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Given an array, print the Next Smaller Element (NSE) for every element. The NSE for an element x is the first smaller element on the right side of x in the array. Elements for which no smaller element exist (on the right side), consider NSE as -1.

Examples:

a) For any array, the rightmost element always has NSE as -1.
b) For an array that is sorted in increasing order, all elements have NSE as -1.
c) For the input array [4, 8, 5, 2, 25}, the NSE for each element is as follows.

Element         NSE
4      -->    2
8      -->    5
5      -->    2
2      -->   -1
25     -->   -1

d) For the input array [13, 7, 6, 12}, the next smaller elements for each element are as follows.

  Element        NSE
13      -->    7
7       -->    6
6       -->   -1
12      -->   -1

Method 1 (Simple):

Use two loops: The outer loop picks all the elements one by one. The inner loop looks for the first smaller element for the element picked by outer loop. If a smaller element is found then that element is printed as next, otherwise, -1 is printed.

## C++

 // Simple C++ program to print// next smaller elements in a given array#include "bits/stdc++.h"using namespace std; /* prints element and NSE pairfor all elements of arr[] of size n */void printNSE(int arr[], int n){    int next, i, j;    for (i = 0; i < n; i++)    {        next = -1;        for (j = i + 1; j < n; j++)        {            if (arr[i] > arr[j])            {                next = arr[j];                break;            }        }        cout << arr[i] << " -- "             << next << endl;    }} // Driver Codeint main(){    int arr[]= {11, 13, 21, 3};    int n = sizeof(arr) / sizeof(arr);    printNSE(arr, n);    return 0;} // This code is contributed by shivanisinghss2110

## C

 // Simple C program to print next smaller elements// in a given array#include /* prints element and NSE pair for all elements ofarr[] of size n */void printNSE(int arr[], int n){    int next, i, j;    for (i=0; i arr[j])            {                next = arr[j];                break;            }        }        printf("%d -- %d\n", arr[i], next);    }} int main(){    int arr[]= {11, 13, 21, 3};    int n = sizeof(arr)/sizeof(arr);    printNSE(arr, n);    return 0;}

## Java

 // Simple Java program to print next// smaller elements in a given array class Main {    /* prints element and NSE pair for     all elements of arr[] of size n */    static void printNSE(int arr[], int n)    {        int next, i, j;        for (i = 0; i < n; i++) {            next = -1;            for (j = i + 1; j < n; j++) {                if (arr[i] > arr[j]) {                    next = arr[j];                    break;                }            }            System.out.println(arr[i] + " -- " + next);        }    }     public static void main(String args[])    {        int arr[] = { 11, 13, 21, 3 };        int n = arr.length;        printNSE(arr, n);    }}

## Python

 # Function to print element and NSE pair for all elements of listdef printNSE(arr):     for i in range(0, len(arr), 1):         next = -1        for j in range(i + 1, len(arr), 1):            if arr[i] > arr[j]:                next = arr[j]                break                     print(str(arr[i]) + " -- " + str(next)) # Driver program to test above functionarr = [11, 13, 21, 3]printNSE(arr) # This code is contributed by Sunny Karira

## C#

 // Simple C# program to print next// smaller elements in a given arrayusing System; class GFG {     /* prints element and NSE pair for    all elements of arr[] of size n */    static void printNSE(int[] arr, int n)    {        int next, i, j;        for (i = 0; i < n; i++) {            next = -1;            for (j = i + 1; j < n; j++) {                if (arr[i] > arr[j]) {                    next = arr[j];                    break;                }            }            Console.WriteLine(arr[i] + " -- " + next);        }    }     // driver code    public static void Main()    {        int[] arr = { 11, 13, 21, 3 };        int n = arr.Length;         printNSE(arr, n);    }} // This code is contributed by Sam007

## PHP

  $arr[$j])            {                $next = $arr[$j]; break; } } echo $arr[$i]." -- ". $next."\n";             }}     // Driver Code    $arr= array(11, 13, 21, 3); $n = count($arr); printNSE($arr, \$n);     // This code is contributed by Sam007?>

## Javascript

 

Output

11 -- 3
13 -- 3
21 -- 3
3 -- -1

Time Complexity : The worst case occurs when all elements are sorted in increasing order.

Auxiliary Space: O(1):  As constant extra space is used

Method 2 (Using Segment Tree and Binary Search)

This method is also pretty simple if one knows Segment trees and Binary Search. Lets consider an array and lets suppose NSE for is , we simply need to binary search for in range to  will be the first index , such that range minimum of elements from index to ( ) is lesser than .

