How do you solve Delete Duplicate Folders in System on LeetCode?

Delete Duplicate Folders in System (LeetCode #1948) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Identical folders are determined by their subfolder structures.

What is the brute force solution for Delete Duplicate Folders in System?

The brute force approach for Delete Duplicate Folders in System is Brute Force, with O(n²) time complexity and O(n) space complexity. The brute-force approach involves comparing each folder with every other folder to check for duplicates by examining their subfolder structures. This method is straightforward but inefficient as it requires multiple comparisons. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Delete Duplicate Folders in System?

Delete Duplicate Folders in System uses the following concepts: Array, Hash Table, String, Trie, Hash Function. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Delete Duplicate Folders in System?

Think about how to represent the folder structure uniquely. Consider edge cases and how they might affect your solution. Practice explaining your thought process clearly as you code.

What are common mistakes when solving Delete Duplicate Folders in System?

Not considering all levels of subfolders when checking for duplicates. Failing to handle edge cases where folders may have different names but identical structures.

#1948

Delete Duplicate Folders in System

Hard

ArrayHash TableStringTrieHash FunctionHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(n)

The optimal solution utilizes a hash map to store folder structures and their paths, allowing for efficient identification of duplicates. By representing the folder structures as strings, we can quickly compare them.

⚙️

Algorithm

4 steps

1Step 1: Create a hash map to store folder structures and their paths.
2Step 2: For each path, generate a unique representation of its structure.
3Step 3: If a structure is already in the map, mark it as a duplicate.
4Step 4: Filter out the marked duplicates and return the remaining paths.

solution.py18 lines

1def deleteDuplicateFolders(paths):
2    from collections import defaultdict
3
4    def get_structure(path):
5        return '/'.join(sorted(path))
6
7    structures = defaultdict(list)
8    duplicates = set()
9
10    for path in paths:
11        structure = get_structure(path)
12        structures[structure].append(path)
13
14    for key, value in structures.items():
15        if len(value) > 1:
16            duplicates.add(key)
17
18    return [path for path in paths if get_structure(path) not in duplicates]

ℹ

Complexity note: The time complexity is O(n) because we only traverse the list of paths a few times. The space complexity is O(n) due to the storage of folder structures and duplicates.

1Identical folders are determined by their subfolder structures.
2Using a hash map allows for efficient storage and retrieval of folder structures.

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