(1) Course Prefix and Number: CS 580B3
(2) Course Title: Artificial Intelligence for Software Engineering
(3) Catalog Description: This course is designed as a graduate-level Artificial Intelligence for Software Engineering (AI4SE). The objective is to provide students with a comprehensive overview of AI applied to software engineering (SE), equipping them with a fundamental understanding of the challenges involved in adopting state-of-the-art AI techniques to the SE life cycle, improving or redesigning the way SE is employed. Key methodologies currently used to address these challenges will be explored, setting the foundation for AI4SE studies.
While advanced mathematical proficiency is not expected, the course will provide opportunities to develop and apply fundamental mathematical and computational skills crucial to AI. We expect basic knowledge of AI and SE domains.
The curriculum will encompass various subareas of AI4SE, including requirements, testing and code quality. To ensure a comprehensive understanding of the AI4SE’s state of the art, materials will be provided for topics based on recently published articles.
(4) Prerequisite courses for undergraduates: (CS314 with a C or better) AND (STAT 301 with a C or better or STAT 315 with a C or better) AND (CS345 with a C or better)
(5) Co-requisites: N/A
(6) Credit Hours: 4
(7) Semester: Spring 2026
(8) Class Meeting Time(s), location and format:
Time: T-TH 2:00-3:15
Location: Eddy 118 / Online (Echo 360)
Format: In-Person/Online
(9) Instructor: Dr. Fabio Santos
(10) Contact Information:
- Dr Santos.
Office hours: T-TH, 10:00 AM – 11:00 AM
Location: Office (CS Building office 458)/Teams
- TA – Satya Kadiyala
Office Hours: T 1:00 PM – 2:00 PM / TH 9 AM – 10 AM
Location: CSB 120 / Microsoft Teams
(11) Concerns: Questions, comments, or requests regarding this course should be taken to the instructor.
(12) Course Learning Outcomes:
By the end of this course, students will be able to:
CLO 1 – Mine software repositories.
CLO 2 – Describe the role of AI in supporting SE domains.
CLO 3 – Build AI solutions for software maintenance activities.
CLO 4 – Leverage AI to enhance the collaboration and productivity of software engineering teams.
CLO 5 – Improve code quality by using AI and MLOps.
CLO 6 – Automate code and documentation generation with LLMs.
CLO 7 – Implement AI-driven testing automation.
(13) Course-specific Required Materials:
Recent or relevant articles published
(14) Course Content:
Topics to be covered
Note: The instructor reserves the right to modify the class schedule and the time spent on each topic/chapter. Further, the course content is tentative and is covered as time permits.
Syllabus is subject to change as long it is informed to the class.
Date Created: 01/06/2026
Updates to Syllabus:
NA
(15) Grading Scale and Policies:
Undergraduate students:
Assessment
Activity Percentage
Assignments 40%
1 Project 30%
1 Article 30%
Total 100%
Grading Scale:
Point range Letter grade
above 90 A
86-89 B+
82-85 B
78-81 B-
74-77 C+
70-73 C
60-70 D
below 60 F
1: Assignments mean, including but not limited to, presentations, discussions, exercises, quizzes, short essays, homework, labs. Students should accomplish assignments in the assigned time slots.
Late assignments:
Presentations/Project and Article: No late submissions will be accepted, as a discussion follows the presentation and delivery.
Other assignments: 1 week after the due date, assignments will be penalized with 10% a day. Electronic submission is closed 1 week after assignments are due; students who have not submitted programs receive an automatic zero on the assignment.
“Emergencies” require that YOU contact the instructor ASAP. Students’ requests for late submissions after the due time may not be granted. If an extraordinary medical or appropriate personal circumstance prevents you from attending courses or taking the midterm or final exam, please contact the instructor as soon as possible.
(16) Additional Course Information
Students are expected to attend class. Absence from class hampers your ability to learn the course material. This, in turn, adversely affects the instructor and your classmates. Please inform the instructor of any absences via Discord as early as possible.
