainStack.pop();
    }

    /**
     * Returns but not remove smallest element from the stack. Return null if stack is empty.
     *
     */
    public E getMinimum()
    {
        return minStack.peek();
    }

    @Override
    public String toString() {
        StringBuilder sb = new StringBuilder();
        sb.append("Main stack{");
        for (E e : mainStack) {         
            sb.append(e.toString()).append(",");
        }
        sb.append("}");

        sb.append(" Min stack{");
        for (E e : minStack) {          
            sb.append(e.toString()).append(",");
        }
        sb.append("}");

        sb.append(" Minimum = ").append(getMinimum());
        return sb.toString();
    }

    public static void main(String[] args) {
        MinStack<Integer> st = new MinStack<Integer>(Comparators.INTEGERS);

        st.push(2);
        Assert.assertTrue("2 is min in stack {2}", st.getMinimum().equals(2));
        System.out.println(st);

        st.push(6);
        Assert.assertTrue("2 is min in stack {2,6}", st.getMinimum().equals(2));
        System.out.println(st);

        st.push(4);
        Assert.assertTrue("2 is min in stack {2,6,4}", st.getMinimum().equals(2));
        System.out.println(st);

        st.push(1);
        Assert.assertTrue("1 is min in stack {2,6,4,1}", st.getMinimum().equals(1));
        System.out.println(st);

        st.push(5);
        Assert.assertTrue("1 is min in stack {2,6,4,1,5}", st.getMinimum().equals(1));
        System.out.println(st);

        st.pop();
        Assert.assertTrue("1 is min in stack {2,6,4,1}", st.getMinimum().equals(1));
        System.out.println(st);

        st.pop();
        Assert.assertTrue("2 is min in stack {2,6,4}", st.getMinimum().equals(2));
        System.out.println(st);

        st.pop();
        Assert.assertTrue("2 is min in stack {2,6}", st.getMinimum().equals(2));
        System.out.println(st);

        st.pop();
        Assert.assertTrue("2 is min in stack {2}", st.getMinimum().equals(2));
        System.out.println(st);

        st.pop();
        Assert.assertTrue("null is min in stack {}", st.getMinimum()==null);
        System.out.println(st);
    }
}

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;

namespace Solution 
{
    public class MinStack
    {
        public MinStack()
        {
            MainStack=new Stack<int>();
            Min=new Stack<int>();
        }

        static Stack<int> MainStack;
        static Stack<int> Min;

        public void Push(int item)
        {
            MainStack.Push(item);

            if(Min.Count==0 || item<Min.Peek())
                Min.Push(item);
        }

        public void Pop()
        {
            if(Min.Peek()==MainStack.Peek())
                Min.Pop();
            MainStack.Pop();
        }
        public int Peek()
        {
            return MainStack.Peek();
        }

        public int GetMin()
        {
            if(Min.Count==0)
                throw new System.InvalidOperationException("Stack Empty"); 
            return Min.Peek();
        }
    }
}

在这里看到了一个出色的解决方案：https : //www.geeksforgeeks.org/design-a-stack-that-supports-getmin-in-o1-time-and-o1-extra-space/

贝娄是我按照以下算法编写的python代码：

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None

class MinStack:
    def __init__(self):
        self.head = None
        self.min = float('inf')

    # @param x, an integer
    def push(self, x):
        if self.head == None:
            self.head = Node(x)
            self.min = x
        else:
            if x >= self.min:
                n = Node(x)
                n.next = self.head
                self.head = n
            else:
                v = 2 * x - self.min
                n = Node(v)
                n.next = self.head
                self.head = n
                self.min = x

    # @return nothing
    def pop(self):
        if self.head:
            if self.head.value < self.min:
                self.min = self.min * 2 - self.head.value
            self.head = self.head.next

    # @return an integer
    def top(self):
        if self.head:
            if self.head.value < self.min:
                self.min = self.min * 2 - self.head.value
                return self.min
            else:
                return self.head.value
        else:
            return -1

    # @return an integer
    def getMin(self):
        if self.head:
            return self.min
        else:
            return -1

从Stack获得MinMin元素。我们必须使用两个stack .ie Stack s1和Stack s2。

1. 最初，两个堆栈都是空的，因此向两个堆栈中添加元素

---------------------递归地调用步骤2到4 -----------------------

2. 如果将新元素添加到堆栈s1中，则从堆栈s2中弹出元素

3. 将新元素与s2比较。哪一个较小，请按s2。

4. 从堆栈s2中弹出（包含min元素）

代码如下：

package Stack;
import java.util.Stack;
public class  getMin 
{  

        Stack<Integer> s1= new Stack<Integer>();
        Stack<Integer> s2 = new Stack<Integer>();

        void push(int x)
        {
            if(s1.isEmpty() || s2.isEmpty())

            {
                 s1.push(x);
                 s2.push(x);
            }
            else
            {

               s1. push(x);
                int y = (Integer) s2.pop();
                s2.push(y);
                if(x < y)
                    s2.push(x);
                        }
        }
        public Integer pop()
        {
            int x;
            x=(Integer) s1.pop();
            s2.pop();
            return x;

        }
    public  int getmin()
        {
            int x1;
            x1= (Integer)s2.pop();
            s2.push(x1);
            return x1;
        }

    public static void main(String[] args) {
        getMin s = new getMin();
            s.push(10);
            s.push(20);
            s.push(30);
            System.out.println(s.getmin());
            s.push(1);
            System.out.println(s.getmin());
        }

