Lecture Overview: DSAI2201

PolyU DSAI2201 • Lecture 13 • 2025-11-25

Our Foundational Roadmap

This lecture series (DSAI2201) serves as our foundational roadmap for mastering efficient computation. We will systematically explore techniques for measuring efficiency and implementing fundamental organizational structures.

Key Units of Study

  1. Complexity Analysis ($\mathcal{O}$ Notation): Quantifying performance (Time and Space).
  2. Linear Structures: Arrays, Linked Lists, Stacks, and Queues.
  3. Non-Linear Structures (Trees): Heaps, BSTs, and specialized search structures.
  4. Non-Linear Structures (Graphs): Representation, Traversal (BFS/DFS), and shortest path algorithms.
  5. Advanced Optimization: Dynamic Programming and Greedy Algorithms.

Core Objective

By the end of this journey, you should be able to select, implement, and rigorously justify the most efficient data structure and algorithm for any given computational problem, moving beyond merely 'working' code to optimal code.

Structure vs. Action

  • Data Structures organize data for efficient access and modification.
  • Algorithms define the procedural steps (actions) taken on that data.

An efficient algorithm on a poorly chosen structure is often slower than a moderately efficient algorithm on an optimal structure.

📝 Interactive Quiz

1. What is the primary motivation for studying Complexity Analysis ($\mathcal{O}$ Notation) in depth?

  • A) To ensure code is bug-free.
  • B) To determine exactly how long a program takes to run in seconds.
  • C) To predict how algorithm running time scales relative to input size ($N$).
  • D) To standardize programming language syntax.

2. Which of the following best describes a "Data Structure"?

  • A) A step-by-step procedure for solving a problem.
  • B) A way of organizing and storing data for efficient access.
  • C) A specific programming language feature.
  • D) The process of compiling code.

3. Which of these is a non-linear data structure?

  • A) Array
  • B) Stack
  • C) Graph
  • D) Linked List

4. What is the ultimate goal of this course, beyond just writing functional code?

  • A) To write the shortest code possible.
  • B) To select and justify the most efficient solution for a problem.
  • C) To use the newest programming languages.
  • D) To memorize as many algorithms as possible.