Students should expect a response to messages within 48 hours during business days.
(17) Academic Support and Student Success– CSU has many resources available to support students. Check the web page below for details: https://catalog.colostate.edu/general-catalog/academic-services-support/services-programs/
(18) Academic Honesty – We expect all students, faculty, and staff to operate honestly and ethically. Academic dishonesty is a severe offense because it undermines the value of your education and the education of others. Students who engage in academic dishonesty face significant penalties. Forms of academic dishonesty include but are not limited to, plagiarism, cheating, contract cheating, misrepresentation, and other actions you take. Some of these are defined below:
● Plagiarism means passing off someone else’s work as your own, intentional or unintentional.
● Cheating includes copying from another person or source of information to meet the requirements of a task.
● Contract cheating is paying someone else or a company to do your work.
● Misrepresentation means you are posing as someone else or someone else is posing as you to complete a task.
● Collusion means working with one or more people to cheat. You will face the same penalties if you help someone cheat or plagiarize.
Use of AI: AI is allowed to prepare code assignments, except when explicitly mentioned in assignments. Students must report AI usage.
For more information, visit the Student Resolution – Student Conduct Code. https://resolutioncenter.colostate.edu/conduct/code/
(19) Accessibility – Colorado State University is committed to making our campus accessible. See more at: https://www.colostate.edu/accessibility-statement/
(20) Mandatory Reporting – Colorado State University is committed to intervening in, preventing and eliminating sexual misconduct, gender discrimination, and gender-based violence within the CSU community. For more information visit: https://titleix.colostate.edu/
(21) Academic calendar: https://catalog.colostate.edu/general-catalog/calendar/calendar.pdf
(22) Schedule (subject to change):
Week Topic Lab/Recitation
Week 1 – Jan 20, 22 – Course introduction, open source software (OSS) communities and their importance for software engineering research, Introduction to AI4SE, OSS, Contribution cycle of life, version control systems.
Week 2-3 – Jan 27, 29, and Feb 03, 05 – AI methods for architecting software projects, group formation, study of papers, and gap identification.
APIs for mining software repositories (MSR), Token creation, APIs.
Introduction to LLMs: prompt engineering, fine-tuning, and RAG fundamentals.
Week 4 – Feb 10, 12 – Datasets for AI4SE. Paper Introduction.
Week 5 – Feb 17, 19 – AI for Requirements. Paper Related Work.
Week 6 – Feb 24, 26 – AI for Onboarding contributors to OSS projects. Paper Method 1.
Week 7 – Mar 03, 05 – Knowledge modeling and Reasoning applied to AI4SE. Paper Method 2.
Week 8 – Mar 10, 12 – AI 4 documentation. Paper Preliminary Results.
Week 9 – Mar 17, 19 – Spring Break.
Week 9 – Mar 24, 26 – Bug Localization. Paper Results.
Week 10 – Mar 31, Apr 02 – Automatic Program Repair. Paper Discussion.
Week 11 – Apr 07, 09 – Lab MSR. Paper Limitations.
Week 12 – Apr 14, 16 – Lab LLM. Paper Future Work. Conclusion.
Week 13 – Apr 21, 23 – AI 4 Code review, AI 4 Test – Work on final project, Research methods for SE.
Week 14 – Apr 28, 30 – Work on final project, project wrap-up, and presentations
Week 15 – May 05, 07 – Work on final project, project wrap-up, and presentations
Week 16 – May 12, 14 Final Exam.
(23) The linked page provides policies relevant to their courses and resources to help with various challenges they may encounter. https://col.st/2FA2g including, Canvas Information and Technical Support, Universal Design for Learning/Accommodation of Needs, Undocumented Student Support, Food Insecurity, Title IX/Interpersonal Violence, Religious Observances, CSU Principles of Community, Diversity and Inclusion, Student Parents/Guardians/Caregivers, Student Case Management, Mental Health and Wellness.
