CS 104c: Competitive Programming



Course Information

  • Instructional Mode: Face-to-face

Instructors

Prof. Etienne Vouga
https://www.cs.utexas.edu/~evouga/
Prof. Glenn Downing
https://www.cs.utexas.edu/~downing/

UGCAs

UGCA: Aiyaz Mostofa
Office Hours: W 2 pm, GDC basement
UGCA: Michael Xiang
Office Hours: Th 4 pm, GDC basement

Welcome Message

  • Sign in to Canvas and confirm your registration for the course. Check your grades regularly.
  • Confirm that you can access Ed Discussion on Canvas to post class questions.
  • If it involves something personal, like your grade, please make a private post on Ed Discussion.
  • Sign up for a Codeforces account.
  • Sign up for a GitLab account and clone the class repo to access the slides:
    • git clone https://gitlab.com/gpdowning-ut/cs104c.git
  • Sign up for a CSES account.
  • Sign up for a Zoom account. You must use your UT EID credentials. Ensure that you have the latest version of the app: 6.5.10

Communication

  • Please use Ed Discussion for all of your communication with the staff.

Catalog Description

  • Explores the algorithms needed to solve a given problem, reason about corner cases, and write correct implementations under time pressure.
  • Focuses on skills useful for international programming competitions, whiteboard job interviews, and programming tasks that require quickly solving challenging problems with creative use of algorithms.

Overview of the Class

Week Date Topic Contest
1 25 Aug Intro
2 01 Sep Labor Day
3 08 Sep Prefix Sums 1 (team)
4 15 Sep Graphs, Search, Shortest Path
5 22 Sep Binary Search 2 (individual)
6 29 Sep Greedy Algorithms
7 06 Oct Midterm #1 3 (team)
8 13 Oct DFS Backtracking
9 20 Oct Dynamic Programming I 4 (individual)
10 27 Oct Dynamic Programming II
11 03 Nov Midterm #2 5 (WiCS)
12 10 Nov Number Theory
13 17 Nov Union Find
14 24 Nov Fall Break
15 01 Dec String Algorithms
16 08 Dec Segment Trees
12 Dec Final Exam

Lectures Online

  • This class is using the Lectures Online recording system. This system records the audio and video material presented in class for you to review after class. Links for the recordings will appear in the Lectures Online tab on the Canvas page for this class. You will find this tab along the left side of the navigation in Canvas.
  • To review a recording, click on the Lectures Online navigation tab and follow the instructions on the page. You can learn more about how to use the Lectures Online system at http://sites.la.utexas.edu/lecturesonline/students/how-to-access-recordings/.
  • You can find additional information about Lectures Online at https://sites.la.utexas.edu/lecturesonline/.

Pre-Requisites of the Course

  • Computer Science 311 or 311H with a grade of at least C-, and registration or credit in Computer Science 314 or 314H with a grade of at least C-.

Software


Grading Policy

  • We expect each student to abide by the University of Texas Honor Code: "As a student of The University of Texas at Austin, I shall abide by the university's core values and uphold academic integrity." We permit discussing problem solutions with other students, asking others for conceptual help with a problem, looking online for tutorials explaining how to solve a problem, or getting help from a classmate debugging code you wrote. However, all code you turn in must be your own. The penalty for copying code (either from another student or the Internet) is an F in the course.
  • We will compute your grade with an innovative approach called specifications grading.
  • We will evaluate each assignment to see whether it meets the specifications.
  • Here's the EMRN scale:

  • The Canvas grade book uses a numerical scoring system, and therefore, we will map the EMRN scale onto a numerical scale:
    • E (2) [Excellent/Exemplary]
    • M (1) [Meets Expectations]
    • R / N (0) [Revision Needed / Not Assessable]
  • In this class, an E (2) will not affect your final grade. Instead, it will just be a recognition that you went above and beyond what we expected..

Assignments

Assignment R / N (0) M (1) E (2)
11 problems on Codeforces
  • 3 per week offered
  • resubmissions within one week
  • only three times
  • 1 problem per week
  • 3 problems per week
4 contests on Codeforces
  • must attend the entire contest
  • resubmissions within one week
  • only three times
  • 2 problems per contest
  • 5 problems per contest
11 problems on CSES
  • 3 per week offered
  • resubmissions within one week
  • only three times
  • 1 problem per week
  • 3 problems per week
11 find-the-bug problems on Canvas
  • 1 per week
  • resubmissions within one week
  • only three times
  • 1 problem per week
  • no E (2)s
11 quizzes on Canvas
  • 1 per week
  • makeups within one week
  • oral presentation to Dr. Vouga
  • only three times
  • 1 quiz per week
  • no E (2)s
3 tests on Codeforces
  • makeups within one week
  • oral presentation to Dr. Vouga
  • 2 problems per test
  • no E (2)s
  • Test makeups require a documented emergency excuse, medical excuse or UT-related event.
  • You must submit an emergency excuse to Student Emergency Services (SES). If the excuse is approved, SES will contact the instructor.

Grades

Letter Percent Codeforces Contests CSES Find the Bugs Quizzes Tests
11 4 11 11 11 3
A 94% 10 4 10 10 10 3
B 84% 9 3 9 9 9 2
C 74% 8 3 8 8 8 1
D 64% 7 3 7 7 7 0
  • Your course grade will depend on the number of assignments you complete with an M (1) or an E (2). It will then be the lowest grade in all assignment categories.

Generative Artificial Intelligence

  • AI tools (such as UT's Microsoft Copilot) and similar assistants can be valuable resources for learning and improving your code.
  • However, in this course, you are expected to use AI as a helper, not as a coder.
    • Do use AI to ask questions about concepts, debugging strategies, error messages, or ways to improve the clarity, style, or efficiency of your code.
    • Do use AI to deepen your understanding of why your code works, or doesn’t, and to learn alternative approaches.
    • Do not ask AI to generate solutions, write complete programs, or provide code that you then submit as your own.
  • The goal is for you to learn to think and code independently.
  • There is nothing to lose and everything to gain by asking an AI not to do your work but to critique it instead!

Overview of all Major Course Requirements and Assignments


Canvas Assignments


Required Course Materials

  • No required materials.

Recommended Course Materials


Final Exam Date and Time

  • Fri, 12 Dec, 7-9 pm: RLP 0.128

Class Canvas Site Weblink


Notice of Academic Accommodations from Disability and Access (D & A)

  • The university is committed to creating an accessible and inclusive learning environment consistent with university policy and federal and state law.
  • Please let us know if you experience any barriers to learning so I can work with you to ensure you have equal opportunity to participate fully in this course.
  • If you are a student with a disability or think you may have a disability and need accommodations, please get in touch with Disability and Access (D & A).
  • If you have already registered with D & A, please deliver your Accommodation Letter to me as early as possible in the semester so we can discuss your approved accommodations and needs in this course.

University Policies and Resources for Students Canvas Page

  • This Canvas page is a supplement to all UT syllabi and contains University policies and resources that you can refer to as you engage with and navigate your courses and the university.

Copyright © Glenn P. Downing, 2014-2025
Updated 26 Sep 2025