Sorting Algorithms O(N^2) vs O(N log N)
Visualize Selection, Insertion, and Merge sort line-by-line. Track memory accesses, array swaps, and Big-O efficiency in real time.
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AP CSA
Binary Search Tree
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.
AP CSA
Array vs ArrayList Memory Resizing
Witness the internal array backing an ArrayList dynamically resize. Compare fixed memory bounds against O(N) copy operations when capacity is exceeded.
AP CSA
2D Array Traversal
Deconstruct nested loops covering Row-Major, Column-Major, and boundary tracing across a 2D integer matrix.
AP CSA
Big-O Complexity
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.