Data Structure and Algorithm Design II

Course Introduction

Xingang (Ian) Fang

Introduction to HTML Slides

System:
- Sphinx
- Reveal.js
Navigation:
- Left/Right Arrow
- Up/Down Arrow
- Space Bar
- Esc Key
Print:
- add “?print-pdf” to the URL after .html
- choose number of slides per page

Description:

A second course in Data Structures and Algorithms covers topics including the mathematical properties of algorithms (complexity, correctness), trees and graphs, hashing, relational (database) structures, Dynamic Programming, and numerical programming. The emphasis is on issues of correctness and efficiency. Students entering this course are expected to have a solid knowledge of programming.
Keywords:

Abstract Data Type (ADT); Data Structure; Algorithm; Algorithm Analysis; Recursion; Self-balancing trees; Master Theorem; Graph; Counting; Greedy algorithms; Genetic algorithms; Dynamic programming;

Develop solutions to problems by applying algorithms discussed in class.
Develop solutions that emphasize mathematical and scientific problems.
Write algorithms for solving problems prior to coding.
Analyze solutions in terms of time complexity.
Solve probability problems and counting problems with permutations and combinations.
Utilize greedy algorithms when applicable.
Construct graphs and implement representative algorithms.
Analyze and contrast graph based solutions.
Construct solutions that make use of Dynamic Programming techniques.

Required textbook in this course
- Data Structures and Algorithm Analysis in C++, 4th Edition. Mark Allen Weiss.
- ISBN-13: 978-0132847377

Learn Canvas LMS: Notification tool, calendar, mobile app
Front page gives a calendar view of the course schedule
- Follow the links to modules, pages, and assignments
Zoom tab
- Find perspective meetings
- View recordings of past classes

During the first weeks, actively follow the live walkthroughs for the course setup, Canvas layout, Git, Classroom 50, labs, and projects.
Take notes and ask questions as soon as a step is unclear. Reconstructing a missed technical workflow later is usually slower and more stressful.
Flexible attendance does not change your responsibility to learn workflows demonstrated in class. Later assignments build on these skills.
Before asking for help:
1. Read the lab or project instructions and locate the relevant Canvas module.
2. Review the class Zoom recording if you missed or need to repeat a demonstration.
3. Reproduce the problem and copy the exact command and error message.
4. Push your current code before requesting help with a programming problem.

Provided by the instructor as a supplement to the textbook

Supplemental Material Website

Code Example Repository

Keep updated 🔔
- Group email
- Canvas announcement
- Discord @everyone message
Get help
- Discord - sharable questions
- Email; Discord DM - private questions, identify yourself first
- Zoom (Office hour, appointment, etc.)
- Always share your whole project by pushing to GitHub when asking help on code
Avoid 🚫
- Canvas/Navigation messages
- Provide error messages or screenshots without code

Two midterm exams
- 75 minutes
- First class meeting time in week 6 and 11
Comprehensive final exam
- 150 minutes
- during final exam week
- University schedule