Example

## C++

 #include using namespace std; // Program to find next smaller element for all elements in// an array, using segment tree and binary search // --------Segment Tree Starts Here----------------- vector<int> seg_tree; // combine function for combining two nodes of the tree, in// this case we need to take min of twoint combine(int a, int b) { return min(a, b); } // build function, builds seg_tree based on vector parameter// arrvoid build(vector<int>& arr, int node, int tl, int tr){    // if current range consists only of one element, then    // node should be this element    if (tl == tr) {        seg_tree[node] = arr[tl];    }    else {        // divide the build operations into two parts        int tm = (tr - tl) / 2 + tl;         build(arr, 2 * node, tl, tm);        build(arr, 2 * node + 1, tm + 1, tr);         // combine the results from two parts, and store it        // into current node        seg_tree[node] = combine(seg_tree[2 * node],                                 seg_tree[2 * node + 1]);    }} // query function, returns minimum in the range [l, r]int query(int node, int tl, int tr, int l, int r){    // if range is invalid, then return infinity    if (l > r) {        return INT32_MAX;    }     // if range completely aligns with a segment tree node,    // then value of this node should be returned    if (l == tl && r == tr) {        return seg_tree[node];    }     // else divide the query into two parts    int tm = (tr - tl) / 2 + tl;     int q1 = query(2 * node, tl, tm, l, min(r, tm));    int q2 = query(2 * node + 1, tm + 1, tr, max(l, tm + 1),                   r);     // and combine the results from the two parts and return    // it    return combine(q1, q2);} // --------Segment Tree Ends Here----------------- void printNSE(vector<int> arr, int n){    seg_tree = vector<int>(4 * n);     // build segment tree initially    build(arr, 1, 0, n - 1);     int q, l, r, mid, ans;    for (int i = 0; i < n; i++) {        // binary search for ans in range [i + 1, n - 1],        // initially ans is -1 representing there is no NSE        // for this element        l = i + 1;        r = n - 1;        ans = -1;         while (l <= r) {            mid = (r - l) / 2 + l;            // q is the minimum element in range [l, mid]            q = query(1, 0, n - 1, l, mid);             // if the minimum element in range [l, mid] is            // less than arr[i], then mid can be answer, we            // mark it, and look for a better answer in left            // half. Else if q is greater than arr[i], mid            // can't be an answer, we should search in right            // half             if (q < arr[i]) {                ans = arr[mid];                r = mid - 1;            }            else {                l = mid + 1;            }        }         // print NSE for arr[i]        cout << arr[i] << " ---> " << ans << "\n";    }} // Driver program to test above functionsint main(){    vector<int> arr = { 11, 13, 21, 3 };    printNSE(arr, 4);    return 0;}

## Java

 // Program to find next smaller element for all elements in// an array, using segment tree and binary search // --------Segment Tree Starts Here----------------- import java.util.*; class GFG {   static int[] seg_tree;   // combine function for combining two nodes of the tree, in  // this case we need to take min of two  static int combine(int a, int b) {    return Math.min(a, b);  }   // build function, builds seg_tree based on vector parameter  // arr  static void build(int[] arr, int node, int tl, int tr)  {    // if current range consists only of one element, then    // node should be this element    if (tl == tr) {      seg_tree[node] = arr[tl];    }    else {      // divide the build operations into two parts      int tm = (tr - tl) / 2 + tl;       build(arr, 2 * node, tl, tm);      build(arr, 2 * node + 1, tm + 1, tr);       // combine the results from two parts, and store it      // into current node      seg_tree[node] = combine(seg_tree[2 * node],seg_tree[2 * node + 1]);    }  }   // query function, returns minimum in the range [l, r]  static int query(int node, int tl, int tr, int l, int r)  {    // if range is invalid, then return infinity    if (l > r) {      return Integer.MAX_VALUE;    }     // if range completely aligns with a segment tree node,    // then value of this node should be returned    if (l == tl && r == tr) {      return seg_tree[node];    }     // else divide the query into two parts    int tm = (tr - tl) / 2 + tl;     int q1 = query(2 * node, tl, tm, l, Math.min(r, tm));    int q2 = query(2 * node + 1, tm + 1, tr, Math.max(l, tm + 1),r);     // and combine the results from the two parts and return    // it    return combine(q1, q2);  }   // --------Segment Tree Ends Here-----------------   static void printNSE(int[] arr, int n)  {    seg_tree = new int[4 * n];     // build segment tree initially    build(arr, 1, 0, n - 1);     int q, l, r, mid, ans;    for (int i = 0; i < n; i++) {      // binary search for ans in range [i + 1, n - 1],      // initially ans is -1 representing there is no NSE      // for this element      l = i + 1;      r = n - 1;      ans = -1;       while (l <= r) {        mid = (r - l) / 2 + l;        // q is the minimum element in range [l, mid]        q = query(1, 0, n - 1, l, mid);         // if the minimum element in range [l, mid] is        // less than arr[i], then mid can be answer, we        // mark it, and look for a better answer in left        // half. Else if q is greater than arr[i], mid        // can't be an answer, we should search in right        // half         if (q < arr[i]) {          ans = arr[mid];          r = mid - 1;        }        else {          l = mid + 1;        }      }       // print NSE for arr[i]      System.out.println(arr[i] + " ---> " + ans);    }  }  public static void main(String[] args) {    int[] arr = { 11, 13, 21, 3 };    printNSE(arr, 4);  }} // This code is contributed by aadityaburujwale.

## Python3

 # Program to find next smaller element for all elements in# an array, using segment tree and binary searchimport math # --------Segment Tree Starts Here-----------------seg_tree = [] def combine(a, b):    return min(a, b) def build(arr, node, tl, tr):    # if current range consists only of one element, then    # node should be this element    if tl == tr:        seg_tree[node] = arr[tl]    else:        # divide the build operations into two parts        tm = (tr - tl) // 2 + tl         build(arr, 2 * node, tl, tm)        build(arr, 2 * node + 1, tm + 1, tr)         # combine the results from two parts, and store it        # into current node        seg_tree[node] = combine(seg_tree[2 * node], seg_tree[2 * node + 1])  def query(node, tl, tr, l, r):    # if range is invalid, then return infinity    if l > r:        return float('inf')     # if range completely aligns with a segment tree node,    # then value of this node should be returned    if l == tl and r == tr:        return seg_tree[node]     # else divide the query into two parts    tm = (tr - tl) // 2 + tl     q1 = query(2 * node, tl, tm, l, min(r, tm))    q2 = query(2 * node + 1, tm + 1, tr, max(l, tm + 1), r)     # and combine the results from the two parts and return    # it    return combine(q1, q2) # --------Segment Tree Ends Here-----------------  def printNSE(arr, n):    global seg_tree    seg_tree =  * (4 * n)     # build segment tree initially    build(arr, 1, 0, n - 1)     for i in range(n):        # binary search for ans in range [i + 1, n - 1],        # initially ans is -1 representing there is no NSE        # for this element        l = i + 1        r = n - 1        ans = -1         while l <= r:            mid = (r - l) // 2 + l            # q is the minimum element in range [l, mid]            q = query(1, 0, n - 1, l, mid)             # if the minimum element in range [l, mid] is            # less than arr[i], then mid can be answer, we            # mark it, and look for a better answer in left            # half. Else if q is greater than arr[i], mid            # can't be an answer, we should search in right            # half             if q < arr[i]:                ans = arr[mid]                r = mid - 1            else:                l = mid + 1         # print NSE for arr[i]        print(arr[i], "-->", ans)  arr = [11, 13, 21, 3]printNSE(arr, 4) # This code is contributed by lokeshmvs21.

