Java Program to Maximize Count of Substrings Containing at Least 1 Vowel and 1 Consonant

One fascinating difficulty in many string-related problems is locating and counting substrings that meet specific requirements. Finding and counting all substrings with at least one vowel and one consonant is one such task. This problem illustrates a variety of algorithmic techniques, from brute force tactics to more effective strategies, and it is also crucial to comprehending string manipulation.

In this section, we will discuss some approaches to utilising Java to solve this problem. We will begin with a primary brute force method that examines every substring before moving on to more efficient alternatives like the counting method and the sliding window technique.

A thorough explanation and code implementation will be provided for each method so you can see the trade-offs between performance and simplicity.

Examples

Input: S = "sunnyday"

Output: 2

Explanation: The string can be split as "su", "nnyday".

Input: S = "programming"

Output: 4

Explanation: The string can be split as "pro", "gr", "amm", "ing".

Approach 1: Brute Force Method

Steps

1. Generate all possible substrings.
2. Check if the generated substring contains at least one vowel and one consonant.
3. If it does, increment the count.

File Name: VowelConsonantSubstrings.java

Output:

 
Total substrings: 7   

Approach 2: Optimized Sliding Window Method

This approach optimizes the brute force method by using the sliding window technique. The idea is to maintain a window that dynamically adjusts as we traverse through the string.

Steps

1. Use two pointers to define a sliding window.
2. Expand the window until it contains both a vowel and a consonant.
3. Count all possible valid substrings within this window.
4. Adjust the window to look for the next valid substring.

File Name: VowelConsonantSubstrings.java

Output:

 
Total substrings: 7   

Explanation

The sliding window method uses a window to alter and evaluate substrings dynamically as we travel the text, hence optimising the brute force approach. To define the window, we keep two pointers and expand it until we locate a vowel and a consonant inside of it.

After identifying a legitimate window, we advance the window forward to carry on the search by counting all substrings that can be created from the present window. Although this approach eliminates redundancy and lowers the time complexity to O(n 2), it is still less effective than the counting method because it still requires nested loops.

Approach 3: Vowel and Consonant Pairs

By going over the string and counting the vowels and consonants, this method can be applied. We count how many valid substrings can be constructed with the consonants we have seen so far for each vowel that is detected.

Steps

1. Traverse the string.
2. Count the number of consonants encountered so far for each vowel counted.
3. Count the number of vowels encountered so far for each consonant counted.

File Name: VowelConsonantSubstrings.java

Output:

 
Total valid substrings: 2   

Explanation

Through direct counting of the number of valid substrings as we traverse the string, this method further optimises the process. For each recognised vowel, we add the number of substrings that may be created using all of the preceding consonants and vice versa. Since we just go through the string once, the time complexity is lowered to O(n), and it effectively counts all potential valid substrings.

Conclusion

Different strategies, each with differing degrees of effectiveness, can be used to maximise the count of substrings that contain at least one vowel and one consonant. For big strings, the brute force method, while easy, is ineffective.

Although it optimises the search, the sliding window method still has a quadratic time complexity. The most effective technique reduces the temporal complexity to linear time by simply counting the pairings.