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Course title

EECS 581 (3 credit hours): Software Engineering II — Fall 2026
Meets in person, Tuesdays, 4:00 pm - 5:50 pm, Eaton 2

Instructor

Professor Hossein Saiedian
Office: Eaton Hall 3012
☎ +1 785-864-8812
@ saiedian @ ku.edu
🌐 people.eecs.ku.edu/~saiedian
Teaching: people.eecs.ku.edu/~saiedian/Teaching
Office hours: Tuesdays and Thursdays, 1:00-2:30 PM (and by appointment)

Teaching assistants

Jawad Ahsan j.ahsan02 @ku.edu
Evans Chigweshe e462c110 @ku.edu
Nooreen Fatima noor16 @ku.edu
Xiaomin (Sherri) Rong xrong123 @ku.edu
Huy Tran huydinhtran @ku.edu

Course description

This lecture/laboratory course covers the systematic development of software products. Topics include: scope of software engineering, life-cycle models, software process, teams, ethics, tools, testing, planning, and estimating. It concentrates on requirements, analysis, design, implementation, and maintenance of software products.

Prerequisite: EECS 348, EECS 330, and upper-level EECS eligibility. Corequisite: EECS 565.

Course outcomes

1. Mastery of software engineering processes: Demonstrate proficiency in applying software engineering life-cycle models, including requirements analysis, design, implementation, testing, and maintenance, to develop robust and scalable software systems, incorporating database concepts such as relational schemas and SQL-based data management when appropriate.

2. Effective team collaboration and project management: Function effectively within a team of 5–6 members to plan, schedule, and execute a team-based software project, utilizing project management tools, version control systems (e.g., GitHub), and communication strategies to ensure successful delivery of project artifacts.

3. Proficiency in software requirements and modeling: Develop and document precise software requirements using formal modeling techniques (e.g., state modeling with Z, dynamic behavior modeling) and create software architectures that address quality attributes, ensuring traceability and alignment with project goals.

4. Software quality and testing competence: Apply modern software quality assurance practices, including test-driven development, static and dynamic testing (e.g., black-box and white-box testing), and capability maturity model integration, to ensure high-quality, reliable software products.

5. Ethical and social impact awareness: Analyze and articulate the local and global impacts of software systems on individuals, organizations, and society, applying ethical principles (e.g., ACM and IEEE codes of ethics) to design inclusive, accessible, and sustainable software solutions.

6. Lifelong learning and adaptation: Acquire and apply new knowledge as needed, using appropriate learning strategies to stay current with emerging software engineering trends, tools, and technologies.

Recommended textbooks

Below are several relevant textbooks that address topics covered in this course.
Software Engineering: A
	  Practitioner's Approach
Roger Pressman and Bruce Maxim, Software Engineering: A Practitioner's Approach, 9th edition, McGraw-Hill, 2020.

Table of Contents

Mathematical Foundations of Software
	  Engineering
Gerard O'Regan, Mathematical Foundations of Software Engineering, Springer, 2024.

Table of Contents

UML Distilled
Martin Fowler, UML Distilled: A Brief Guide to the Standard Object Modeling Language, Pearson, 2003.

Table of Contents

Evaluation (subject to revision)

Evaluation criteria. Students will be evaluated as follows:

🎯Term projects: 60%
✍ Assignments: 10%
📝 Exams: 30%

Term projects. Students will form teams of 5–6 to complete three collaborative software engineering projects using the Scrum agile methodology, with a Teaching Assistant serving as the Scrum Master. The first project involves developing a software from provided specifications, the second focuses on maintaining and enhancing another team’s project, and the third is an innovative, team-designed system integrating advanced technologies (e.g., cloud computing, a backend database, microservices, or secure database solutions). Teams may choose their programming language (e.g., Python, C, C++, C#, Go) and must use GitHub for version control and Canvas for submissions. Detailed requirements, sprint expectations, and rubrics will be available on Canvas, emphasizing technical quality, process adherence, and ethical considerations aligned with ACM and IEEE codes of ethics.

Term Project 1: The Minesweeper Game (20%). A foundational project involving the development of the Minesweeper game. This phase assesses your ability to apply core EECS348 course concepts

Term Project 2: Peer Code Enhancement (10%). This project focuses on developing a crucial professional skill: understanding and maintaining existing codebases. Your team will be tasked with adding features to another team's Minesweeper project, providing practical experience in working with and enhancing code written by others.

Term Project 3: Team-Generated Application (30%). A culminating Agile project where teams will conceptualize, design, and develop a novel application from scratch. This part of the project evaluates creativity, teamwork, and mastery of advanced course material.

Everything you need to know about the term projects, including requirements for each, required artifacts, grading rubrics, and due dates, is available on the course’s official Canvas page.