## C#

 // Program to find next smaller element for all elements in// an array, using segment tree and binary search // --------Segment Tree Starts Here-----------------using System; public class GFG {   static int[] seg_tree;   // combine function for combining two nodes of the tree,  // in  // this case we need to take min of two  static int combine(int a, int b)  {    return Math.Min(a, b);  }   // build function, builds seg_tree based on vector  // parameter arr  static void build(int[] arr, int node, int tl, int tr)  {    // if current range consists only of one element,    // then node should be this element    if (tl == tr) {      seg_tree[node] = arr[tl];    }    else {      // divide the build operations into two parts      int tm = (tr - tl) / 2 + tl;       build(arr, 2 * node, tl, tm);      build(arr, 2 * node + 1, tm + 1, tr);       // combine the results from two parts, and store      // it into current node      seg_tree[node] = combine(        seg_tree[2 * node], seg_tree[2 * node + 1]);    }  }   // query function, returns minimum in the range [l, r]  static int query(int node, int tl, int tr, int l, int r)  {    // if range is invalid, then return infinity    if (l > r) {      return Int32.MaxValue;    }     // if range completely aligns with a segment tree    // node, then value of this node should be returned    if (l == tl && r == tr) {      return seg_tree[node];    }     // else divide the query into two parts    int tm = (tr - tl) / 2 + tl;     int q1      = query(2 * node, tl, tm, l, Math.Min(r, tm));    int q2 = query(2 * node + 1, tm + 1, tr,                   Math.Max(l, tm + 1), r);     // and combine the results from the two parts and    // return it    return combine(q1, q2);  }   // --------Segment Tree Ends Here-----------------   static void printNSE(int[] arr, int n)  {    seg_tree = new int[4 * n];     // build segment tree initially    build(arr, 1, 0, n - 1);     int q, l, r, mid, ans;    for (int i = 0; i < n; i++) {      // binary search for ans in range [i + 1, n -      // 1], initially ans is -1 representing there is      // no NSE for this element      l = i + 1;      r = n - 1;      ans = -1;       while (l <= r) {        mid = (r - l) / 2 + l;        // q is the minimum element in range [l,        // mid]        q = query(1, 0, n - 1, l, mid);         // if the minimum element in range [l, mid]        // is less than arr[i], then mid can be        // answer, we mark it, and look for a better        // answer in left half. Else if q is greater        // than arr[i], mid can't be an answer, we        // should search in right half         if (q < arr[i]) {          ans = arr[mid];          r = mid - 1;        }        else {          l = mid + 1;        }      }       // print NSE for arr[i]      Console.WriteLine(arr[i] + " ---> " + ans);    }  }   static public void Main()  {     // Code    int[] arr = { 11, 13, 21, 3 };    printNSE(arr, 4);  }} // This code is contributed by lokeshmvs21.

## Javascript

 // Program to find next smaller element for all elements in// an array, using segment tree and binary search // combine function for combining two nodes of the tree, in// this case we need to take min of twofunction combine(a, b) {    return Math.min(a, b);} // build function, builds seg_tree// based on vector parameter arrfunction build(arr, node, tl, tr) {         // if current range consists only of one element, then    // node should be this element    if (tl === tr) {        seg_tree[node] = arr[tl];    }    else {           // divide the build operations into two parts        var tm = Math.floor((tr - tl) / 2 + tl);        build(arr, 2 * node, tl, tm);        build(arr, 2 * node + 1, tm + 1, tr);             // combine the results from two parts, and store it        // into current node        seg_tree[node] = combine(seg_tree[2 * node], seg_tree[2 * node + 1]);    }} // query function, returns minimum in the range [l, r]function query(node, tl, tr, l, r) {     // if range is invalid, then return infinity    if (l > r) {        return Number.MAX_SAFE_INTEGER;    }     // if range completely aligns with a segment tree node,    // then value of this node should be returned    if (l === tl && r === tr) {        return seg_tree[node];    }     // else divide the query into two parts    var tm = Math.floor((tr - tl) / 2 + tl);    var q1 = query(2 * node, tl, tm, l, Math.min(r, tm));    var q2 = query(2 * node + 1, tm + 1, tr, Math.max(l, tm + 1), r);     // and combine the results from the    // two parts and return it    return combine(q1, q2);} // --------Segment Tree Ends Here----------------- function printNSE(arr, n) {    seg_tree = new Array(4 * n);       // build segment tree initially    build(arr, 1, 0, n - 1);    var q, l, r, mid, ans;    for (var i = 0; i < n; i++) {           // binary search for ans in range [i + 1, n - 1],        // initially ans is -1 representing there is no NSE        // for this element        l = i + 1;        r = n - 1;        ans = -1;         while (l <= r) {            mid = Math.floor((r - l) / 2 + l);             // q is the minimum element in range [l, mid]            q = query(1, 0, n - 1, l, mid);             // if the minimum element in range [l, mid] is            // less than arr[i], then mid can be answer, we            // mark it, and look for a better answer in left            // half. Else if q is greater than arr[i], mid            // can't be an answer, we should search in right            // half            if (q < arr[i]) {                ans = arr[mid];                r = mid - 1;            }            else {                l = mid + 1;            }        }             // print NSE for arr[i]        console.log(arr[i] + " ---> " + ans);    }} // Driver program to test above functionsvar arr = [11, 13, 21, 3];printNSE(arr, 4); // This code is contributed by Akash Bankar (thebeginner01)

Output

11 ---> 3
13 ---> 3
21 ---> 3
3 ---> -1

Time Complexity : For each of array elements we do a binary search, which includes steps, and each step costs operations [range minimum queries].

