LeetCode Problem

How to Solve Longest Subsequence Repeated k Times

To solve this problem, we need to identify the longest subsequence repeated k times in the string. Backtracking search with pruning is a suitable approach for this problem, and pruning helps cut down unnecessary search paths. Efficient handling of subsequences and lexicographical order is crucial to finding the correct solution.

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Problem #2014Backtracking search with pruningReviewed 2026-03-08
Difficulty
Hard
Primary pattern
Backtracking search with pruning
Answer-first problem summary
Step-by-step approach and complexity
GhostInterview solver workflow

To solve this problem, we need to identify the longest subsequence repeated k times in the string. Backtracking search with pruning is a suitable approach for this problem, and pruning helps cut down unnecessary search paths. Efficient handling of subsequences and lexicographical order is crucial to finding the correct solution.

Problem Statement

Given a string s and an integer k, you are tasked with finding the longest subsequence repeated exactly k times in s. A subsequence is derived from the string by removing characters while maintaining the original order of the remaining characters.

The problem requires finding the longest subsequence seq such that seq repeated k times is a valid subsequence of s. Your goal is to identify the lexicographically largest subsequence if there are multiple candidates. Note that the length of the longest subsequence will not exceed n/k.

Examples

Example 1

Input: s = "letsleetcode", k = 2

Output: "let"

There are two longest subsequences repeated 2 times: "let" and "ete". "let" is the lexicographically largest one.

Example 2

Input: s = "bb", k = 2

Output: "b"

The longest subsequence repeated 2 times is "b".

Example 3

Input: s = "ab", k = 2

Output: ""

There is no subsequence repeated 2 times. Empty string is returned.

Constraints

  • n == s.length
  • 2 <= k <= 2000
  • 2 <= n < min(2001, k * 8)
  • s consists of lowercase English letters.

Solution Approach

Backtracking Search with Pruning

Start with a backtracking search to explore possible subsequences and attempt to form seq repeated k times. Use pruning to discard invalid or unnecessary paths early in the search process.

Greedy Selection for Lexicographical Order

To handle multiple subsequences of the same length, employ a greedy approach to select the lexicographically largest subsequence among the valid options.

Efficient Pruning Strategy

As the subsequence is built, prune paths that cannot possibly lead to a valid sequence repeated k times. This reduces the search space and improves efficiency.

Complexity Analysis

MetricValue
TimeO(n \cdot {\lfloor \dfrac{n}{k} \rfloor}!)
SpaceO(\lfloor \dfrac{n}{k} \rfloor!)

The time complexity is O(n · ⌊n/k⌋!), where n is the length of the string, and ⌊n/k⌋ is the upper limit on the length of the subsequence. The space complexity is O(⌊n/k⌋!), driven by the recursive depth and subsequence storage.

What Interviewers Usually Probe

  • Can the candidate identify the importance of pruning in reducing the search space?
  • Does the candidate understand the relationship between subsequence length and k?
  • How well does the candidate handle lexicographical ordering in the subsequence selection?

Common Pitfalls or Variants

Common pitfalls

  • Failing to prune search paths that cannot possibly yield valid subsequences.
  • Overlooking the lexicographical order requirement when multiple valid subsequences exist.
  • Incorrectly assuming the subsequence length can exceed n/k.

Follow-up variants

  • Modify the problem to find subsequences repeated m times for a different integer m.
  • Change the problem to find the shortest subsequence repeated k times.
  • Consider the case where the subsequence must be contiguous instead of a general subsequence.

How GhostInterview Helps

  • GhostInterview assists by offering detailed explanations of backtracking with pruning for subsequence problems.
  • It provides examples and step-by-step strategies for handling lexicographical order in subsequences.
  • GhostInterview aids in understanding how to handle pruning effectively, making your solution more efficient.

Topic Pages

FAQ

What is the primary pattern to solve the Longest Subsequence Repeated k Times problem?

The primary pattern is backtracking search with pruning, which explores subsequences efficiently while eliminating unnecessary paths.

How does pruning help in the Longest Subsequence Repeated k Times problem?

Pruning reduces the search space by discarding subsequences that cannot possibly form a valid sequence repeated k times, improving efficiency.

What is the time complexity of the Longest Subsequence Repeated k Times problem?

The time complexity is O(n · ⌊n/k⌋!), where n is the length of the string and ⌊n/k⌋ is the upper bound on subsequence length.

How do you handle lexicographical order in this problem?

Use a greedy strategy to select the lexicographically largest subsequence when multiple subsequences of the same length are possible.

What does it mean for a subsequence to be repeated k times?

A subsequence is repeated k times if concatenating the subsequence k times results in a valid subsequence of the string s.

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