Visualize recursive function calls and the call stack to understand how recursion works. Explore the essential components: base case (stopping condition) and recursive case (function calling itself with modified parameters). Trace classic examples like factorial, Fibonacci sequence, and binary search. Understand stack frames, how recursive calls build up then unwind, and compare recursion with iterative solutions for efficiency and readability.
Construct dynamic 2D Binary Search Trees element by element. Run animated depth-first traversals (In-order, Pre-order, Post-order) stepping through the recursive call stack.
Witness the internal array backing an ArrayList dynamically resize. Compare fixed memory bounds against O(N) copy operations when capacity is exceeded.
Deconstruct nested loops covering Row-Major, Column-Major, and boundary tracing across a 2D integer matrix.
Analyze algorithm efficiency using Big-O notation to describe time and space complexity. Compare O(1) constant time, O(log n) logarithmic, O(n) linear, O(n log n) linearithmic, O(n²) quadratic, and O(2ⁿ) exponential growth rates. Visualize how input size affects runtime, understand best/average/worst case scenarios, and learn to identify complexity by analyzing loops, recursion depth, and data structure operations.