Syllabus¶
Course: Software Engineering Economics Instructor: Dr. Zhijiang Chen Term: Summer 2026 — Weeks 14–16 Daily Time Slot: 16:20 – 18:10
Course Description¶
Software Engineering Economics is the application of economic principles and decision-analysis techniques to the engineering of software systems. This course follows the classical framework established by Barry W. Boehm and extends it to address contemporary challenges, including the economics of AI-assisted development. Students learn to estimate cost, evaluate alternatives, manage risk, and communicate the economic case for software investments.
Learning Outcomes¶
Upon successful completion of this course, students will be able to:
- Apply the time value of money to discrete and continuous cash flows.
- Compare alternatives using NPV, IRR, payback period, and profitability index.
- Perform break-even, sensitivity, and risk analyses (including decision trees).
- Estimate software size and effort using Function Points and COCOMO II.
- Analyze quality, maintenance, and technical-debt economics.
- Apply Value-Based Software Engineering to build/buy/reuse decisions.
- Reason about the cost structure and ROI of AI-assisted software work.
- Produce a complete economic analysis of a software project and defend it before peers.
Schedule¶
Week 14 — Foundations (June 3 – June 7, 2026)¶
| # | Date | Day | Room | Topic |
|---|---|---|---|---|
| 1 | 2026-06-03 | Wed | YF302 | Introduction to Software Engineering Economics |
| 2 | 2026-06-04 | Thu | YF302 | Software Cost Concepts & Lifecycle Cost |
| 3 | 2026-06-05 | Fri | SY109 | Time Value of Money |
| 4 | 2026-06-06 | Sat | SY109 | Cash Flow Analysis & Equivalence |
| 5 | 2026-06-07 | Sun | SY109 | Investment Decisions & Alternative Selection |
Week 15 — Decision Methods, Estimation & Strategic Decisions (June 8 – June 14, 2026)¶
| # | Date | Day | Room | Topic |
|---|---|---|---|---|
| 6 | 2026-06-08 | Mon | YF108 | Break-even & Sensitivity Analysis |
| 7 | 2026-06-09 | Tue | YF108 | Risk & Decision under Uncertainty |
| 8 | 2026-06-10 | Wed | YF302 | Cost Estimation I: Size Metrics & Function Points |
| 9 | 2026-06-11 | Thu | YF302 | Cost Estimation II: COCOMO II |
| 10 | 2026-06-12 | Fri | SY109 | Quality & Maintenance Economics |
| 11 | 2026-06-13 | Sat | SY109 | Build / Buy / Reuse & VBSE |
| 12 | 2026-06-14 | Sun | SY109 | AI Topic I — Estimation & Productivity Disruption |
Week 16 — AI Economics, Presentations & Final Exam (June 15 – June 18, 2026)¶
| # | Date | Day | Room | Topic |
|---|---|---|---|---|
| 13 | 2026-06-15 | Mon | YF108 | AI Topic II — Token Economics & Project ROI |
| 14 | 2026-06-16 | Tue | YF108 | Student Presentations — Part 1 |
| 15 | 2026-06-17 | Wed | YF302 | Student Presentations — Part 2 |
| 16 | 2026-06-18 | Thu | YF302 | Final Exam |
Assessment¶
| Component | Weight | Description |
|---|---|---|
| Participation & in-class quizzes | 15% | Short quizzes at the start of most sessions; in-class participation. |
| Homework assignments | 25% | ~6 problem sets covering core methods. |
| Group project & presentation | 30% | Complete economic analysis of a chosen software project. Presented in Lectures 14–15. |
| Final exam | 30% | Closed-book, comprehensive exam in Lecture 16. |
Group Project¶
Teams of 3–4 students choose a software project (real or hypothetical) and produce:
- A cost estimate (Function Points or COCOMO II).
- A cash-flow forecast.
- NPV, IRR, payback, and PI for at least two alternatives.
- A sensitivity or risk analysis.
- (Bonus) An AI-cost dimension (token / API spend, productivity impact).
Project briefs are released in Lecture 8 (2026-06-10); presentations occur in Lectures 14 and 15.
Grading Scale¶
A: 90+ · B: 80–89 · C: 70–79 · D: 60–69 · F: below 60
Course Policies¶
- Attendance. Regular attendance is expected. Three or more unexcused absences may lower the final grade.
- Late work. Homework submitted late loses 10% per day (max 3 days).
- Academic integrity. All work must be original. AI tools may be used as study aids and for project research, but the analysis and conclusions must be your own. Disclose AI use in your project report.
- Accommodations. Students requiring accommodations should contact the Office of Disability Support Services.
Required & Recommended Reading¶
- Boehm, B. W. (1981). Software Engineering Economics. Prentice Hall.
- Boehm, B. W., et al. (2000). Software Cost Estimation with COCOMO II. Prentice Hall.
- Park, C. S. Contemporary Engineering Economics (any recent edition) — for foundational engineering-economics methods.
- Selected articles on Value-Based SE and AI economics (linked in each lecture).