1960. Maximum Product of the Length of Two Palindromic Substrings
Problem Explanation
You are given a string s
and your task is to find two non-intersecting palindromic substrings of odd length such that the product of their lengths is maximized. Both the substrings should be palindromes and have odd lengths.
A palindrome is a string that is the same forward and backward. A substring is a contiguous sequence of characters in a string.
Example
Let's walk through an example to understand the problem better.
Input: s = “ababbb” Output: 9
In this example, we have two substrings, "aba" and "bbb", which are palindromes with odd lengths. We can calculate the product as follows: 3 * 3 = 9
, and thus, the output is 9.
Approach
The approach we will use for this problem is the Manacher's Algorithm. Here are the steps we will follow:
- For each position in the string
s
, find the length of the longest palindrome that has the center at that position. - Find two non-overlapping longest palindromes.
- Return the product of the lengths of the two longest non-overlapping palindromes.
Manacher's Algorithm
Manacher's Algorithm is an efficient method to find the longest palindromic substring in linear time complexity. It works by calculating the lengths of all palindromic substrings for each position in the given string, hence finding the longest palindrome substring.
Algorithm Steps
- Implement the Manacher's Algorithm and store the length of the longest palindrome centered at each position in an array.
- Find the left to right and right to left longest palindromes using the array derived in step 1.
- Iterate through the array, finding two non-overlapping longest palindromes.
- Return the product of the lengths of the two non-overlapping longest palindromes.
Now, let's implement the solution in different languages.
C++ Solution
cpp
class Solution {
public:
long long maxProduct(string s) {
const int n = s.length();
long long ans = 1;
// l[i] := max length of palindromes in s[0..i)
vector<int> l = manacher(s, n);
// r[i] := max length of palindromes in s[i..n)
vector<int> r = manacher(string(rbegin(s), rend(s)), n);
reverse(begin(r), end(r));
for (int i = 0; i + 1 < n; ++i)
ans = max(ans, (long long)l[i] * r[i + 1]);
return ans;
}
private:
vector<int> manacher(const string& s, int n) {
vector<int> maxExtends(n);
vector<int> l2r(n, 1);
int center = 0;
for (int i = 0; i < n; ++i) {
const int r = center + maxExtends[center] - 1;
const int mirrorIndex = center - (i - center);
int extend = i > r ? 1 : min(maxExtends[mirrorIndex], r - i + 1);
while (i - extend >= 0 && i + extend < n &&
s[i - extend] == s[i + extend]) {
l2r[i + extend] = 2 * extend + 1;
++extend;
}
maxExtends[i] = extend;
if (i + maxExtends[i] >= r)
center = i;
}
for (int i = 1; i < n; ++i)
l2r[i] = max(l2r[i], l2r[i - 1]);
return l2r;
}
};
We will now implement the solution in other languages.## Python Solution
python class Solution: def maxProduct(self, s: str) -> int: n = len(s) ans = 1 l = self.manacher(s, n) r = self.manacher(s[::-1], n) r.reverse() for i in range(n - 1): ans = max(ans, l[i] * r[i + 1]) return ans def manacher(self, s: str, n: int) -> list: maxExtends = [0] * n l2r = [1] * n center = 0 for i in range(n): r = center + maxExtends[center] - 1 mirrorIndex = center - (i - center) extend = 1 if i > r else min(maxExtends[mirrorIndex], r - i + 1) while i - extend >= 0 and i + extend < n and s[i - extend] == s[i + extend]: l2r[i + extend] = 2 * extend + 1 extend += 1 maxExtends[i] = extend if i + maxExtends[i] >= r: center = i for i in range(1, n): l2r[i] = max(l2r[i], l2r[i - 1]) return l2r
JavaScript Solution
javascript class Solution { maxProduct(s) { const n = s.length; let ans = 1; const l = this.manacher(s, n); const r = this.manacher(s.split('').reverse().join(''), n); r.reverse(); for (let i = 0; i + 1 < n; ++i) ans = Math.max(ans, l[i] * r[i + 1]); return ans; } manacher(s, n) { const maxExtends = new Array(n).fill(0); const l2r = new Array(n).fill(1); let center = 0; for (let i = 0; i < n; ++i) { const r = center + maxExtends[center] - 1; const mirrorIndex = center - (i - center); let extend = i > r ? 1 : Math.min(maxExtends[mirrorIndex], r - i + 1); while (i - extend >= 0 && i + extend < n && s[i - extend] === s[i + extend]) { l2r[i + extend] = 2 * extend + 1; ++extend; } maxExtends[i] = extend; if (i + maxExtends[i] >= r) center = i; } for (let i = 1; i < n; ++i) l2r[i] = Math.max(l2r[i], l2r[i - 1]); return l2r; } }
Java Solution
java class Solution { public int maxProduct(String s) { int n = s.length(); int ans = 1; int[] l = manacher(s, n); int[] r = manacher(new StringBuilder(s).reverse().toString(), n); int[] reverseR = new int[n]; for (int i = 0; i < n; ++i) { reverseR[i] = r[n - i - 1]; } for (int i = 0; i + 1 < n; ++i) { ans = Math.max(ans, l[i] * reverseR[i + 1]); } return ans; } private int[] manacher(String s, int n) { int[] maxExtends = new int[n]; int[] l2r = new int[n]; int center = 0; for (int i = 0; i < n; ++i) { int r = center + maxExtends[center] - 1; int mirrorIndex = center - (i - center); int extend = i > r ? 1 : Math.min(maxExtends[mirrorIndex], r - i + 1); while (i - extend >= 0 && i + extend < n && s.charAt(i - extend) == s.charAt(i + extend)) { l2r[i + extend] = 2 * extend + 1; ++extend; } maxExtends[i] = extend; if (i + maxExtends[i] >= r) { center = i; } } for (int i = 1; i < n; ++i) { l2r[i] = Math.max(l2r[i], l2r[i - 1]); } return l2r; } }
These solutions in C++, Python, JavaScript, and Java implement the Manacher's Algorithm to find the two non-intersecting palindromic substrings of odd length with the maximum product of their lengths in a given string s
.
Ready to land your dream job?
Unlock your dream job with a 2-minute evaluator for a personalized learning plan!
Start EvaluatorWhat are the most two important steps in writing a depth first search function? (Select 2)
Recommended Readings
LeetCode Patterns Your Personal Dijkstra's Algorithm to Landing Your Dream Job The goal of AlgoMonster is to help you get a job in the shortest amount of time possible in a data driven way We compiled datasets of tech interview problems and broke them down by patterns This way we
Recursion Recursion is one of the most important concepts in computer science Simply speaking recursion is the process of a function calling itself Using a real life analogy imagine a scenario where you invite your friends to lunch https algomonster s3 us east 2 amazonaws com recursion jpg You first
Runtime Overview When learning about algorithms and data structures you'll frequently encounter the term time complexity This concept is fundamental in computer science and offers insights into how long an algorithm takes to complete given a certain input size What is Time Complexity Time complexity represents the amount of time
Want a Structured Path to Master System Design Too? Don’t Miss This!