Assignments. Assignments may take a variety of forms, including labs, homework exercises, in‑class activities, or mini‑projects. Students are expected to complete assigned work both inside and outside the classroom as appropriate for the course. In courses that include hands‑on laboratory components (such as software engineering course), certain lab activities must be completed during scheduled lab sessions under TA supervision to ensure academic integrity; work completed outside the lab in these cases will not receive credit. Full assignment descriptions, requirements, and due dates are provided on Canvas.

Exams and quizzes. Exams and quizzes will be conducted in person and administered through Canvas. All exams and quizzes are closed-book and closed-notes.

Students must bring a laptop or tablet with a sufficiently large screen capable of accessing Canvas. During an exam or quiz, the only permitted application is the Canvas app or a web browser with a single tab open to Canvas. All other applications, files, browser tabs, windows, and electronic resources must be closed before the assessment begins and may not be accessed during the assessment.

To maintain academic integrity, students must remain focused on the exam window for the entire assessment. Canvas records instances of "Stopped viewing the quiz-taking page", and such instances may be reviewed and investigated as potential academic integrity violations.

Only devices and applications explicitly required for taking the assessment are permitted. Smartphones, smartwatches, earbuds, headphones, Bluetooth devices other than a mouse or stylus, remote-access software, screen-sharing software, generative AI tools, and similar technologies are prohibited unless expressly authorized by the instructor. Because these technologies can facilitate communication, information access, or other unauthorized assistance, their use is not permitted during exams or quizzes.

Screen brightness must remain at a normal, visible level throughout the assessment. The use of display dimmers, screen-darkening software, privacy overlays, or any method intended to obscure screen contents is not permitted.

Violations of the above testing requirements may be treated as violations of the University's academic integrity policy and may result in disciplinary action.

  • Structuring responses for exams, quizzes, and lab assignments. For questions with multiple parts (e.g., “name three parts of…”), address each part separately to ensure clarity and avoid confusion. Use clear identifiers such as “(1)”, “(2)”, and “(3)” to organize your answers. If more than the requested number of parts are provided, only the first three will be graded. Structured, precise responses demonstrate your understanding effectively.
  • Demonstrating engagement in exams, quizzes, and lab assignments. Responses should reflect your understanding of concepts as presented and discussed in class. Credit will be awarded for answers that demonstrate familiarity with course lectures, discussions, examples, and assigned materials, rather than reliance on external sources.
  • Providing technical and detailed responses. Exams, quizzes, and lab assignments require precise, technically accurate, and comprehensive answers. Vague, incomplete, or off-topic responses will not earn full credit, even if partially correct. To maximize points, provide detailed explanations supported by specific examples and relevant course concepts. Demonstrate a clear understanding through well-crafted, focused responses.

Submission format policy. All course work—including assignments, reports, and projects—must be typeset and submitted electronically via Canvas. Please note that “typeset” refers to work composed using digital tools (e.g., word processors, , image editing software, etc.). Handwritten or hand-drawn submissions will not be accepted.

Course lectures and resources

Students are responsible for engaging with all course materials, including lecture slides, topics covered in class discussions, assigned readings, and supplementary resources (e.g., handouts, code samples, or project guidelines) distributed during class sessions. All materials will be posted on Canvas, and students are expected to regularly check Canvas for updates to ensure they remain informed and prepared. Active engagement with these resources is critical for success in assignments, projects, and exams, and aligns with the course’s emphasis on professional responsibility and self-directed learning.

Course announcements (Canvas)
Lecture slides (Canvas)
Readings (Canvas)
Project resources (Canvas)

Guest speakers

Throughout the semester, we may host guest speakers who bring valuable insights and real-world perspectives related to the course material. Attendance during these sessions is especially important, as guest speakers may not provide lecture slides or written materials. Students are expected to take careful notes and engage respectfully. These sessions may include content relevant to assignments or exams.

Grading philosophy and scale

This course is not curved in the traditional sense. I do not set a fixed class average (e.g., a "B") and scale grades to fit a predetermined distribution. Instead, I ask one fundamental question: “Has this student mastered the material?”

If every student demonstrates clear mastery of the course content, then every student earns an A. Grades are not a measure of relative ranking—they are a reflection of your personal understanding and engagement with the work.

I encourage you to shift your focus away from grade anxiety. Instead, concentrate on being present, asking questions, exploring ideas, and participating fully in the learning process. In return, I promise to be fair, transparent, and extra supportive. We are in this together, and I want each of you to succeed—not just by earning a grade, but by growing as scholars and professionals.

I am genuinely invested in your progress, and nothing would make me happier than seeing every student earn an A through honest work and intellectual curiosity.

