- Instructor: Lingming Zhang (lingming)
- TA: Yuxiang Wei (ywei40)
- Class Time: Tue/Thu 09:30 AM - 10:45 AM (Central Time)
- Location: 3025 Campus Instructional Facility
- Instructor Office Hours: Tue/Thu 10:45 AM - 11:45 AM (Central Time)
- TA Office Hours: Thu 3:00 PM - 5:00 PM (Central Time) | Zoom Link
- Communication: Campuswire (Use
netid@illinois.eduto join)
Important
Join the Campuswire forum before the first class as all notifications, assignments, and project submissions will be managed there.
Modern Large Language Models (LLMs) and agents have demonstrated remarkable capabilities across diverse fields, with software engineering as one of their most successful applications. This course dives deep into the intersection of LLM agents and software engineering, exploring how recent advances in generative AI can substantially transform the way people build and maintain software systems.
This is a research-driven course targeting students interested in research. Students must possess:
- Research background in PL/FM/SE or NLP/ML fields.
- Proficiency in Python programming.
- Completion of NLP/ML coursework.
- Solid background in algorithms and strong problem-solving skills.
For course restrictions, see: go.cs.illinois.edu/csregister
There is no required textbook. The course is discussion-based, and students are expected to read assigned papers before each class.
During class, students may be randomly selected to discuss the following aspects of a paper:
- Problem: What is the problem and why does it matter?
- Solution: What is the proposed solution and how does it differ from prior work?
- Evaluation: What benchmarks and metrics were used? Is it convincing?
- Results: What were the results and did they meet expectations?
- Critique: What are the strengths (pros) and limitations (cons)?
- Future Work: What are the potential next steps?
There is no exam. Grades are calculated based on the following:
| Component | Weight | Description |
|---|---|---|
| Homework Assignments | 20% | Released via Campuswire ("Assignments" page). No late submissions without prior approval/documentation. |
| Paper Presentation | 20% | Lead discussion for one paper. Select at least five classes you would like to present by Jan. 30th (submission link shown in Campuswire "Assignments"). Upload your initial slides to Campuswire a week before your presentation slot for comments, and upload the final version of the slides 48 hours before the lecture. Make it clear if you reuse any of the original slides from the authors. |
| Class Participation | 10% | This is a discussion-based course, so it does matter that you show up in our class meetings and participate in the discussion. |
| Course Project | 50% | The best way to learn software engineering is go there and do software engineering! You will undertake your own course project in a group (3-5 students). We will provide a list of directions (available on Campuswire) to get you started thinking, but I highly encourage you to pursue your own ideas. You are encouraged to use GitHub to host your development history and all the code/data. For the teams proposing your own ideas, you are required to meet with Lingming before Feb. 9th to discuss your proposal. |
- Proposal submission/presentation: 5%
- Midterm project report/presentation: 20%.
- Final project report/presentation: 25%.
| Grade | Percent | Grade | Percent |
|---|---|---|---|
| A | 93% | C+ | 77% |
| A- | 90% | C | 73% |
| B+ | 87% | C- | 70% |
| B | 83% | D+ | 67% |
| B- | 80% | D | 63% |
| F | <60% | D- | 60% |