Auxiliary Space: O(N)

As extra space is used for storing the elements of the segment tree.

Method 3 (Using Segment Tree and Coordinate Compression)

In this approach, we build a segment tree on indices of compressed array elements:

1. Somewhere along the lines, we would build a array such-that is the smallest index at which is present in input array.
2. Its easy to see that we need to compress the input array so as to build this array because if exceeds (memory limit of online judge) chances are we would get a segmentation fault.
3. To compress we sort the input array, and then for each new value seen in array we map it to a corresponding smaller value, if possible. Use these mapped values to generate a array with same order as input array.
4. So now that we are done with compression, we can begin with the query part:
• Suppose in previous step, we compressed the array to distinct values. Initially set , this signifies no value is processed at any index as of now.
• Traverse the compressed array in reverse order, this would imply that in past we would have only processed elements that are on the right side.
• For , query (and store in ) the smallest index of values using segment tree, this must be the NSE for !
• Update the index of to .
5. We stored the index of NSEs for all array elements, we can easily print NSEs themselves as shown in code.

Note: In implementation we use INT32_MAX instead of -1 because storing INT32_MAX doesn’t affect our min-segment tree and still serves the purpose of identifying unprocessed values.

As extra space is used for storing the elements of the segment tree.

## C++

 #include using namespace std; // Program to find next smaller element for all elements in// an array, using segment tree and coordinate compression // --------Segment Tree Starts Here----------------- vector<int> seg_tree; // combine function for combining two nodes of the tree, in// this case we need to take min of twoint combine(int a, int b) { return min(a, b); } // build function, builds seg_tree based on vector parameter// arrvoid build(vector<int>& arr, int node, int tl, int tr){    // if current range consists only of one element, then    // node should be this element    if (tl == tr) {        seg_tree[node] = arr[tl];    }    else {        // divide the build operations into two parts        int tm = (tr - tl) / 2 + tl;         build(arr, 2 * node, tl, tm);        build(arr, 2 * node + 1, tm + 1, tr);         // combine the results from two parts, and store it        // into current node        seg_tree[node] = combine(seg_tree[2 * node],                                 seg_tree[2 * node + 1]);    }} // update function, used to make a point update, update// arr[pos] to new_val and make required changes to segtreevoid update(int node, int tl, int tr, int pos, int new_val){    // if current range only contains one point, this must    // be arr[pos], update the corresponding node to new_val    if (tl == tr) {        seg_tree[node] = new_val;    }    else {        // else divide the range into two parts        int tm = (tr - tl) / 2 + tl;         // if pos lies in first half, update this half, else        // update second half        if (pos <= tm) {            update(2 * node, tl, tm, pos, new_val);        }        else {            update(2 * node + 1, tm + 1, tr, pos, new_val);        }         // combine results from both halves        seg_tree[node] = combine(seg_tree[2 * node],                                 seg_tree[2 * node + 1]);    }} // query function, returns minimum in the range [l, r]int query(int node, int tl, int tr, int l, int r){    // if range is invalid, then return infinity    if (l > r) {        return INT32_MAX;    }     // if range completely aligns with a segment tree node,    // then value of this node should be returned    if (l == tl && r == tr) {        return seg_tree[node];    }     // else divide the query into two parts    int tm = (tr - tl) / 2 + tl;     int q1 = query(2 * node, tl, tm, l, min(r, tm));    int q2 = query(2 * node + 1, tm + 1, tr, max(l, tm + 1),                   r);     // and combine the results from the two parts and return    // it    return combine(q1, q2);} // --------Segment Tree Ends Here----------------- void printNSE(vector<int> original, int n){    vector<int> sorted(n);    map<int, int> encode;     // -------Coordinate Compression Starts Here ------     // created a temporary sorted array out of original    for (int i = 0; i < n; i++) {        sorted[i] = original[i];    }    sort(sorted.begin(), sorted.end());     // encode each value to a new value in sorted array    int ctr = 0;    for (int i = 0; i < n; i++) {        if (encode.count(sorted[i]) == 0) {            encode[sorted[i]] = ctr++;        }    }     // use encode to compress original array    vector<int> compressed(n);    for (int i = 0; i < n; i++) {        compressed[i] = encode[original[i]];    }     // -------Coordinate Compression Ends Here ------     // Create an aux array of size ctr, and build a segtree    // based on this array     vector<int> aux(ctr, INT32_MAX);    seg_tree = vector<int>(4 * ctr);     build(aux, 1, 0, ctr - 1);     // For each compressed[i], query for index of NSE and    // update segment tree     vector<int> ans(n);    for (int i = n - 1; i >= 0; i--) {        ans[i] = query(1, 0, ctr - 1, 0, compressed[i] - 1);        update(1, 0, ctr - 1, compressed[i], i);    }     // Print -1 if NSE doesn't exist, otherwise print NSE    // itself     for (int i = 0; i < n; i++) {        cout << original[i] << " ---> ";        if (ans[i] == INT32_MAX) {            cout << -1;        }        else {            cout << original[ans[i]];        }        cout << "\n";    }} // Driver program to test above functionsint main(){    vector<int> arr = { 11, 13, 21, 3 };    printNSE(arr, 4);    return 0;}

