Class: DSAVisualizer::DataStructures::BinaryTree

Inherits:
Object
  • Object
show all
Defined in:
lib/dsa_visualizer/data_structures/binary_tree.rb

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize ⇒ BinaryTree

Returns a new instance of BinaryTree.



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# File 'lib/dsa_visualizer/data_structures/binary_tree.rb', line 16

def initialize
  @root = nil
end

Instance Attribute Details

#root ⇒ Object (readonly)

Returns the value of attribute root.



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# File 'lib/dsa_visualizer/data_structures/binary_tree.rb', line 14

def root
  @root
end

Class Method Details

.demo ⇒ Object 



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# File 'lib/dsa_visualizer/data_structures/binary_tree.rb', line 43

def self.demo
  Visualizer.print_header("BINARY SEARCH TREE - Core Level Visualization")
  
  Visualizer.print_section("1. BST Concept")
  puts "\nBinary Search Tree properties:"
  puts "  - Left subtree < node < right subtree"
  puts "  - Enables O(log n) search in balanced tree"
  puts "  - Can degrade to O(n) if unbalanced"
  
  Visualizer.print_section("2. Implementation Comparison")
  
  ruby_code = <<~RUBY
    class TreeNode
      attr_accessor :value, :left, :right
      def initialize(value)
        @value = value
        @left = @right = nil
      end
    end
    
    # Ruby: object references for children
    # GC handles memory
  RUBY

  cpp_code = <<~CPP
    struct TreeNode {
      int value;
      TreeNode *left, *right;
      TreeNode(int v) : value(v), 
        left(nullptr), right(nullptr) {}
    };
    
    // C++: explicit pointers
    // Manual memory management
  CPP

  explanation = "Both use pointer-based structure. Ruby uses object references with GC, C++ uses raw pointers requiring manual deletion. Tree traversal is same in both."
  
  Visualizer.print_comparison(ruby_code, cpp_code, explanation)
  
  tree = BinaryTree.new
  values = [50, 30, 70, 20, 40, 60, 80]
  
  Visualizer.print_step(1, "Inserting values: #{values.join(', ')}")
  values.each { |v| tree.insert(v) }
  
  puts "\nTree structure:"
  puts "        50"
  puts "       /  \\"
  puts "      30   70"
  puts "     / \\   / \\"
  puts "    20 40 60 80"
  
  puts "\n\nšŸŽÆ Key Takeaways:".colorize(:green).bold
  puts "  1. BST enables efficient searching: O(log n) average"
  puts "  2. Insertion/deletion: O(log n) average"
  puts "  3. Worst case O(n) for unbalanced tree"
  puts "  4. Self-balancing trees (AVL, Red-Black) maintain O(log n)"
end

.learn ⇒ Object 



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# File 'lib/dsa_visualizer/data_structures/binary_tree.rb', line 39

def self.learn
  demo
end

Instance Method Details

#insert(value) ⇒ Object 



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# File 'lib/dsa_visualizer/data_structures/binary_tree.rb', line 20

def insert(value)
  @root = insert_recursive(@root, value)
end