Given a string S of length N, the task is to find the minimum operations required to make the frequency of every distinct character prime. Frequency of a character can be increased or decreased by 1 in a single operation.
Input: S = “abba”
Explanation: There are two characters in the string S and the frequency of ‘a’ is 2 which is prime. The frequency of ‘b’ is 2 which is also a prime number.Hence no operations are required for this case.
Input: S = “aaaaaaaaa”
Explanation: The frequency of ‘a’ in the string is 9. Either remove 2 a’s from the string or add 2 a’s in the string to make the frequency of ‘a’ prime. Thus minimum number of operations needed is 2.
Find the frequency of each character in the string. Let the frequency be X. Find the prime number greater than X and less than X. Compare the difference between X and the two prime numbers found and choose the closest prime number. Add the difference between the closest prime number and X to the number of operations. Thus the minimum number of operations will be obtained. It is an inefficient approach as the lower and upper bound to find the prime number is not known.
Efficient Approach :
- Use the sieve algorithm to find all the prime numbers up to N and store them in an array.
- Find out the nearest lower prime number for all the numbers from i = 1 to N and store the difference between i and its nearest lower prime number in an array say arr1.
- Find out the nearest higher prime number for all the numbers from i = 1 to N and store the difference between i and its nearest higher prime number in an array say arr2.
- Traverse the string and find the frequency of all the distinct characters in the string and use an unordered_map to save the frequencies of these distinct characters.
- Let the frequency of any distinct character be X then find out the distance between X and nearest prime number from the arrays arr1 and arr2.
- Choose the distance which is lesser between the two and add this distance to the number of operations.
- Do this for all the distinct characters and print the number of operations finally.
Below is the implementation of the above approach:
Time complexity: O(N * log(log(N)))
Auxillary Space complexity: O(N)
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