## Java

 // Java code to implement the above approachimport java.io.*;import java.util.*; class GFG {   // Program to find next smaller element for all elements  // in  // an array, using segment tree and coordinate  // compression   // --------Segment Tree Starts Here-----------------  static int[] seg_tree;   // combine function for combining two nodes of the tree,  // in  // this case we need to take min of two  static int combine(int a, int b)  {    return Math.min(a, b);  }   // build function, builds seg_tree based on vector  // parameter  // arr  static void build(int[] arr, int node, int tl, int tr)  {    // if current range consists only of one element,    // then    // node should be this element    if (tl == tr) {      seg_tree[node] = arr[tl];    }    else {      // divide the build operations into two parts      int tm = (tr - tl) / 2 + tl;       build(arr, 2 * node, tl, tm);      build(arr, 2 * node + 1, tm + 1, tr);       // combine the results from two parts, and store      // it into current node      seg_tree[node] = combine(        seg_tree[2 * node], seg_tree[2 * node + 1]);    }  }   // update function, used to make a point update, update  // arr[pos] to new_val and make required changes to  // segtree  static void update(int node, int tl, int tr, int pos,                     int new_val)  {    // if current range only contains one point, this    // must    // be arr[pos], update the corresponding node to    // new_val    if (tl == tr) {      seg_tree[node] = new_val;    }    else {      // else divide the range into two parts      int tm = (tr - tl) / 2 + tl;       // if pos lies in first half, update this half,      // else update second half      if (pos <= tm) {        update(2 * node, tl, tm, pos, new_val);      }      else {        update(2 * node + 1, tm + 1, tr, pos,               new_val);      }       // combine results from both halves      seg_tree[node] = combine(        seg_tree[2 * node], seg_tree[2 * node + 1]);    }  }   // query function, returns minimum in the range [l, r]  static int query(int node, int tl, int tr, int l, int r)  {    // if range is invalid, then return infinity    if (l > r) {      return Integer.MAX_VALUE;    }     // if range completely aligns with a segment tree    // node,    // then value of this node should be returned    if (l == tl && r == tr) {      return seg_tree[node];    }     // else divide the query into two parts    int tm = (tr - tl) / 2 + tl;     int q1      = query(2 * node, tl, tm, l, Math.min(r, tm));    int q2 = query(2 * node + 1, tm + 1, tr,                   Math.max(l, tm + 1), r);     // and combine the results from the two parts and    // return it    return combine(q1, q2);  }   // --------Segment Tree Ends Here-----------------   static void printNSE(int[] original, int n)  {    int[] sorted = new int[n];    HashMap encode = new HashMap<>();     // -------Coordinate Compression Starts Here ------     // created a temporary sorted array out of original    for (int i = 0; i < n; i++) {      sorted[i] = original[i];    }    Arrays.sort(sorted);     // encode each value to a new value in sorted array    int ctr = 0;    for (int i = 0; i < n; i++) {      if (!encode.containsKey(sorted[i])) {        encode.put(sorted[i], ctr++);      }    }     // use encode to compress original array    int[] compressed = new int[n];    for (int i = 0; i < n; i++) {      compressed[i] = encode.get(original[i]);    }     // -------Coordinate Compression Ends Here ------     // Create an aux array of size ctr, and build a    // segtree based on this array     int[] aux = new int[ctr];    for (int i = 0; i < ctr; i++) {      aux[i] = Integer.MAX_VALUE;    }    seg_tree = new int[4 * ctr];     build(aux, 1, 0, ctr - 1);     // For each compressed[i], query for index of NSE    // and    // update segment tree     int[] ans = new int[n];     for (int i = n - 1; i >= 0; i--) {      ans[i] = query(1, 0, ctr - 1, 0,                     compressed[i] - 1);      update(1, 0, ctr - 1, compressed[i], i);    }     // Print -1 if NSE doesn't exist, otherwise print    // NSE    // itself     for (int i = 0; i < n; i++) {      System.out.print(original[i] + " ---> ");      if (ans[i] == Integer.MAX_VALUE) {        System.out.println(-1);      }      else {        System.out.println(original[ans[i]]);      }    }  }   public static void main(String[] args)  {    int[] arr = { 11, 13, 21, 3 };    printNSE(arr, 4);  }} // This code is contributed by lokesh.

