Is Longest Duplicate Substring easy or hard?

Longest Duplicate Substring is classified as a hard problem because it requires combining multiple algorithmic concepts such as binary search, rolling hash, or suffix arrays. Efficient solutions must avoid naive substring comparisons, which quickly become too slow for large inputs.

How to solve Longest Duplicate Substring in O(n)?

True O(n) solutions exist using advanced suffix array or suffix tree algorithms with linear-time construction and longest common prefix processing. These techniques are complex and rarely expected in interviews. Most practical implementations use O(n log n) time with binary search and rolling hash.

What is the best approach for Longest Duplicate Substring?

Binary search combined with rolling hash (Rabin–Karp) is the most practical approach. It searches for the maximum substring length while verifying duplicates using hash values in O(n) time per check. The overall complexity becomes O(n log n) with O(n) extra space. This solution is widely used in coding interviews and competitive programming.

Is Longest Duplicate Substring asked at Google/Amazon/Meta?

Longest Duplicate Substring is considered a hard string problem and appears in interviews at companies that test advanced algorithmic knowledge. Variants involving rolling hash, suffix arrays, or longest repeated substring logic have been reported in interviews at companies like Google and Amazon.

What data structure is used in Longest Duplicate Substring?

Common structures include hash sets for storing rolling hash values, arrays for prefix hashes and powers, and suffix arrays for lexicographic ordering of suffixes. These structures enable efficient substring comparison without directly comparing characters repeatedly.

What is the time complexity of Longest Duplicate Substring?

The optimal solutions run in O(n log n) time. Binary search over substring length requires log n iterations, and each iteration checks duplicates using rolling hash in O(n). Suffix array based approaches also run in roughly O(n log n) time depending on the construction algorithm.

Longest Duplicate Substring Python or Java solution approach?

Both Python and Java solutions typically implement binary search on substring length with a rolling hash (Rabin–Karp). A sliding window computes hash values for substrings of length L, and duplicates are detected using a hash set. This approach runs in O(n log n) time and O(n) space.

Description Hints 2 Solution Video 29:42

1044. Longest Duplicate Substring

Hard31.1% acceptance7 companies

Given a string s, consider all duplicated substrings: (contiguous) substrings of s that occur 2 or more times. The occurrences may overlap.

Return any duplicated substring that has the longest possible length. If s does not have a duplicated substring, the answer is "".

Example 1:

Input: s = "banana"
Output: "ana"

Example 2:

Input: s = "abcd"
Output: ""

Constraints:

2 <= s.length <= 3 * 10⁴
s consists of lowercase English letters.

Asked at 7 companies

Coupang Tiktok

Google Amazon Goldman Sachs Meta Bloomberg

Topics

Hints open one at a time

Hint 1

Binary search for the length of the answer. (If there's an answer of length 10, then there are answers of length 9, 8, 7, ...)

Hint 2

To check whether an answer of length K exists, we can use Rabin-Karp 's algorithm.

29:42

Still stuck?Read 3 approaches, or watch a walkthrough.

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1class Solution:
2    def longestDupSubstring(self, s: str) -> str:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2

Input

"banana"

Input

"abcd"

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