CS 180 Introduction to Software Engineering (Spring 2026)
- Instructor: Professor Qian Zhang
- Email:
- Office: WCH357
- Office Hours: By appointment
- Teaching Assistant: TBA
- Lecture and discussion sections: Please check the official UCR schedule and Canvas for finalized room/time information.
Course Description
CS 180 introduces core software engineering principles for building reliable, maintainable, and scalable software systems. The course covers requirements, design, implementation, testing, debugging, and project management, with practical experience in modern development workflows.
In Spring 2026, we are modernizing CS 180 around agentic software engineering. Students will learn how to effectively collaborate with coding agents in realistic software engineering workflows while maintaining software quality, reliability, and human oversight.
Spring 2026 Modernization Focus
- This offering is focused on agentic software engineering and AI-assisted development practices.
- We will teach students practical strategies to use coding agents effectively for planning, implementation, testing, and debugging.
- Hands-on activities will include coding-agent workflows using Google AI Studio and Google Vertex AI.
- We will open-source the course and lab materials so instructors and students can reuse and extend them.
Learning Goals
- Apply software lifecycle methods from requirements to maintenance.
- Design and implement team-based software projects with version control and code review.
- Use testing and debugging techniques to improve quality and reliability.
- Evaluate coding agent outputs and integrate them safely into engineering workflows.
- Use Google AI Studio and Google Vertex AI tools effectively in course projects and labs.
Grading: TBD
Tentative Weekly Topics
| Week | Topics | Milestones |
| 1-2 | Introduction, software processes, requirements engineering | Team formation, project proposal |
| 3-4 | Design modeling, architecture, design patterns | Design review |
| 5-6 | Implementation workflows, code quality, refactoring | Midpoint progress report |
| 7-8 | Testing strategies, debugging, CI basics | Testing milestone |
| 9-10 | Verification basics, release engineering, project demos | Final demo and final report |
Resources
- Canvas for announcements, assignments, and grade updates.
- Google AI Studio and Google Vertex AI will be used in selected labs and project activities.
- Open-source course and lab materials will be published for public access (link to be posted).
- Course handouts, slides, and project templates will be posted on Canvas.