Chapter 01
Foundations & The Hardware Reality
- 01.1 Computational Complexity — Demystifying Time and Space Big O notation through code loops.
- 01.2 Memory Layouts — How data actually sits in the Stack vs Heap allocations, and the role of pointers.
Chapter 02
Linear Data Structures
- 02.1 Static & Dynamic Arrays — Contiguous block allocations, random access mechanics, and capacity scaling.
- 02.2 Singly & Doubly Linked Lists — Scattered heap nodes linked by memory references.
- 02.3 Stacks & Queues — LIFO and FIFO execution profiles built over arrays and linked lists.
Chapter 03
Non-Linear Structures
- 03.1 Binary Trees & BSTs — Hierarchical parent-child links, searching properties, and traversal strategies.
- 03.2 Heaps & Priority Queues — Array-represented complete binary trees optimized for min/max tracking.
- 03.3 Hash Maps & Hashing — Fast lookup keys, hash functions, and bucket collision strategies.
Chapter 04
Algorithmic Paradigms
- 04.1 Sorting & Searching — Breaking down QuickSort, MergeSort, and binary search logic.
- 04.2 Recursion & Backtracking — Handling call stack frames, base states, and depth-first decision spaces.
Chapter 05
Advanced Optimization
- 05.1 Graph Algorithms — Adjacency lists vs matrices, BFS, DFS, and shortest-path trees.
- 05.2 Dynamic Programming — Overcoming recursive overlaps via memoization and tabular state layouts.