## C#

 // C# code to implement the above approach using System;using System.Collections;using System.Collections.Generic; public class GFG {     // Program to find next smaller element for all elements    // in an array, using segment tree and coordinate    // compression     // --------Segment Tree Starts Here-----------------    static int[] seg_tree;     // combine function for combining two nodes of the tree,    // in this case we need to take min of two    static int combine(int a, int b)    {        return Math.Min(a, b);    }     // build function, builds seg_tree based on vector    // parameter arr    static void build(int[] arr, int node, int tl, int tr)    {        // if current range consists only of one element,        // then node should be this element        if (tl == tr) {            seg_tree[node] = arr[tl];        }        else {            // divide the build operations into two parts            int tm = (tr - tl) / 2 + tl;             build(arr, 2 * node, tl, tm);            build(arr, 2 * node + 1, tm + 1, tr);             // combine the results from two parts, and store            // it into current node            seg_tree[node] = combine(                seg_tree[2 * node], seg_tree[2 * node + 1]);        }    }     // update function, used to make a point update, update    // arr[pos] to new_val and make required changes to    // segtree    static void update(int node, int tl, int tr, int pos,                       int new_val)    {        // if current range only contains one point, this        // must be arr[pos], update the corresponding node        // to new_val        if (tl == tr) {            seg_tree[node] = new_val;        }        else {            // else divide the range into two parts            int tm = (tr - tl) / 2 + tl;             // if pos lies in first half, update this half,            // else update second half            if (pos <= tm) {                update(2 * node, tl, tm, pos, new_val);            }            else {                update(2 * node + 1, tm + 1, tr, pos,                       new_val);            }             // combine results from both halves            seg_tree[node] = combine(                seg_tree[2 * node], seg_tree[2 * node + 1]);        }    }     // query function, returns minimum in the range [l, r]    static int query(int node, int tl, int tr, int l, int r)    {        // if range is invalid, then return infinity        if (l > r) {            return Int32.MaxValue;        }         // if range completely aligns with a segment tree        // node, then value of this node should be returned        if (l == tl && r == tr) {            return seg_tree[node];        }         // else divide the query into two parts        int tm = (tr - tl) / 2 + tl;         int q1            = query(2 * node, tl, tm, l, Math.Min(r, tm));        int q2 = query(2 * node + 1, tm + 1, tr,                       Math.Max(l, tm + 1), r);         // and combine the results from the two parts and        // return it        return combine(q1, q2);    }     // --------Segment Tree Ends Here-----------------     static void printNSE(int[] original, int n)    {        int[] sorted = new int[n];        Dictionary<int, int> encode            = new Dictionary<int, int>();         // -------Coordinate Compression Starts Here ------         // created a temporary sorted array out of original        for (int i = 0; i < n; i++) {            sorted[i] = original[i];        }        Array.Sort(sorted);         // encode each value to a new value in sorted array        int ctr = 0;        for (int i = 0; i < n; i++) {            if (!encode.ContainsKey(sorted[i])) {                encode.Add(sorted[i], ctr++);            }        }         // use encode to compress original array        int[] compressed = new int[n];        for (int i = 0; i < n; i++) {            compressed[i] = encode[original[i]];        }         // -------Coordinate Compression Ends Here ------         // Create an aux array of size ctr, and build a        // segtree based on this array         int[] aux = new int[ctr];        for (int i = 0; i < ctr; i++) {            aux[i] = Int32.MaxValue;        }        seg_tree = new int[4 * ctr];         build(aux, 1, 0, ctr - 1);         // For each compressed[i], query for index of NSE        // and update segment tree         int[] ans = new int[n];         for (int i = n - 1; i >= 0; i--) {            ans[i] = query(1, 0, ctr - 1, 0,                           compressed[i] - 1);            update(1, 0, ctr - 1, compressed[i], i);        }         // Print -1 if NSE doesn't exist, otherwise print        // NSE itself         for (int i = 0; i < n; i++) {            Console.Write(original[i] + " ---> ");            if (ans[i] == Int32.MaxValue) {                Console.WriteLine(-1);            }            else {                Console.WriteLine(original[ans[i]]);            }        }    }     static public void Main()    {         // Code        int[] arr = { 11, 13, 21, 3 };        printNSE(arr, 4);    }} // This code is contributed by lokesh.

## Python3

 # Program to find next smaller element for all elements in# an array, using segment tree and coordinate compression # --------Segment Tree Starts Here----------------- seg_tree = [] # combine function for combining two nodes of the tree, in# this case we need to take min of twodef combine(a, b):    return min(a, b) # build function, builds seg_tree based on vector parameter# arrdef build(arr, node, tl, tr):         # if current range consists only of one element, then    # node should be this element    if tl == tr:        seg_tree[node] = arr[tl]    else:        # divide the build operations into two parts        tm = (tr - tl)//2 + tl                 build(arr, 2 * node, tl, tm)        build(arr, 2 * node + 1, tm + 1, tr)                 # combine the results from two parts, and store it        # into current node        seg_tree[node] = combine(seg_tree[2 * node],                                seg_tree[2 * node + 1]) # update function, used to make a point update, update# arr[pos] to new_val and make required changes to segtreedef update(node, tl, tr, pos, new_val):         # if current range only contains one point, this must    # be arr[pos], update the corresponding node to new_val    if tl == tr:        seg_tree[node] = new_val    else:        # else divide the range into two parts        tm = (tr - tl)//2 + tl                 # if pos lies in first half, update this half, else        # update second half        if pos <= tm:            update(2 * node, tl, tm, pos, new_val)        else:            update(2 * node + 1, tm + 1, tr, pos, new_val)                 # combine results from both halves        seg_tree[node] = combine(seg_tree[2 * node],                            seg_tree[2 * node + 1]) # query function, returns minimum in the range [l, r]def query(node, tl, tr, l, r):         # if range is invalid, then return infinity    if l > r:        return float("inf")         # if range completely aligns with a segment tree node,    # then value of this node should be returned    if l == tl and r == tr:        return seg_tree[node]         # else divide the query into two parts    tm = (tr - tl)//2 + tl         q1 = query(2 * node, tl, tm, l, min(r, tm))    q2 = query(2 * node + 1, tm + 1, tr, max(l, tm + 1), r)         # and combine the results from the two parts and return    # it    return combine(q1, q2) # --------Segment Tree Ends Here----------------- def printNSE(original, n):    sorted = *n    encode = {}     # -------Coordinate Compression Starts Here ------     # created a temporary sorted array out of original    for i in range(n):        sorted[i] = original[i]    sorted.sort()     # encode each value to a new value in sorted array    ctr = 0    for i in range(n):        if sorted[i] not in encode.keys():            encode[sorted[i]] = ctr            ctr += 1         # use encode to compress original array    compressed = *n    for i in range(n):        compressed[i] = encode[original[i]]     # -------Coordinate Compression Ends Here ------     # Create an aux array of size ctr, and build a segtree    # based on this array     aux = [float("inf")]*ctr    seg_tree[:] = [float("inf")]*4*ctr     build(aux, 1, 0, ctr - 1)     # For each compressed[i], query for index of NSE and    # update segment tree     ans = *n    for i in range(n-1, -1, -1):        ans[i] = query(1, 0, ctr - 1, 0, compressed[i] - 1)        update(1, 0, ctr - 1, compressed[i], i)     # Print -1 if NSE doesn't exist, otherwise print NSE    # itself     for i in range(n):        print(original[i], " ---> ", end = "")        if ans[i] == float("inf"):            print(-1, end = "")        else:            print(original[ans[i]], end = "")        print() # Driver program to test above functionsif __name__ == '__main__':    arr = [11, 13, 21, 3]    printNSE(arr, 4)

