design a stack such that getMinimum( ) should be O

Question

This is one of an interview question. You need to design a stack which holds an integer value such that getMinimum() function should return the minimum element in the stack.

For example: consider the below example

case #1

5  --> TOP
1
4
6
2

When getMinimum() is called it should return 1, which is the minimum element 
in the stack. 

case #2

stack.pop()
stack.pop()

Note: Both 5 and 1 are poped out of the stack. So after this, the stack
looks like,

4  --> TOP
6
2

When getMinimum() is called is should return 2 which is the minimum in the 
stack.

Constriants:

1. getMinimum should return the minimum value in O(1)
2. Space constraint also has to be considered while designing it and if you use extra space, it should be of constant space.

Answer 1

Here is my Code which runs with O(1). Here I used vector pair which contain the value which pushed and also contain the minimum value up to this pushed value.

Here is my version of C++ implementation.

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 
    }
};

Answer 2

Add a field to hold the minimum value and update it during Pop() and Push(). That way getMinimum() will be O(1), but Pop() and Push() will have to do a little more work.

If minimum value is popped, Pop() will be O(n), otherwise they will still both be O(1). When resizing Push() becomes O(n) as per the Stack implementation.

Here's a quick implementation

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; } }
}

Answer 3

Here is my solution in java using liked list.

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;
  }

}

Answer 4

 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);

}
}

Answer 5

We can do this in O(n) time and O(1) space complexity, like so:

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

Answer 6

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();
    }

}

It stores the current minimum explicitly, and if the minimum changes, instead of pushing the value, it pushes a value the same difference the other side of the new minimum ( if min = 7 and you push 5, it pushes 3 instead ( 5-|7-5| = 3) and sets min to 5; if you then pop 3 when min is 5 it sees that the popped value is less than min, so reverses the procedure to get 7 for the new min, then returns the previous min). As any value which doesn't cause a change the current minimum is greater than the current minimum, you have something that can be used to differentiate between values which change the minimum and ones which don't.

In languages which use fixed size integers, you're borrowing a bit of space from the representation of the values, so it may underflow and the assert will fail. But otherwise, it's constant extra space and all operations are still O(1).

Stacks which are based instead on linked lists have other places you can borrow a bit from, for example in C the least significant bit of the next pointer, or in Java the type of the objects in the linked list. For Java this does mean there's more space used compared to a contiguous stack, as you have the object overhead per link:

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;
    }

In C, the overhead isn't there, and you can borrow the lsb of the next pointer:

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.;

However, none of these are truly O(1). They don't require any more space in practice, because they exploit holes in the representations of numbers, objects or pointers in these languages. But a theoretical machine which used a more compact representation would require an extra bit to be added to that representation in each case.