Alibaba Interview Question: Path Merge & Directory Summarization Depth Analysis

Top tech companies like Alibaba often design complex and detail-oriented algorithmic problems to comprehensively evaluate a candidate's logical reasoning, algorithm design, and adaptability under pressure.

This article uses a real Alibaba technical interview question to demonstrate how candidates can showcase their best performance with real-time assistance from oavoservice.

📋 Technical Interview Question

Problem Description

Given a list of current directories and a list of selected directories, return the selected directories after summarizing.

Example Input/Output:

Current Directories:
["/a", "/a/b", "/a/b/c", "/a/b/c/d", "/a/e"]

Selected Directories:
["/a/b/c", "/a/b/c/d", "/a/e"]

Expected Output:
["/a/b/c", "/a/e"]

Objective: Combine and summarize selected directories by collapsing redundant subdirectories under their parent directory.

Explanation:

• /a/b/c/d is a subdirectory of /a/b/c, so it can be omitted.
• Finally, only keep /a/b/c and /a/e.

🎯 Core Concepts Analysis

This question mainly tests:

1. String Processing: Parsing and comparing paths.
2. Prefix Matching: Determining parent-child directory relationships.
3. Data Structure Choice: Trie tree or Sorting + Traversal.
4. Edge Case Handling: Handling special path formats.

💡 Solution Strategy (oavoservice Guidance)

Clarification Phase

oavoservice Reminder: Before coding, be sure to clarify the following:

1. Is the path format standard? (Does it start with /, does it have a trailing /?)
2. Are there duplicate paths?
3. Do we need to handle file paths (with extensions)?
4. Is the input already sorted?

Method 1: Sorting + Prefix Matching

oavoservice Suggestion: The most intuitive method is to sort first, then check if each path is a subdirectory of the previous path.

def summarize_directories(selected):
    if not selected:
        return []
    
    # Sort: Ensure parent directories come before subdirectories
    selected.sort()
    
    result = []
    for path in selected:
        # Check if it is a subdirectory of the previous path
        if not result or not path.startswith(result[-1] + '/'):
            result.append(path)
    
    return result

# Test
selected = ["/a/b/c", "/a/b/c/d", "/a/e"]
print(summarize_directories(selected))
# Output: ['/a/b/c', '/a/e']

Time Complexity: O(n log n + n × m)

• n is the number of paths
• m is the average path length

Space Complexity: O(1) (ignoring output)

Method 2: Trie Tree (Optimized)

oavoservice Advanced Guidance: For large-scale data or frequent queries, a Trie tree is a better choice.

class TrieNode:
    def __init__(self):
        self.children = {}
        self.is_selected = False

def summarize_with_trie(selected):
    root = TrieNode()
    
    # Build Trie
    for path in selected:
        node = root
        parts = path.split('/')[1:]
        for part in parts:
            if part not in node.children:
                node.children[part] = TrieNode()
            node = node.children[part]
        node.is_selected = True
    
    # DFS to collect results
    result = []
    def dfs(node, path):
        if node.is_selected:
            result.append('/' + '/'.join(path))
            return
        for name, child in node.children.items():
            dfs(child, path + [name])
    
    dfs(root, [])
    return result

🚀 Deep Follow-up Questions in Interviews

Q1: How to handle a mix of file paths and directory paths?

oavoservice Suggestion:

• Process files and directories separately.
• File paths need to be preserved individually.
• Directory paths are processed according to merge rules.

Q2: What if the paths are very deep (1000+ levels)?

oavoservice Suggestion:

• Use iteration instead of recursion to avoid stack overflow.
• Consider path compression techniques.
• Use generators to reduce memory usage.

Q3: How to optimize processing for large-scale data?

oavoservice Suggestion:

• Use parallel processing.
• Process paths in batches.
• Use more efficient data structures (like Prefix Trees).

📊 Complexity Comparison

Method	Time Complexity	Space Complexity	Applicable Scenario
Sorting + Traversal	O(n log n)	O(1)	General scenarios
Trie	O(n × m)	O(n × m)	Frequent queries
Hash Set	O(n × m²)	O(n)	Small scale data

💼 How oavoservice Helps with Alibaba Interviews

In Alibaba interviews, oavoservice provides:

Problem Clarification Guidance: Ensure understanding of requirements. Algorithm Selection Advice: Quickly find the optimal solution. Code Implementation Assistance: Ensure logic is clear and correct. Follow-up Response Strategy: Confidently answer deep follow-ups. Optimization Discussion: Demonstrate engineering practice capabilities.

Want to stand out in interviews with top tech companies like Alibaba, ByteDance, Tencent, etc.?

Contact oavoservice for professional VO interview assistance services to help you secure your Offer smoothly.

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Tags: #Alibaba #StringProcessing #Trie #PathMerge #InterviewPrep #VOHelp #1point3acres

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