The above said, final course grades will be determined by the total percentage of points earned. The following standard scale will be used:

  • A (Excellent): 90–100%
  • B (Good): 80–89%
  • C (Satisfactory): 70–79%
  • D (Poor): 60–69%
  • F (Failing): Below 60%

Tentative weekly schedule (re-visit for updates)

Foundations: The human side of software engineering

➡️ Course syllabus and course overview
  -- Description of the term projects
  -- Striving for successful teams
  -- Team assignments
  -- Scrum / Agile basics

Please watch: Intro to Scrum (7 minutes)
Please watch: Scrum under 10 minutes

In this initial phase, students should meet with their teammates to get acquainted and discuss each other's backgrounds, skills, and working styles. Teams should also openly discuss and tentatively assign roles—such as project manager—based on individual strengths and interests. The goal is to build rapport and begin identifying how each member might contribute to the project.

➡️ AI in software engineering
➡️ Ethics in software engineering
  -- General ethics, AI ethics
  -- ACM and IEEE codes of ethics
➡️ Software project management
  -- Project planning
  -- Introduction to effort and cost estimation

➡️ Software project management (continued)
  -- Effort and cost estimation: story points, use case points, parametric models
  -- Risk management
  -- Team communication and pair-programming in Agile

Exam 1 (primarily on ethics, AI in SE, project management)

Freeze code on the master branch of your team's GitHub repository. Prepare to demonstrate your project's core features, functionality, and user experience to your Scrum Master—highlighting how it meets requirements, solves the intended problem, and reflects team collaboration.
Software architecture and system design

➡️ New: Guest lectures on AI in software engineering and professionalism in communication
➡️ Software architecture fundamentals
  -- Components, connectors, rationale
➡️ Architecture quality attributes
  -- Understanding quality attributes

➡️ Architecture quality attributes (continued)
  -- Achieving quality attributes
➡️ Architectural styles, patterns, and tactics
  -- Software product lines (brief overview, within architecture context)

➡️ Service-oriented architecture
  -- Service contracts, operations, service composition
  -- Service registry, service customers

Demonstrate the enhancements your team made to the original Minesweeper project, highlighting added functionality and/or improved usability. The objective is to assess whether your team successfully understood the code developed by another team and enhanced it with meaningful new features.
Fall break (first part of week)

Initial Requirements Stack & Story Point Estimate. Submit a prioritized list of initial features and user stories for your application, along with estimated story points to guide sprint planning.

➡️ Microservices architecture
  -- Deployment and scalability
➡️ Containerization and orchestration

Initial Architecture & Sprint 1 Requirements List. Provide a high-level overview of your system architecture and a detailed list of user stories selected for Sprint 1 implementation.

➡️ Why software quality matters

Exam 2 (primarily software architecture and system design)

Software quality and formalism in software engineering

➡️ Software quality assurance
  -- Modern software quality management
  -- Software process improvement (CMMI)
  -- Test-driven development
  -- Static testing (inspection, formal reviews, proof of correctness)

Sprint 1 Release & Sprint 2 Requirements List. Deliver the first working release of your application and submit the updated list of user stories planned for Sprint 2.

➡️ White-box testing
  -- Dataflow testing examples

➡️ What makes software engineering "engineering"; formalism in SE
➡️ State transition (dynamic behavior) modeling

Required reading (external; not on Canvas): Chris Newcombe, et al., How Amazon Web Services uses formal methods, Communications of the ACM, 58(4), April 2015.

Sprint 2 Release & Sprint 3 Requirements List. Release Sprint 2 features and submit the next set of prioritized user stories for Sprint 3 development.

➡️ State transition modeling (continued)
➡️ Model checking
➡️ Brief introduction to Z (overview only)

Required reading (external; not on Canvas): Marc Brooker and Ankush Desai, Leveraging formal and semi-formal methods: systems correctness practices at Amazon Web Services, Communications of the ACM, 68(6), June 2025.

Sprint 3 Release & Final Sprint Requirements List. Submit the Sprint 3 release and outline the final set of features and refinements planned for the last sprint.

November 25–27: Thanksgiving break (no impact on Tuesday class schedule)

➡️ History of computing and software engineering: Turing to Agile
➡️ Societal impact of software engineering
➡️ Sustainable development practices, inclusive and accessible design, and intellectual property in software engineering

➡️ Architecting the future of software engineering
➡️ Course review

Final Sprint Release & Presentation (in person or video). Deliver the final version of your application and present your project—highlighting key features, design decisions, and team collaboration.

Final exam @ 1:30–4:00pm (primarily on SQA, formal modeling in software engineering, history)

Course policies
:

Classroom engagement via

iClicker is an interactive classroom response system that allows students to engage actively by answering questions and participating in polls. The University of Kansas has secured an iClicker subscription for classroom use, and the EECS department is incorporating this system into its courses to boost student engagement. Participation in the iClicker community is mandatory for this course.

