How do you solve Construct String With Repeat Limit on LeetCode?

Construct String With Repeat Limit (LeetCode #2182) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n log k) time complexity and O(k) space complexity. Key insight: Using a max heap allows us to efficiently access the largest character available.

What is the time complexity of Construct String With Repeat Limit?

The optimal solution for Construct String With Repeat Limit runs in O(n log k) time and uses O(k) space. The time complexity is O(n log k) where n is the length of the string and k is the number of unique characters. The heap operations take log k time.

What is the brute force solution for Construct String With Repeat Limit?

The brute force approach for Construct String With Repeat Limit is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves generating all possible strings from the characters of 's' and checking each one to see if it meets the repeat limit condition. This is simple but inefficient, as it explores too many combinations. The optimal Optimal Solution approach improves this to O(n log k).

What algorithm or data structure is used to solve Construct String With Repeat Limit?

Construct String With Repeat Limit uses the following concepts: Hash Table, String, Greedy, Heap (Priority Queue), Counting. The recommended patterns to study are: Greedy Algorithm, Heap (Priority Queue), Counting.

What are the interview tips for Construct String With Repeat Limit?

Always clarify the problem constraints and edge cases before diving into coding. Explain your thought process while coding to demonstrate your problem-solving skills. Practice writing clean and efficient code, as readability matters in interviews.

What are common mistakes when solving Construct String With Repeat Limit?

Failing to check the repeat limit correctly when constructing the string. Not considering edge cases where characters may run out before reaching the repeat limit.

#2182

Construct String With Repeat Limit

Medium

Hash TableStringGreedyHeap (Priority Queue)CountingGreedy AlgorithmHeap (Priority Queue)Counting

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n log k)
Space	O(1)	O(k)

💡

Intuition

Time O(n log k)Space O(k)

The optimal approach uses a greedy strategy with a max heap to construct the result string in descending order. This ensures we always pick the largest character available while respecting the repeat limit.

⚙️

Algorithm

3 steps

1Step 1: Count the frequency of each character in the string.
2Step 2: Use a max heap to store characters based on their lexicographical order.
3Step 3: Construct the result string by repeatedly adding characters from the heap, ensuring not to exceed the repeatLimit.

solution.py28 lines

1# Full working Python code
2import heapq
3from collections import Counter
4
5def repeatLimitedString(s, repeatLimit):
6    char_count = Counter(s)
7    max_heap = [-ord(char) for char in char_count]
8    heapq.heapify(max_heap)
9    result = ''
10
11    while max_heap:
12        current_char = -heapq.heappop(max_heap)
13        count = char_count[chr(current_char)]
14        use_count = min(count, repeatLimit)
15        result += chr(current_char) * use_count
16        char_count[chr(current_char)] -= use_count
17
18        if char_count[chr(current_char)] > 0:
19            if max_heap:
20                next_char = -heapq.heappop(max_heap)
21                result += chr(next_char)
22                char_count[chr(next_char)] -= 1
23                if char_count[chr(next_char)] > 0:
24                    heapq.heappush(max_heap, -next_char)
25                heapq.heappush(max_heap, -current_char)
26            else:
27                break
28    return result

ℹ

Complexity note: The time complexity is O(n log k) where n is the length of the string and k is the number of unique characters. The heap operations take log k time.

1Using a max heap allows us to efficiently access the largest character available.
2Greedy algorithms often yield optimal solutions in string manipulation problems.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.