Given a binary string str of length N, the task is to find the maximum count of consecutive substrings str can be divided into such that all the substrings are balanced i.e. they have equal number of 0s and 1s. If it is not possible to split str satisfying the conditions then print -1.
Example:
Input: str = “0100110101”
Output: 4
The required substrings are “01”, “0011”, “01” and “01”.
Input: str = “0111100010”
Output: 3
Input: str = “0000000000”
Output: -1
Approach: Initialize count = 0 and traverse the string character by character and keep track of the number of 0s and 1s so far, whenever the count of 0s and 1s become equal increment the count. As in the given question, if it is not possible to split string then on that time count of 0s must not be equal to count of 1s then return -1 else print the value of count after the traversal of the complete string.
Below is the implementation of the above approach:
C++
#include <bits/stdc++.h>
using namespace std;
int maxSubStr(string str, int n)
{
int count0 = 0, count1 = 0;
int cnt = 0;
for ( int i = 0; i < n; i++) {
if (str[i] == '0' ) {
count0++;
}
else {
count1++;
}
if (count0 == count1) {
cnt++;
}
}
if (count0!=count1) {
return -1;
}
return cnt;
}
int main()
{
string str = "0100110101" ;
int n = str.length();
cout << maxSubStr(str, n);
return 0;
}
|
Java
class GFG
{
static int maxSubStr(String str, int n)
{
int count0 = 0 , count1 = 0 ;
int cnt = 0 ;
for ( int i = 0 ; i < n; i++)
{
if (str.charAt(i) == '0' )
{
count0++;
}
else
{
count1++;
}
if (count0 == count1)
{
cnt++;
}
}
if (count0 != count1)
{
return - 1 ;
}
return cnt;
}
public static void main(String []args)
{
String str = "0100110101" ;
int n = str.length();
System.out.println(maxSubStr(str, n));
}
}
|
Python3
def maxSubStr( str , n):
count0 = 0
count1 = 0
cnt = 0
for i in range (n):
if str [i] = = '0' :
count0 + = 1
else :
count1 + = 1
if count0 = = count1:
cnt + = 1
if count0 ! = count1:
return - 1
return cnt
str = "0100110101"
n = len ( str )
print (maxSubStr( str , n))
|
C#
using System;
class GFG
{
static int maxSubStr(String str, int n)
{
int count0 = 0, count1 = 0;
int cnt = 0;
for ( int i = 0; i < n; i++)
{
if (str[i] == '0' )
{
count0++;
}
else
{
count1++;
}
if (count0 == count1)
{
cnt++;
}
}
if (count0 != count1)
{
return -1;
}
return cnt;
}
public static void Main(String []args)
{
String str = "0100110101" ;
int n = str.Length;
Console.WriteLine(maxSubStr(str, n));
}
}
|
Javascript
<script>
function maxSubStr(str, n)
{
var count0 = 0, count1 = 0;
var cnt = 0;
for ( var i = 0; i < n; i++) {
if (str[i] == '0' ) {
count0++;
}
else {
count1++;
}
if (count0 == count1) {
cnt++;
}
}
if (count0 != count1) {
return -1;
}
return cnt;
}
var str = "0100110101" ;
var n = str.length;
document.write( maxSubStr(str, n));
</script>
|
Time complexity: O(N) where N is the length of the string
Space Complexity: O(1)
Another approach using Stack :
Approach: Similar to balanced parenthesis approach using stack, we keep inserting if top of stack matches with traversing character. we keep popping when its not matching with top of stack. Whenever stack is empty, it means we got a balanced substring. In this case, we increase answer variable. At last after complete traversal, we will check if stack is empty or not. If yes, it means everything is balanced out. If not, it means it’s not balanced.
Below is the implementation of the above approach:
C++
#include<bits/stdc++.h>
using namespace std;
int maxSubStr(string str, int n)
{
int ans=0;
int i=0;
stack< int >s;
s.push(str[i]);
i++;
while (i<str.size()){
while (i<str.size()&&s.size()&&i<str.size()&&(s.top()!=str[i])){
s.pop();
i++;
}
if (s.empty()){
ans++;
}
while ((i<str.size())&&(s.empty()||s.top()==str[i])){
s.push(str[i]);
i++;
}
}
if (s.empty())
return ans;
return -1;
}
int main()
{
string str = "0100110101" ;
int n = str.length();
cout << maxSubStr(str, n);
return 0;
}
|
Java
import java.util.*;
class Main
{
static int maxSubStr(String str, int n)
{
int ans = 0 ;
int i = 0 ;
Stack<Character> s = new Stack<>();
s.push(str.charAt(i));
i++;
while (i<str.length()){
while (i<str.length() && !s.empty() && s.peek()!=str.charAt(i)){
s.pop();
i++;
}
if (s.empty()){
ans++;
}
while (i<str.length() && (s.empty() || s.peek()==str.charAt(i))){
s.push(str.charAt(i));
i++;
}
}
if (s.empty())
return ans;
return - 1 ;
}
public static void main(String[] args)
{
String str = "0100110101" ;
int n = str.length();
System.out.println(maxSubStr(str, n));
}
}
|
Python3
def maxSubStr(s: str ) - > int :
ans = 0
i = 0
stack = [s[i]]
i + = 1
while i < len (s):
while i < len (s) and stack and i < len (s) and stack[ - 1 ] ! = s[i]:
stack.pop()
i + = 1
if not stack:
ans + = 1
while i < len (s) and ( not stack or stack[ - 1 ] = = s[i]):
stack.append(s[i])
i + = 1
if not stack:
return ans
return - 1
str = "0100110101"
print (maxSubStr( str ))
|
C#
using System;
using System.Collections.Generic;
public class MaxSubStrSolution
{
public static int MaxSubStr( string str, int n)
{
int ans = 0;
int i = 0;
Stack< char > s = new Stack< char >();
s.Push(str[i]);
i++;
while (i < str.Length)
{
while (i < str.Length && s.Count > 0 && i < str.Length && s.Peek() != str[i])
{
s.Pop();
i++;
}
if (s.Count == 0)
{
ans++;
}
while (i < str.Length && (s.Count == 0 || s.Peek() == str[i]))
{
s.Push(str[i]);
i++;
}
}
if (s.Count == 0)
{
return ans;
}
return -1;
}
public static void Main()
{
string str = "0100110101" ;
int n = str.Length;
Console.WriteLine(MaxSubStr(str, n));
}
}
|
Javascript
const maxSubStr = (str, n) => {
let ans = 0;
let i = 0;
let s = [];
s.push(str[i]);
i++;
while (i < str.length){
while (i < str.length && s.length > 0 && s[s.length-1] !== str[i]){
s.pop();
i++;
}
if (s.length === 0)
ans++;
while (i < str.length && (s.length === 0 || s[s.length-1] === str[i])){
s.push(str[i]);
i++;
}
}
if (s.length === 0)
return ans;
return -1;
}
let str = "0100110101" ;
let n = str.length;
console.log(maxSubStr(str, n));
|
Time complexity: O(n), where n is the length of the input string. This is because the code iterates over the string once.
Auxiliary Space: O(n), the above code is using a stack to store the elements of string, so over all complexity is O(n).
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