DFS Algorithm in Go

[Shubham-Khetan-2005]

Add Depth-First Search (DFS) Traversal in Go

This implementation uses a recursive approach on a graph represented by an adjacency list. It traverses as far as possible along each branch before backtracking and returns the nodes in preorder (the order they are first visited).

Features 🚀

Represents an undirected graph with integer node IDs using an adjacency list.

Provides a DFS function to initiate the traversal from a specified start node.

Returns the sequence of visited nodes as a slice of integers.

Handles various graph structures, including disconnected components and isolated nodes.

Includes a sample test suite demonstrating correct behavior and edge cases (e.g., missing start node).

Complexity Analysis 📊

Time Complexity

O(V+E), where V is the number of vertices and E is the number of edges, as each vertex and edge is visited once.

Space Complexity

O(V) to store the visited set and for the recursion call stack in the worst-case scenario (for a path graph).

[github-actions]

💎 Code Quality Check Results

❌ Missing Algorithm Description

These files don't explain what the algorithm does:

• CPP/algorithms/sorting/Shell_Sort.cpp

Required: Add a description explaining the algorithm, its purpose, and how it works

⚠️ Insufficient Comments

These files have very few comments:

• CPP/algorithms/sorting/Shell_Sort.cpp

Recommended: Add inline comments explaining the logic and key steps

📚 Quality Standards

To maintain high quality, every contribution should include:

1. ✍️ Algorithm Description

   • Explain what the algorithm does
   • Describe the approach and methodology
   • Include use cases or applications

2. 📊 Complexity Analysis

   • Time complexity (e.g., O(n log n))
   • Space complexity (e.g., O(n))
   • Brief explanation of why

3. 💬 Meaningful Comments

   • Explain complex logic
   • Document function parameters
   • Add inline comments for clarity

4. ✅ Test Cases/Examples

   • Demonstrate the code works
   • Show different input scenarios
   • Include edge cases

💡 Example Template

"""
Binary Search Algorithm

Description: Searches for a target value in a sorted array using divide-and-conquer

Time Complexity: O(log n) - halves search space each iteration
Space Complexity: O(1) - only uses constant extra space
"""

def binary_search(arr, target):
    # Initialize pointers
    left, right = 0, len(arr) - 1

    while left <= right:
        mid = (left + right) // 2

        # Check if target found
        if arr[mid] == target:
            return mid
        # Search right half
        elif arr[mid] < target:
            left = mid + 1
        # Search left half
        else:
            right = mid - 1

    return -1  # Not found

# Test cases
if __name__ == "__main__":
    test_arr = [1, 3, 5, 7, 9]
    print(binary_search(test_arr, 5))  # Output: 2
    print(binary_search(test_arr, 6))  # Output: -1

🔧 How to Fix

1. Review each file mentioned above
2. Add the missing documentation
3. Push your changes
4. The workflow will re-run automatically

💪 You've Got This!

These checks help maintain quality and make your contribution more valuable to learners. Thank you for taking the time to improve! 🙏

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Quality over quantity - let's build something amazing together! 🌟

[github-actions]

🔍 Duplicate Detection Results

⚠️ Potential Duplicates Found

⚠️ Potential Duplicate: CPP/algorithms/sorting/Shell_Sort.cpp
Similar file(s) already exist:

• CPP/algorithms/sorting/Sorting/C++/Sorting/Shell_sort.cpp
• CPP/algorithms/sorting/Shell_Sort.cpp

⚠️ Potential Duplicate: Java/algorithms/sorting/RadixSortRevant.java
Similar file(s) already exist:

• Java/algorithms/sorting/RadixSortRevant.java
• Java/algorithms/sorting/RadixSortREVANT.java

📝 What This Means

We found existing implementations that appear similar to your contribution. This doesn't necessarily mean your PR will be rejected, but please review:

1. Is this truly a duplicate? Check the existing files to see if they implement the same algorithm
2. Is your implementation different/better? If so, explain in your PR description:
   • What makes it different
   • Why it's an improvement
   • Any unique features or optimizations
3. Consider improving existing code instead of adding a duplicate

✅ What To Do Next

• If it's a duplicate: Consider withdrawing this PR and improving the existing implementation
• If it's different: Add a clear explanation in your PR description about how it differs
• If unsure: Ask the maintainers for guidance!

💡 Quality Over Quantity

Remember: One high-quality, unique contribution is worth more than multiple duplicates! 🌟

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This is an automated check. Maintainers will make the final decision.

[github-actions]

🎉 Welcome to Hacktoberfest 2025, @Shubham-Khetan-2005! 🎃

Thank you for your first contribution to our DSA repository! Here's what happens next:

🔍 Automatic Checks

• ✅ Code Validation: Passed
• 🧪 Compilation Tests: Passed

📋 Next Steps

🎯 Great job! Your code compiled successfully. Maintainers @Karanjot786 and @Pradeepsingh61 will review your PR soon.

🎁 What You Get

• 🏆 Hacktoberfest Credit: This PR counts toward your 6 PR goal for exclusive T-shirt + Tree!
• 🌟 Hall of Fame: You'll be featured in our contributors list
• 📚 Learning: Code review feedback from experienced developers

💡 Tips for Success

• Follow our Contributing Guidelines
• Add comments explaining your algorithm
• Include time/space complexity analysis
• Test your code before submitting

Welcome to the community! 🚀

[github-actions]

🤖 Automated PR Status

🔍 Code Validation

✅ Passed - File naming and structure look good!

🧪 Compilation Tests

✅ Passed - All code compiles successfully!

📋 Overall Status

🎉 Ready for Review - Your PR has passed all automated checks!
👥 Maintainers have been notified for review.

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