38. Count and Say
DifficultyMedium
Description
The count-and-say sequence is a sequence of digit strings defined by the recursive formula:
countAndSay(1) = "1"countAndSay(n)is the run-length encoding ofcountAndSay(n - 1).
Run-length encoding (RLE) is a string compression method that works by replacing each maximal group of consecutive identical characters with the concatenation of the length of the group followed by the character itself. For example, to compress the string "3322251" we replace "33" with "23", replace "222" with "32", replace "5" with "15", and replace "1" with "11". Thus the compressed string becomes "23321511".
Given a positive integer n, return the nth element of the count-and-say sequence.
Example 1:
Input: n = 4
Output: "1211"
Explanation:
countAndSay(1) = "1" countAndSay(2) = RLE of "1" = "11" countAndSay(3) = RLE of "11" = "21" countAndSay(4) = RLE of "21" = "1211"
Example 2:
Input: n = 1
Output: "1"
Explanation:
This is the base case.
Constraints:
1 <= n <= 30
Follow up: Could you solve it iteratively?
Solutions
Solution 1: Simulation
Thinking
The definition itself is “the \(n\)-th term describes the \((n-1)\)-th”, so there is no cheaper closed form. \(n \le 30\), so we can start from "1" and iterate \(n-1\) times.
Each term is a run-length encoding of the previous one: a streak of the same character becomes “count + character”.
Two pointers walk the current string \(s\) and append each run’s length and character to a new string. The follow-up asks for an iterative solution, which also avoids a recursion stack.
The task requires outputting the appearance sequence of the \(n\)-th item, where the \(n\)-th item is the description of the \(n-1\)-th item in the sequence. Therefore, we iterate \(n-1\) times. In each iteration, we use fast and slow pointers, denoted as j and i respectively, to record the current character's position and the position of the next character that is not equal to the current character. We then update the sequence of the previous item to be \(j-i\) occurrences of the current character.
Overall, the time complexity is \(O(nm)\), and the space complexity is \(O(m)\), where \(n\) is the input parameter representing the term to generate, and \(m\) is the maximum length of the string in the sequence.
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