1759. Count Number of Homogenous Substrings

MediumMathString
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Problem Description

The task is to find the number of homogenous substrings in a given string s. A string is considered homogenous if all characters in the string are identical. A substring refers to a consecutive sequence of characters within a string. The answer should be returned modulo 10^9 + 7 to prevent overflow issues due to potentially large numbers.

For example, if s = "aaa", then the homogenous substrings are "a", "a", "a", "aa", "aa", and "aaa", which totals up to 6.

Intuition

To solve this problem efficiently, we can utilize a two-pointer technique.

  1. We iterate over the string using two pointers, i and j.
  2. The first pointer i marks the start of a potential homogenous substring, while j scans ahead to find where this substring ends (i.e., where a character different from s[i] is encountered).
  3. For each character position i, we find the longest stretch of the same character by incrementally increasing j as long as s[j] is equal to s[i].
  4. The length of the homogenous substring starting at i is (j - i). For each such substring, we calculate the number of homogenous substrings that can be made, which is given by the formula (1 + cnt) * cnt / 2, where cnt is the length of the homogenous substring.
  5. Why this formula? Consider a homogenous string of length n. We can make n single-character substrings, n-1 substrings of length 2, n-2 of length 3, and so on, down to 1 substring of length n. This forms an arithmetic sequence that sums to n*(n+1)/2.
  6. The answer is incremented by this count for each homogenous stretch we find.
  7. We use the modulo operation to keep our calculations within the prescribed limit to avoid integer overflow.
  8. The first pointer i is then set to j to start searching for the next homogenous substring.

This approach optimizes the process by minimizing the number of times we traverse the string, leading to an efficient solution.

Learn more about Math patterns.

Solution Approach

The implementation of the solution uses a two-pointer technique along with basic arithmetic calculations to find the number of homogenous substrings. Here is the walkthrough of the code:

  • The function countHomogenous starts by initializing the variable mod to 10**9 + 7 for modulo operations to prevent overflow.
  • Two variables are declared, i being the start pointer (initialized at index 0) and n being the length of the input string s.
  • We also initialize a variable ans to store the cumulative number of homogenous substrings found.

The solution enters a loop that continues until the start pointer i has reached the end of the string (i < n):

  1. A second pointer j is set to start at the same position as i. This will be used to find the end of the current homogenous substring.
  2. A while loop is used to move j forward as long as s[j] is the same as s[i]. When s[j] is different from s[i], it means we have found the end of the homogenous substring.
  3. After the while loop, we now have a substring from index i to j - 1 that is homogenous. The length of this substring is cnt = j - i.
  4. To find the number of homogenous substrings within this section, we use the arithmetic series sum formula (1 + cnt) * cnt / 2, where cnt is the length of the homogenous substring.
  5. The result is added to ans, which keeps the running total of homogenous substrings. Every time a new count is added, we perform a modulo operation to make sure ans doesn't exceed 10**9 + 7.
  6. Finally, we move the start pointer i to the position where j ended, as everything before j is already part of a homogenous substring we've counted.

The use of the two-pointer technique efficiently reduces the time complexity since each character in the string is checked only once. By only considering stretches of identical characters and using the arithmetic series sum formula, we avoid having to individually count each possible substring. This is what makes the algorithm efficient.

The function ends by returning the total count ans as the resulting number of homogenous substrings.

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Example Walkthrough

Let's illustrate the solution approach with a small example. Assume the input string s = "abbba".

  • The countHomogenous function begins by initializing the variables (mod = 10^9 + 7, i = 0, n = 5, and ans = 0).
  • The main loop starts with i < n, which is true at the start (i = 0).

Starting with i = 0:

  1. We set the second pointer j = i = 0. We are now looking for a homogenous substring starting at 'a'.

  2. As we increment j, we realize that s[j] == s[i] only for j = 0. As soon as j becomes 1, s[j] becomes 'b', which is different from s[i] ('a'). So the while loop stops with j = 1.

  3. We found a homogenous substring 'a' from index 0 to 0. Thus cnt = j - i = 1 - 0 = 1.

  4. The number of homogenous substrings for this cnt is (1 + 1) * 1 / 2 = 1.

  5. We add this to ans, ans = 0 + 1 = 1.

  6. We then set i = j, so i is now 1 and we start looking for a new homogenous substring.

Next with i = 1:

  1. Set j to 1. The character at this index is 'b'.

  2. We increment j while s[j] is the same as s[i]. This gives us j = 4 because indices 1, 2, and 3 are all 'b'.

  3. We found a homogenous substring 'bbb' from index 1 to 3, so cnt = j - i = 4 - 1 = 3.

  4. Using the formula for cnt = 3, the number of homogenous substrings is (1 + 3) * 3 / 2 = 6.

  5. This is added to ans, which becomes ans = 1 + 6 = 7.

  6. The i is moved to the index 4.

The last character is evaluated but as there are no repeating characters beyond this point, j never increments. Therefore, this results in a cnt of 1, which provides a single homogenous substring 'a'.

The answer, or total number of homogenous substrings, is summed up as ans = 7 + 1 = 8, which is the result returned by the function.

This walkthrough simplifies how the solution makes efficient use of the two-pointer technique to calculate the number of homogenous substrings without having to count each one individually.