}

我认为仅推动操作就受够了。我的实现包括一堆节点。每个节点都包含数据项以及该时刻的最小值。每次执行推送操作时都会更新此最小值。

以下是一些需要理解的要点：

• 我使用链接列表实现了堆栈。

• 指针顶部始终指向最后推送的项目。如果该堆栈中没有项目，则top为NULL。

• 推送项目时，将分配一个新节点，该节点具有指向上一堆栈的下一个指针，并且top会更新以指向此新节点。

与常规堆栈实现的唯一区别在于，在推入过程中，它将更新新节点的成员min。

请看一下出于演示目的在C ++中实现的代码。

/*
 *  Implementation of Stack that can give minimum in O(1) time all the time
 *  This solution uses same data structure for minimum variable, it could be implemented using pointers but that will be more space consuming
 */

#include <iostream>
using namespace std;

typedef struct stackLLNodeType stackLLNode;

struct stackLLNodeType {
    int item;
    int min;
    stackLLNode *next;
};

class DynamicStack {
private:
    int stackSize;
    stackLLNode *top;

public:
    DynamicStack();
    ~DynamicStack();
    void push(int x);
    int pop();
    int getMin();
    int size() { return stackSize; }
};

void pushOperation(DynamicStack& p_stackObj, int item);
void popOperation(DynamicStack& p_stackObj);

int main () {
    DynamicStack stackObj;

    pushOperation(stackObj, 3);
    pushOperation(stackObj, 1);
    pushOperation(stackObj, 2);
    popOperation(stackObj);
    popOperation(stackObj);
    popOperation(stackObj);
    popOperation(stackObj);
    pushOperation(stackObj, 4);
    pushOperation(stackObj, 7);
    pushOperation(stackObj, 6);
    popOperation(stackObj);
    popOperation(stackObj);
    popOperation(stackObj);
    popOperation(stackObj);

    return 0;
}

DynamicStack::DynamicStack() {
    // initialization
    stackSize = 0;
    top = NULL;
}

DynamicStack::~DynamicStack() {
    stackLLNode* tmp;
    // chain memory deallocation to avoid memory leak
    while (top) {
        tmp = top;
        top = top->next;
        delete tmp;
    }
}

void DynamicStack::push(int x) {
    // allocate memory for new node assign to top
    if (top==NULL) {
        top = new stackLLNode;
        top->item = x;
        top->next = NULL;
        top->min = top->item;
    }
    else {
        // allocation of memory
        stackLLNode *tmp = new stackLLNode;
        // assign the new item
        tmp->item = x;
        tmp->next = top;

        // store the minimum so that it does not get lost after pop operation of later minimum
        if (x < top->min)
            tmp->min = x;
        else
            tmp->min = top->min;

        // update top to new node
        top = tmp;
    }
    stackSize++;
}

int DynamicStack::pop() {
    // check if stack is empty
    if (top == NULL)
        return -1;

    stackLLNode* tmp = top;
    int curItem = top->item;
    top = top->next;
    delete tmp;
    stackSize--;
    return curItem;
}

int DynamicStack::getMin() {
    if (top == NULL)
        return -1;
    return top->min;
}
void pushOperation(DynamicStack& p_stackObj, int item) {
    cout<<"Just pushed: "<<item<<endl;
    p_stackObj.push(item);
    cout<<"Current stack min: "<<p_stackObj.getMin()<<endl;
    cout<<"Current stack size: "<<p_stackObj.size()<<endl<<endl;
}

void popOperation(DynamicStack& p_stackObj) {
    int popItem = -1;
    if ((popItem = p_stackObj.pop()) == -1 )
        cout<<"Cannot pop. Stack is empty."<<endl;
    else {
        cout<<"Just popped: "<<popItem<<endl;
        if (p_stackObj.getMin() == -1)
            cout<<"No minimum. Stack is empty."<<endl;
        else
            cout<<"Current stack min: "<<p_stackObj.getMin()<<endl;
        cout<<"Current stack size: "<<p_stackObj.size()<<endl<<endl;
    }
}

程序的输出如下所示：

Just pushed: 3
Current stack min: 3
Current stack size: 1

Just pushed: 1
Current stack min: 1
Current stack size: 2

Just pushed: 2
Current stack min: 1
Current stack size: 3

Just popped: 2
Current stack min: 1
Current stack size: 2

Just popped: 1
Current stack min: 3
Current stack size: 1

Just popped: 3
No minimum. Stack is empty.
Current stack size: 0

Cannot pop. Stack is empty.
Just pushed: 4
Current stack min: 4
Current stack size: 1

Just pushed: 7
Current stack min: 4
Current stack size: 2

Just pushed: 6
Current stack min: 4
Current stack size: 3

Just popped: 6
Current stack min: 4
Current stack size: 2

Just popped: 7
Current stack min: 4
Current stack size: 1

Just popped: 4
No minimum. Stack is empty.
Current stack size: 0

Cannot pop. Stack is empty.

public interface IMinStack<T extends Comparable<T>> {
  public void push(T val);
  public T pop();
  public T minValue();
  public int size();
}

import java.util.Stack;

public class MinStack<T extends Comparable<T>> implements IMinStack<T> {
  private Stack<T> stack = new Stack<T>();
  private Stack<T> minStack = new Stack<T>();

  @Override
  public void push(T val) {
    stack.push(val);
    if (minStack.isEmpty() || val.compareTo(minStack.peek()) < 0)
        minStack.push(val);
  }

  @Override
  public T pop() {
    T val = stack.pop();
    if ((false == minStack.isEmpty())
            && val.compareTo(minStack.peek()) == 0)
        minStack.pop();
    return val;
  }

  @Override
  public T minValue() {
    return minStack.peek();
  }

  @Override
  public int size() {
    return stack.size();
  }
}