SPRING 2026 Edition
This course is dedicated to the study of formal techniques for building reliable software systems, covering both classical software components as well as systems that incorporate machine learning models. The course begins by introducing the mathematical foundations for formally representing software as mathematical objects and for reducing verification problems to mathematical theorems. Building on this foundation, we introduce key abstractions, such as contract-based programming, that enable precise specification of software behavior and support modular, scalable, and reliable system development.
We will study a range of verification and bug-finding techniques applicable to both traditional software systems and more challenging settings, including concurrent, non-deterministic, probabilistic, and neuro-symbolic systems. The course will combine theory and practice: students will gain hands-on experience with tools that verify important system properties such as safety, correctness, and termination using abstraction-based techniques, model checking, and contract-driven development.
The lectures can be attended in person (DCL, Room 1310) and online on Zoom. Lectures will be held on Tuesdays and Thursdays, 12:30–1:45 PM. The lecture details will be communicated soon.
01/19/2026: Campuswire, course website link is sent by email.
01/19/2026: The website is up!
We will inform you about the grading policy at the beginning of the class and update here soon.
| Date | Topic | Slides / Video |
|---|---|---|
| 01/20 | Lecture 1. Course Introduction | Slides | Video |
| 01/22 | Lecture 2. Background | Slides | Video |
| 01/27 | Lecture 3. CFGs | Slides (same as 01/22) |
| Grade | A+ | A | A- | B+ | B | B- | C+ | C | C- | D | F |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Score | [95,100] | [90,94] | [85,89] | [80,84] | [75,79] | [70,74] | [65,69] | [60,64] | [55,59] | [50,54] | [0,49] |
In our commitment to academic excellence and ethical scholarship, we emphasize the importance of academic integrity in all aspects of our course. Academic integrity is central to the development of individual responsibility and scholarly credibility. Please be aware that the use of Large Language Model (LLM) tools, including ChatGPT, is strictly prohibited in the completion of any coursework and assignments in this class, unless explicitly specified otherwise. These tools, while valuable in certain contexts, do not align with our commitment to original thought and individual academic effort.
As part of this course, it is essential for all students to familiarize themselves with the University of Illinois at Urbana-Champaign Student Code, which is an integral component of our syllabus. Special attention should be paid to Article 1, Part 4, which focuses on Academic Integrity. You can access and review the Student Code at http://studentcode.illinois.edu/.