You're working on a text formatting tool that needs to rearrange characters in a string to improve readability.
Given a string s
, rearrange the characters of s
so that any two adjacent characters are not the same.
Return any possible rearrangement of s
or return an empty string if not possible.
Input: s = "aab"
Output: "aba"
Explanation: By rearranging the characters, we get 'aba'. This is a valid arrangement since no two adjacent characters are the same.
Input: s = "aaab"
Output: ""
Explanation: There is no way to rearrange the characters to avoid having two adjacent 'a's.
To solve this problem, we need to:
Apply string manipulation concepts to solve a real-world problem.
You're working on a text formatting tool that needs to rearrange characters in a string to improve readability.
Given a string s
, rearrange the characters of s
so that any two adjacent characters are not the same.
Return any possible rearrangement of s
or return an empty string if not possible.
By rearranging the characters, we get 'aba'. This is a valid arrangement since no two adjacent characters are the same.
There is no way to rearrange the characters to avoid having two adjacent 'a's.
If a character appears more than (n+1)/2 times (where n is the length of the string), it's impossible to rearrange the string to avoid adjacent duplicates
The greedy approach of placing the most frequent characters first works well for this problem
Alternating positions (even and odd indices) can be used to distribute characters evenly
A priority queue (max heap) can efficiently track character frequencies and help with the greedy placement
The problem can also be solved by constructing the result string character by character, always choosing the most frequent remaining character that is different from the last one used
This problem has several practical applications:
Improving readability by avoiding repeated adjacent characters in text.
Rearranging data to optimize compression algorithms that work better with varied patterns.
Scheduling tasks to avoid consecutive assignments of the same type.
Distributing network packets to avoid congestion from sequential similar packets.
Generating text with better character distribution for improved readability.
You're working on a text formatting tool that needs to rearrange characters in a string to improve readability.
Given a string s
, rearrange the characters of s
so that any two adjacent characters are not the same.
Return any possible rearrangement of s
or return an empty string if not possible.
Input: s = "aab"
Output: "aba"
Explanation: By rearranging the characters, we get 'aba'. This is a valid arrangement since no two adjacent characters are the same.
Input: s = "aaab"
Output: ""
Explanation: There is no way to rearrange the characters to avoid having two adjacent 'a's.
To solve this problem, we need to:
Apply string manipulation concepts to solve a real-world problem.
You're working on a text formatting tool that needs to rearrange characters in a string to improve readability.
Given a string s
, rearrange the characters of s
so that any two adjacent characters are not the same.
Return any possible rearrangement of s
or return an empty string if not possible.
By rearranging the characters, we get 'aba'. This is a valid arrangement since no two adjacent characters are the same.
There is no way to rearrange the characters to avoid having two adjacent 'a's.
If a character appears more than (n+1)/2 times (where n is the length of the string), it's impossible to rearrange the string to avoid adjacent duplicates
The greedy approach of placing the most frequent characters first works well for this problem
Alternating positions (even and odd indices) can be used to distribute characters evenly
A priority queue (max heap) can efficiently track character frequencies and help with the greedy placement
The problem can also be solved by constructing the result string character by character, always choosing the most frequent remaining character that is different from the last one used
This problem has several practical applications:
Improving readability by avoiding repeated adjacent characters in text.
Rearranging data to optimize compression algorithms that work better with varied patterns.
Scheduling tasks to avoid consecutive assignments of the same type.
Distributing network packets to avoid congestion from sequential similar packets.
Generating text with better character distribution for improved readability.