Explore object-oriented programming concepts of inheritance (creating subclasses that extend superclasses) and polymorphism (objects taking multiple forms). Understand the 'is-a' relationship, method overriding with @Override annotation, the super keyword for accessing parent class methods, and how polymorphism enables writing flexible code where superclass references can point to subclass objects, allowing dynamic method dispatch at runtime.
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.