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📚 CS210 — Data Structures and Algorithms

This course focuses on how data is organized, stored, and processed efficiently. It covers fundamental data structures, algorithm analysis, and practical implementation techniques essential for software development and system design.

This section contains structured study material including topic-based notes, algorithm analysis explanations, and cheat sheets for revision and quick reference. The goal is a clear, practical resource for understanding the material and preparing for exams and programming tasks.

🧭 How to Use This Section

Depending on where you are in the course, use this section differently.

If you are following the course, start with the basic data representation topics and progress toward more advanced structures in order. If you are revising, go directly to the cheat sheets and the topics you find most difficult. If you are practicing implementation, use the topic pages as references for behavior, operations, and complexity.

🗂 Course Topics

  • 🔗 Linked Objects & Data Structures

    How data is represented in memory, object references, and dynamic structures.

  • ↪ Linked Lists

    Single, double, and circular linked lists — traversal, insertion, and deletion operations.

  • 📊 Analysis of Algorithms

    Big O notation, time and space complexity, and iterative versus recursive analysis.

  • 🔄 Sorting Algorithms

    Selection sort, insertion sort, merge sort, and quick sort.

  • 📦 Stacks & Queues

    LIFO and FIFO structures and their applications in compilers and operating systems.

  • 🌳 Binary Trees & BSTs

    Tree traversal methods — inorder, preorder, postorder — plus searching, insertion, and deletion.

  • ⚖ AVL Trees

    Self-balancing trees, rotations, and height maintenance.

  • 🏆 Heaps & Priority Queues

    Binary heaps, heap operations, and practical applications.

  • #⃣ Hashing

    Hash functions and collision resolution techniques including chaining and probing.

  • 🌐 Graphs

    Directed and undirected graphs, graph representations, DFS, BFS, and real-world applications.

🗒 Study & Revision Material

In addition to the topic notes, this section includes cheat sheets for quick revision and condensed references for common operations and complexities. These are designed to support both deep understanding and efficient exam preparation.

Step Topic
1 Linked objects and basic data structures
2 Algorithm analysis — understand performance early
3 Linear structures: linked lists, stacks, and queues
4 Trees, AVL trees, and heaps
5 Hashing and graphs
6 Cheat sheets for revision and quick recall before exams

About This Material

These notes are based on my own coursework and personal study. The focus is on clarity, structure, and practical understanding. Content will continue to be refined and expanded over time.