## Javascript

 // Program to find next smaller element for all elements in// an array, using segment tree and coordinate compression // --------Segment Tree Starts Here----------------- let seg_tree = []; // combine function for combining two nodes of the tree, in// this case we need to take min of twofunction combine(a, b) {    return Math.min(a, b);} // build function, builds seg_tree based on vector parameter// arrfunction build(arr, node, tl, tr) {         // if current range consists only of one element, then    // node should be this element    if (tl === tr) {        seg_tree[node] = arr[tl];    } else {        // divide the build operations into two parts        let tm = Math.floor((tr - tl)/2) + tl;                 build(arr, 2 * node, tl, tm);        build(arr, 2 * node + 1, tm + 1, tr);                 // combine the results from two parts, and store it        // into current node        seg_tree[node] = combine(seg_tree[2 * node],                                seg_tree[2 * node + 1]);    }} // update function, used to make a point update, update// arr[pos] to new_val and make required changes to segtreefunction update(node, tl, tr, pos, new_val) {         // if current range only contains one point, this must    // be arr[pos], update the corresponding node to new_val    if (tl === tr) {        seg_tree[node] = new_val;    } else {        // else divide the range into two parts        let tm = Math.floor((tr - tl)/2) + tl;                 // if pos lies in first half, update this half, else        // update second half        if (pos <= tm) {            update(2 * node, tl, tm, pos, new_val);        } else {            update(2 * node + 1, tm + 1, tr, pos, new_val);        }                 // combine results from both halves        seg_tree[node] = combine(seg_tree[2 * node],                            seg_tree[2 * node + 1]);    }} // query function, returns minimum in the range [l, r]function query(node, tl, tr, l, r) {         // if range is invalid, then return infinity    if (l > r) {        return Number.POSITIVE_INFINITY;    }         // if range completely aligns with a segment tree node,    // then value of this node should be returned    if (l === tl && r === tr) {        return seg_tree[node];    }         // else divide the query into two parts    let tm = Math.floor((tr - tl)/2) + tl;         let q1 = query(2 * node, tl, tm, l, Math.min(r, tm));    let q2 = query(2 * node + 1, tm + 1, tr, Math.max(l, tm + 1), r);         // and combine the results from the two parts and return    // it    return combine(q1, q2);} // --------Segment Tree Ends Here----------------- function printNSE(original, n) {    let sorted = Array(n).fill(0);    let encode = {};     // -------Coordinate Compression Starts Here ------     // created a temporary sorted array out of original    for (let i = 0; i < n; i++) {        sorted[i] = original[i];    }    sorted.sort(function(a, b){return a-b});     // encode each value to a new value in sorted array    let ctr = 0;    for (let i = 0; i < n; i++) {        if (!encode.hasOwnProperty(sorted[i])) {            encode[sorted[i]] = ctr;            ctr += 1;        }    }         // use encode to compress original array    let compressed = Array(n).fill(0);    for (let i = 0; i < n; i++) {        compressed[i] = encode[original[i]];    }     // -------Coordinate Compression Ends Here ------     // Create an aux array of size ctr, and build a segtree    // based on this array     let aux = Array(ctr).fill(Number.POSITIVE_INFINITY);    seg_tree.fill(Number.POSITIVE_INFINITY);     build(aux, 1, 0, ctr - 1);     // For each compressed[i], query for index of NSE and    // update segment tree     let ans = Array(n).fill(0);    for (let i = n-1; i >= 0; i--) {        ans[i] = query(1, 0, ctr - 1, 0, compressed[i] - 1);        update(1, 0, ctr - 1, compressed[i], i);    }     // Print -1 if NSE doesn't exist, otherwise print NSE    // itself     for (let i = 0; i < n; i++) {        if (ans[i] === Number.POSITIVE_INFINITY) {            console.log(original[i], " ---> ", -1);        } else {            console.log(original[i], " ---> ", original[ans[i]]);        }    }} // Driver program to test above functions//if (require.main === module) {    let arr = [11, 13, 21, 3];    printNSE(arr, 4);//} // This code is contributed by akashish__

Output

11 ---> 3
13 ---> 3
21 ---> 3
3 ---> -1

Time Complexity Auxiliary Space: O(N)

Method 4 (Using Stack): This problem is similar to next greater element. Here we maintain items in increasing order in the stack (instead of decreasing in next greater element problem).

1. Push the first element to stack.
2. Pick rest of the elements one by one and follow following steps in loop.
• Mark the current element as next.
• If stack is not empty, then compare next with stack top. If next is smaller than top then next is the NSE for the top. Keep popping from the stack while top is greater than next. next becomes the NSE for all such popped elements
• Push next into the stack
3. After the loop in step 2 is over, pop all the elements from stack and print -1 as next element for them.