Solution Implementation

1class Solution:
2    def countHomogenous(self, s: str) -> int:
3        # Define the modulus as mentioned in the problem statement.
4        modulo_factor = 10**9 + 7
5      
6        # Initialize starting index for iterating the string and the length of the string.
7        current_index, string_length = 0, len(s)
8      
9        # Initialize the answer to count homogenous substrings.
10        homogenous_count = 0
11      
12        # Iterate over the string to find homogenous substrings.
13        while current_index < string_length:
14            # Find the end of the current homogenous substring.
15            next_index = current_index
16            while next_index < string_length and s[next_index] == s[current_index]:
17                next_index += 1
18          
19            # Calculate the length of the current homogenous substring.
20            substring_length = next_index - current_index
21          
22            # Count the number of homogenous substrings which can be formed from 
23            # the current homogenous substring using the formula for the sum of 
24            # the first n natural numbers: n * (n + 1) / 2.
25            homogenous_count += (1 + substring_length) * substring_length // 2
26          
27            # Use modulo operation to avoid large numbers as per problem constraints.
28            homogenous_count %= modulo_factor
29          
30            # Move to the beginning of the next potential homogenous substring.
31            current_index = next_index
32      
33        # Return the final count of homogenous substrings.
34        return homogenous_count
35
1class Solution {
2    private static final int MOD = (int) 1e9 + 7;
3
4    public int countHomogenous(String s) {
5        // Length of the input string
6        int length = s.length();
7        // Variable to hold the total count of homogenous substrings
8        long totalHomogenousSubstrings = 0;
9      
10        // Loop through the string characters
11        for (int startIndex = 0, endIndex = 0; startIndex < length; startIndex = endIndex) {
12            // Set the end index to the current start index
13            endIndex = startIndex;
14            // Extend the end index while the end character is the same as the start character
15            while (endIndex < length && s.charAt(endIndex) == s.charAt(startIndex)) {
16                endIndex++;
17            }
18            // Calculate the length of the homogeneous substring
19            int homogeneousLength = endIndex - startIndex;
20            // Use the formula for sum of first n natural numbers to calculate the number of substrings
21            totalHomogenousSubstrings += (long) (1 + homogeneousLength) * homogeneousLength / 2;
22            // Apply modulo operation to prevent overflow
23            totalHomogenousSubstrings %= MOD;
24        }
25        // Cast the result to int before returning, since the final output must be an integer
26        return (int) totalHomogenousSubstrings;
27    }
28}
29
1class Solution {
2public:
3    static constexpr int MOD = 1e9 + 7; // Define the modulus constant for preventing integer overflow.
4
5    // Method to count the number of homogenous substrings in the given string s.
6    int countHomogenous(string s) {
7        int length = s.size(); // The length of the input string.
8        long long answer = 0;  // To store the final answer, initialized to 0.
9      
10        // Loop through the string to count all homogenous substrings.
11        for (int start = 0, end = 0; start < length; start = end) {
12            // Find the end of the current homogenous substring.
13            end = start;
14            while (end < length && s[end] == s[start]) {
15                ++end;
16            }
17
18            // Compute the count of characters in the current homogenous substring.
19            int count = end - start;
20          
21            // Calculate the number of possible homogenous substrings,
22            // which is the sum of the first count natural numbers: count * (count + 1) / 2.
23            // We use long long to avoid integer overflow during the calculation.
24            answer += static_cast<long long>(count + 1) * count / 2;
25            answer %= MOD; // Apply the modulus to keep the answer within the integer limits.
26        }
27      
28        return static_cast<int>(answer); // Return the answer as an integer.
29    }
30};
31
1// Function to count the number of homogenous substrings in a given string.
2// A homogenous substring is one that consists of a single unique character.
3// For example, in the string "aa", there would be three homogenous substrings: "a", "a", and "aa".
4function countHomogenous(s: string): number {
5    const MODULO: number = 1e9 + 7; // Define a constant for modulo to avoid large numbers
6    const n: number = s.length; // Length of the input string
7    let count: number = 0; // Initialize the count of homogenous substrings
8
9    // Use two pointers to iterate through the string
10    for (let startIndex = 0, currentIndex = 0; currentIndex < n; currentIndex++) {
11        // If the current character is different from the starting character,
12        // update the starting index to the current index
13        if (s[startIndex] !== s[currentIndex]) {
14            startIndex = currentIndex;
15        }
16        // Calculate the number of homogenous substrings found so far based on the current sequence
17        // Add the number of new homogenous substrings from startIndex to currentIndex
18        count = (count + (currentIndex - startIndex + 1)) % MODULO;
19    }
20    // Return the total count of homogenous substrings modulo the defined constant
21    return count;
22}
23

Time and Space Complexity

The time complexity of the given code is O(n), where n is the length of the string s. This is because each character in the string is checked exactly once to form homogenous substrings (characters that are the same and contiguous). The inner while loop runs only once for each homogenous substring, and since it only moves j to the end of a homogenous substring, the iterations of the inner loop throughout the entire run of the algorithm sum up to O(n).

The space complexity of the code is O(1). This is because the algorithm uses a constant number of additional variables (mod, i, n, ans, j, cnt) which do not scale with the input size - they use a constant amount of space regardless of the length of the string s.

Learn more about how to find time and space complexity quickly using problem constraints.


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Question 1 out of 10

Given a sorted array of integers and an integer called target, find the element that equals to the target and return its index. Select the correct code that fills the ___ in the given code snippet.

1def binary_search(arr, target):
2    left, right = 0, len(arr) - 1
3    while left ___ right:
4        mid = (left + right) // 2
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12
1public static int binarySearch(int[] arr, int target) {
2    int left = 0;
3    int right = arr.length - 1;
4
5    while (left ___ right) {
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15}
16
1function binarySearch(arr, target) {
2    let left = 0;
3    let right = arr.length - 1;
4
5    while (left ___ right) {
6        let mid = left + Math.trunc((right - left) / 2);
7        if (arr[mid] == target) return mid;
8        if (arr[mid] < target) {
9            ___ = mid + 1;
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11            ___ = mid - 1;
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13    }
14    return -1;
15}
16

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