CS202 -- Data Structures & Algorithms I: Spring, 2023

Lecture: 9:45 AM - 11:00 AM, Tuesdays & Thursdays in MK 622


Professor: James S. Plank MK320. jplank@utk.edu. Office hours by appointment only.

The grid of TA office hours is on the Canvas site. That also has their locations.


There are four labs for this course:



I'm going without a textbook because they are too expensive. I maintain copious lecture notes and they are your primary reference material. If you want additional material, I'll suggest Data Structures and Algorithm Analysis, by Mark Allen Weiss, Addison Wesley. At this point, they should be giving old editions away on Ebay/Amazon. The textbook is completely supplementary though.

Class Goals

The following are the goals that I have set for teaching this class -- they represent what I'd like you all to get out of the class. When the semester is over, go over this list, and see how well these goals were met. If you feel like it, send me email with comments -- it's more useful after the semester than in the middle of it, I think.

  1. To start becoming self-sufficient C++ programmers.

    This means that when you see a problem that needs to be coded, you have a good idea of how to go about it by writing a C++ program. This includes understanding the logistics of compiling, linking, including, etc., plus setting up the data structures, organizing the I/O, and using standard tools and libraries where appropriate.

    In case you're wondering, this includes understanding pointers, recursion and new/delete.

  2. To understand basic data structures.

    Frankly, there are only three to four basic data structures that can carry you through a lifetime of programming. All the rest are variations on a theme. By the end of this class, you should understand the basics and be prepared to tweak them when necessary.

  3. To understand basic algorithm analysis.

    Knowing how to set up your data structures is one thing. Understanding how fast your program should run is another. This class gets you started with algorithm analysis.