#1598

Easy

auto_awesomeStack-based state management

LeetCode Problem Workspace

Crawler Log Folder

Simulate folder navigation based on a list of operations to determine the current folder depth.

Problem Statement

You are given a list of folder operations where each operation is a string in the format of 'folder_name/' or './' or '../'. The task is to determine how many valid folder changes result in the current folder depth.

For each operation, you need to simulate the change in the folder structure. Use a stack to track the current path, and ensure that each operation updates the folder depth correctly, while ignoring redundant or invalid operations like going up from the root folder.

Examples

Example 1

Input: logs = ["d1/","d2/","../","d21/","./"]

Output: 2

Use this change folder operation "../" 2 times and go back to the main folder.

Example 2

Input: logs = ["d1/","d2/","./","d3/","../","d31/"]

Output: 3

Example details omitted.

Example 3

Input: logs = ["d1/","../","../","../"]

Output: 0

Example details omitted.

Constraints

1 <= logs.length <= 103
2 <= logs[i].length <= 10
logs[i] contains lowercase English letters, digits, '.', and '/'.
logs[i] follows the format described in the statement.
Folder names consist of lowercase English letters and digits.

Solution Approach

Simulate Folder Navigation

We simulate folder changes using a stack. For each operation, we either add a folder, move to the parent folder using 'cd ../', or ignore the operation when it's a 'cd ./'. This allows us to maintain the correct folder depth efficiently.

Process Each Operation Sequentially

Each log entry is processed in order. If it's a folder entry, push it onto the stack. If it's '../', pop the last folder from the stack. If it's './', do nothing. This sequence guarantees we only move within the folder structure correctly.

Handle Edge Cases

Ensure that redundant operations like multiple '../' when at the root or './' do not affect the stack. Only valid folder changes should be considered, ensuring that we correctly track folder depth.

Complexity Analysis

Metric	Value
Time	O(n)
Space	O(n)

The time complexity is O(n) because we process each log entry once. The space complexity is O(n) due to the stack's space requirements, where n is the number of logs.

What Interviewers Usually Probe

Candidates may struggle with handling redundant operations like './' and '../'.
Watch for efficient stack operations and correct handling of the root folder.
Evaluate if the candidate can explain their reasoning for using a stack to manage folder navigation.

Common Pitfalls or Variants

Common pitfalls

Failing to handle redundant './' operations.
Incorrectly managing folder navigation when attempting to move up from the root folder.
Not resetting or updating the stack correctly after each operation.

Follow-up variants

Modify the problem to support a different folder structure (e.g., nested folders).
Change the operations to include invalid paths and check for error handling.
Add operations that represent folder creation or deletion and track changes accordingly.

FAQ

What is the optimal approach for the Crawler Log Folder problem?

The optimal approach is to use a stack-based state management system, where we process each log entry and manage the folder depth using push and pop operations.

How does stack-based state management work for this problem?

Stack-based state management works by simulating folder navigation. Each folder is pushed onto the stack, and 'cd ../' pops the last folder. This approach keeps track of the folder depth efficiently.

How can I avoid errors when moving up from the root folder?

To avoid errors, ensure that '../' operations are ignored when the stack is empty (i.e., at the root folder), so the depth remains correct.

What are some edge cases to consider in the Crawler Log Folder problem?

Edge cases include handling operations like multiple '../' when at the root, and ignoring './' operations. These should not affect the stack or depth.

Can this problem be solved in less than O(n) time?

No, due to the need to process each log entry to maintain the correct folder depth, the time complexity must be O(n).

terminal

Solution

Solution 1

#### Python3

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class Solution:
    def minOperations(self, logs: List[str]) -> int:
        ans = 0
        for v in logs:
            if v == "../":
                ans = max(0, ans - 1)
            elif v[0] != ".":
                ans += 1
        return ans

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