CS 141 Winter 2025¶
Course Information¶
Welcome to CS 141 Winter 2025 at UC Riverside!
The goal of this course is to learn and explore data structures and basic algorithms design and analysis. It will cover the following topics:
- Algorithms analysis (asymptotic notation & recurrence relations)
- Divide-and-conquer algorithms
- Greedy algorithms
- Dynamic programming
- Graph data structures and algorithms
- Advanced topics in algorithms analysis and design (e.g. NP-Completeness, reductions)
Lecture
- Prof. Mingxun Wang - 11 AM MWF
- Prof. Mingxun Wang - 3 PM MWF
Discussion
- Xianghu Wang - Tuesday 8AM PST
- Michael Strobel - Friday 9AM PST
- Ziyang Men - Tuesday at 8PM PST
NOTE: Please attend your assigned discussion section as there is limited seating.
Office Hours
- Prof. Mingxun Wang - Monday 12PM - 1PM - MRB 4122
- TA Ziyang Men - Tuesday 10AM - 11AM - WCH 110
- Prof. Mingxun Wang - Wednesday 1PM - 2PM - MRB 4122
- TA Michael Strobel - Thursday 2PM - 3PM - MRB 2133
- TA Xianghu Wang - Friday 4PM - 5PM - MRB 3rd Floor Inside Near Balcony
Prerequisite(s): CS 014 with a grade of “C-” or better; CS 111; MATH 009C or MATH 09HC; proficiency in C++.
Logistics¶
All written homework and homework solutions will be posted to UCR's Canvas Online System. Graded homework and midterms will be posted to gradescope. Final course grades will be directly transferred to campus after finals.
Instructional Personel¶
- Prof. Mingxun Wang - mingxun.wang@cs.ucr.edu
Teaching Assistants
- Michael Strobel (michael.strobel@email.ucr.edu) - Head TA
- Xianghu Wang (xwang473@ucr.edu)
- Ziyang Men (ziyang.men@email.ucr.edu)
Class Communcation¶
We will use Canvas for class communication for announcements. If you need to contact a TA or Professor, please use email.
Reading Materials¶
Introduction to Algorithms (CLRS).
Third Edition. Cormen, Leiserson, Rivest, and Stein. MIT Press.
Prerequisite knowledge in the book that will not be taught in this course: Please make sure you understand Sections 6, 10-13, and 22.1-22.3 in the book.
Course Schedule¶
| Date | Subject | Section 001 End Slide | Section 002 End Slide |
|---|---|---|---|
| 1/6/2025 - Monday | Introduction | Lecture 2 - Slide 16 | Lecture 2 - Slide 1 |
| 1/8/2025 - Wednesday | Analysis of Algorithms | ||
| 1/10/2025 - Friday | Analysis of Algorithms | ||
| 1/13/2025 - Monday | Divide and Conquer | ||
| 1/15/2025 - Wednesday | Divide and Conquer | ||
| 1/17/2025 - Friday | Divide and Conquer | ||
| 1/20/2025 - Monday | MLK Day | ||
| 1/22/2025 - Wednesday | Greedy Algorithms | ||
| 1/24/2025 - Friday | Greedy Algorithms | ||
| 1/27/2025 - Monday | Greedy Algorithms | ||
| 1/29/2025 - Wednesday | Greedy Algorithms | ||
| 1/31/2025 - Friday | Midterm Exam 1 | ||
| 2/3/2025 - Monday | Greedy Algorithms | ||
| 2/5/2025 - Wednesday | Greedy Algorithms | ||
| 2/7/2025 - Friday | Dynamic Programming | ||
| 2/10/2025 - Monday | Dynamic Programming | ||
| 2/12/2025 - Wednesday | Dynamic Programming | ||
| 2/14/2025 - Friday | Dynamic Programming | ||
| 2/17/2025 - Monday | President's Day | ||
| 2/19/2025 - Wednesday | Dynamic Programming | ||
| 2/21/2025 - Friday | Midterm Exam 2 | ||
| 2/24/2025 - Monday | Dynamic Programming | ||
| 2/26/2025 - Wednesday | Graphs | ||
| 2/28/2025 - Friday | Graphs | ||
| 3/3/2025 - Monday | Graphs | ||
| 3/5/2025 - Wednesday | Revisiting Divide and Conquer | ||
| 3/7/2025 - Friday | Revisiting Greedy | ||
| 3/10/2025 - Monday | Revisiting Dynamic Programming | ||
| 3/12/2025 - Wednesday | Revisiting Dynamic Programming | ||
| 3/14/2025 - Friday | Review Problems |
Student Resources (Slides and other resources)¶
Slides will be made available at the following links after the lecture is given.