Note: To achieve the same order, we use a stack of pairs, where first element is the value and second element is index of array element.

## C++

 // A Stack based C++ program to find next// smaller element for all array elements#include using namespace std; // prints NSE for elements of array arr[] of size n void printNSE(int arr[], int n){    stack > s;    vector<int> ans(n);     // iterate for rest of the elements    for (int i = 0; i < n; i++) {        int next = arr[i];         // if stack is empty then this element can't be NSE        // for any other element, so just push it to stack        // so that we can find NSE for it, and continue        if (s.empty()) {            s.push({ next, i });            continue;        }         // while stack is not empty and the top element is        // greater than next        //  a) NSE for top is next, use top's index to        //    maintain original order        //  b) pop the top element from stack         while (!s.empty() && s.top().first > next) {            ans[s.top().second] = next;            s.pop();        }         // push next to stack so that we can find NSE for it         s.push({ next, i });    }     // After iterating over the loop, the remaining elements    // in stack do not have any NSE, so set -1 for them     while (!s.empty()) {        ans[s.top().second] = -1;        s.pop();    }     for (int i = 0; i < n; i++) {        cout << arr[i] << " ---> " << ans[i] << endl;    }} // Driver program to test above functionsint main(){    int arr[] = { 11, 13, 21, 3 };    int n = sizeof(arr) / sizeof(arr);    printNSE(arr, n);    return 0;}

## Java

 // A Stack based Java program to find next// smaller element for all array elements// in same order as input.import java.io.*;import java.lang.*;import java.util.*; class GFG {    /* prints element and NSE pair for all    elements of arr[] of size n */    public static void printNSE(int arr[], int n)    {        Stack s = new Stack();        HashMap mp            = new HashMap();         /* push the first element to stack */        s.push(arr);         // iterate for rest of the elements        for (int i = 1; i < n; i++) {             if (s.empty()) {                s.push(arr[i]);                continue;            }             /* if stack is not empty, then    pop an element from stack.    If the popped element is greater    than next, then    a) print the pair    b) keep popping while elements are    greater and stack is not empty */             while (s.empty() == false                   && s.peek() > arr[i]) {                mp.put(s.peek(), arr[i]);                s.pop();            }             /* push next to stack so that we can find            next smaller for it */            s.push(arr[i]);        }         /* After iterating over the loop, the remaining        elements in stack do not have the next smaller        element, so print -1 for them */        while (s.empty() == false) {            mp.put(s.peek(), -1);            s.pop();        }         for (int i = 0; i < n; i++)            System.out.println(arr[i] + " ---> "                               + mp.get(arr[i]));    }     /* Driver program to test above functions */    public static void main(String[] args)    {        int arr[] = { 11, 13, 21, 3 };        int n = arr.length;        printNSE(arr, n);    }}

## Python3

 # A Stack based Python3 program to find next# smaller element for all array elements# in same order as input.using System; """ prints element and NSE pair for allelements of arr[] of size n """  def printNSE(arr, n):    s = []    mp = {}     # push the first element to stack    s.append(arr)     # iterate for rest of the elements    for i in range(1, n):        if (len(s) == 0):            s.append(arr[i])            continue         """ if stack is not empty, then        pop an element from stack.        If the popped element is greater        than next, then        a) print the pair        b) keep popping while elements are        greater and stack is not empty """        while (len(s) != 0 and s[-1] > arr[i]):            mp[s[-1]] = arr[i]            s.pop()         """ push next to stack so that we can find        next smaller for it """        s.append(arr[i])     """ After iterating over the loop, the remaining    elements in stack do not have the next smaller    element, so print -1 for them """    while (len(s) != 0):        mp[s[-1]] = -1        s.pop()     for i in range(n):        print(arr[i], "--->", mp[arr[i]])  arr = [11, 13, 21, 3]n = len(arr)printNSE(arr, n) # This code is contributed by decode2207.

## C#

 // A Stack based C# program to find next// smaller element for all array elements// in same order as input.using System;using System;using System.Collections.Generic; class GFG {    /* prints element and NSE pair for all    elements of arr[] of size n */    public static void printNSE(int[] arr, int n)    {        Stack<int> s = new Stack<int>();        Dictionary<int, int> mp            = new Dictionary<int, int>();         /* push the first element to stack */        s.Push(arr);         // iterate for rest of the elements        for (int i = 1; i < n; i++) {            if (s.Count == 0) {                s.Push(arr[i]);                continue;            }            /* if stack is not empty, then            pop an element from stack.            If the popped element is greater            than next, then            a) print the pair            b) keep popping while elements are            greater and stack is not empty */            while (s.Count != 0 && s.Peek() > arr[i]) {                mp.Add(s.Peek(), arr[i]);                s.Pop();            }             /* push next to stack so that we can find            next smaller for it */            s.Push(arr[i]);        }         /* After iterating over the loop, the remaining        elements in stack do not have the next smaller        element, so print -1 for them */        while (s.Count != 0) {            mp.Add(s.Peek(), -1);            s.Pop();        }         for (int i = 0; i < n; i++)            Console.WriteLine(arr[i] + " ---> "                              + mp[arr[i]]);    }     // Driver code    public static void Main()    {        int[] arr = { 11, 13, 21, 3 };        int n = arr.Length;        printNSE(arr, n);    }}// This code is contributed by// 29AjayKumar

## Javascript

 

Output

11 ---> 3
13 ---> 3
21 ---> 3
3 ---> -1

Time Complexity: As we use only single for loop and all the elements in the stack are push and popped atmost once.

Auxiliary Space: O(N)

As extra space is used for storing the elements of the stack.

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