Add js tree data structures

[sea-deep]

Summary

Adds core Tree Data Structure implementations and algorithms in JavaScript.

Changes Included

• Generic Tree: Classes for nodes and trees that allow multiple children.
• Binary Search Tree (BST) Traversal:
  • Depth-First Search (DFS): inorder, preorder, postorder.
  • Breadth-First Search (BFS): levelOrder.
• AVL Tree: Basic implementation for a self-balancing tree (Node, Insertion, Rotations).

Purpose

This code provides fundamental algorithms for handling hierarchical data, which is useful for data modeling and future feature development.

Review Focus

Please verify the logic for the traversal methods (DFS and BFS).

[github-actions]

💎 Code Quality Check Results

❌ Missing Complexity Analysis

These files don't include time/space complexity:

• JavaScript/data_structures/trees/avl_tree.js
• JavaScript/data_structures/trees/bst_traversal.js

Required: Add comments explaining time and space complexity (e.g., Time: O(n log n), Space: O(n))

❌ Missing Algorithm Description

These files don't explain what the algorithm does:

• JavaScript/data_structures/trees/avl_tree.js
• JavaScript/data_structures/trees/bst_traversal.js

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

⚠️ No Test Cases or Examples

These files don't include test cases:

• JavaScript/data_structures/trees/avl_tree.js

Recommended: Add example usage or test cases to demonstrate the code works

📚 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]

🎉 Welcome to Hacktoberfest 2025, @sea-deep! 🎃

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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