- Section 1 and 2 (Wang): All Slides
- Discussion Slides: All Slides
Homeworks¶
Homeworks will be posted on Canvas.
You must submit your solutions (in pdf format generated by LaTeX) via GradeScope. Canvas will not be accepted.
Homeworks will be due at 11:59 PM PST on the due date.
| Release Date | Due Date | Description |
|---|---|---|
| 1/6/2025 | 1/21/2025 | HW1 |
| 1/20/2025 | 2/4/2025 | HW2 |
| 2/3/2025 | 2/18/2025 | HW3 |
| 2/17/2025 | 3/4/2025 | HW4 |
| 3/3/2025 | 3/15/2025 | HW5 |
- Unless mentioned otherwise, late submission allowed for 20% penalty for each calendar day, with the calendar day rolling over at 11:59 PM PST.
- Assignments should be computer-typed and submitted on GradeScope.
- You are expected to understand any source you use and solve problems in your own.
You can get help from the instructor and TA. You can also get help from textbooks (or relevant books), the Internet, or discussions with your classmates, but you must cite them fully and completely (i.e., provide citations to the book or website link, acknowledge the other students that had discussions with you). However, you are NOT allowed to:
- Copy anything from the book or the internet
- Read or look up other's solutions in this course
- Share your solutions with any other students during or after the compleition of this course
It’s OK to get inspirations from other sources, and citing the sources does not affect your grade. However, using any source without citing them will be treated as cheating and will result in unfavorable outcomes.
If you use any AI-based resources (e.g., ChatGPT or other LLMs), you need to provide the full conversation with it to clearly specify what kind of help you received from it.
When you write down your solution, it MUST be close-book. This is to make sure you truly understand and can recreate the solutions.
NOTE: If you share your solutions with others in the course and they turn in a plagarized copy of your answer, we will not distinguish who was the source or the recipient of the material, both parties will be penalized.
Course Work/Grade Breakdown¶
- Five homework assignments (20%) - 4% each
- Two mid-term exams (35%) - 17.5% each
- Final inclusive exam (45%)
- Section 001 - Thursday, March 20, 11:30 a.m. - 2:30 p.m.
- Section 002 - Monday, March 17, 3:00 p.m. - 6:00 p.m.
- Participation (+1% Bonus)
NOTE: Participation will be awarded at the end of the quarter if Ming can recognize your name when compiling final grades. The best way to get this part of the bonus is to attend office hours.
Academic Integrity¶
We have the highest standards and expectations for academic integrity. Please refer to the UCR Guidelines.
Any work submitted as a homework assignment or examination must be entirely your own and may not be derived from the work of others, whether a published or unpublished source, the worldwide web, another student, other textbooks, materials from another course (including prior versions of this course), or any other person or program. You may not copy, examine, or alter anyone else’s homework assignment or computer program, or use a computer program to transcribe or otherwise modify or copy anyone else’s files. It is not acceptable to look at exams or homework assignment solutions from prior quarters.
It is not acceptable to share your solutions or codes with your friends, or anyone else (other than the course staffs) without the permission of the instructors. You are not helping your friends by doing so. It is not acceptable to read other students’ solutions or code. You cannot share the course material (e.g., exams, homework assignments and solutions) with anyone else without the permission of instructors after you have completed the course.
Penalties may be assessed after you have completed the course, and some requirements of the collaboration policy (such as restrictions on you sharing your solutions and standard solutions) extend beyond your completion of the course.
The minimum penalty for cheating (including plagiarism from others or using ML tools such as chatGPT) will be a zero grade for the whole assignment; a typical penalty will be at minimum a -100% on the assignment - this will result in worse of a penalty than a 0 on the assigment and take away credit from other assignments. All violations of this collaboration policy will be reported to the university.