When an iClicker notification is sent, students are briefly polled to confirm receipt. If a student encounters a technical issue or need more time, they should raise their hand to be acknowledged and if the issue is not resolved, meet with the instructor immediately after class to manually adjust the iClicker record.

Responding to iClicker notifications when not physically present in the classroom is strictly prohibited. It constitutes a deliberate act of academic dishonesty and a direct violation of the University of Kansas code of conduct. Logging attendance or submitting responses while absent undermines the integrity of our learning environment and disrespects both the instructor and fellow students who are fully participating. Violations will be treated as academic misconduct and reported accordingly.

LLM and generative AI tools

Generative AI tools, such as ChatGPT, GitHub Copilot, Gemini, and others, can be valuable resources for learning. When used appropriately, they may assist in brainstorming, exploring ideas, and refining drafts. However, they must never replace your own intellectual work.

These tools are akin to the writing center consultants, the EECS programming tutors, and lab assistants: they can guide and support but must not generate final submissions. Submitting content primarily generated by AI is a violation of academic integrity, comparable to submitting work completed by someone else.

Unless explicitly permitted, all coursework must reflect your original understanding, reasoning, and expression. Use of generative AI tools is not permitted for any assignment unless the instructor explicitly authorizes it for that specific assignment; where such use is authorized, it must be disclosed via a brief reflection describing how and why the tool was used, the specific prompts entered, how the output was validated and revised, and any challenges or limitations encountered.

  • A description of how and why AI was used
  • The specific prompts you entered
  • How you validated and revised the AI output
  • The challenges or limitations you faced while using AI

Failure to disclose use of AI tools or submitting AI-generated work as your own will be treated as academic misconduct. Minimum consequences include a zero on the assignment. Depending on severity, further penalties may include failure in the course and formal referral to the School of Engineering disciplinary committee.

This course is designed to build your skills—not evaluate the performance of generative tools. Authentic engagement with course challenges leads to meaningful growth. Overreliance on AI undermines both your learning and the integrity of our academic community.

Intellectual honesty is not optional; it defines your identity as an engineer, a scholar, and a professional.

Academic integrity policy

The University of Kansas, the School of Engineering, and the Department of Electrical Engineering & Computer Science (EECS) maintain a zero-tolerance policy toward academic dishonesty and misconduct. All students enrolled in this course are expected to uphold the highest standards of integrity and professionalism in their academic work.

Academic dishonesty includes, but is not limited to:

  • Plagiarism and unauthorized collaboration: Representing another person’s work, ideas, or writing as your own without proper attribution, or giving/receiving unapproved help on assignments, projects, quizzes, or exams.
  • Cheating: Using unauthorized resources or materials during assessments, or submitting work completed by someone else.
  • Misrepresentation and falsification: Knowingly presenting false information, fabricating or manipulating data/research results, or falsely representing your presence, participation, or attendance in a course activity.

The minimum consequence for an academic integrity violation is a zero on the item in question (e.g., lab, assignment, quiz, or exam). Depending on severity, penalties may include a grade reduction, a failing grade for the course, and formal referral to the School of Engineering's disciplinary committee for further review and sanctions.

Please also see KU's academic misconduct policy

LMS features. During exams or quizzes, only one device should be used, with solely the Canvas app or a single browser tab for Canvas open. Having any other tab, app or file open will be considered a violation of academic integrity. To further facilitate academic integrity, the following features of Canvas will be utilized:

  • The "originality checking" mechanisms of LMS will be utilized for exams but also assignments.
  • LMS features to prohibit printing, copying/pasting of exams will be turned on.
  • LMS lockdown feature will be employed.

Code of student rights and responsibility: Code of Student Rights and Responsibilities

Attendance, late work, and makeup policies

Attendance expectation. Regular attendance is essential for success in this course. Attendance will be recorded throughout the semester via iClicker for classroom meetings (and, if the course includes a lab component, via a sign-up attendance sheet for lab sessions). More than three unexcused absences (in classrooms or labs) will result in a one‑letter reduction in the final course grade, which will be applied when grades are posted at the end of the term.

Course-specific attendance policy (EECS 581). Because this course meets once per week, a single absence carries the weight of two regular sessions. Accordingly, no more than two unexcused absences will be permitted (equivalent to four regular sessions under the standard format); a third unexcused absence will result in the one-letter grade reduction described above. This applies to the Tuesday classroom sessions; TA/Scrum-meeting participation is assessed separately, using the project rubric posted on Canvas.

Late-work, makeup policy. Late work and make‑up opportunities for labs, quizzes, and exams are available exclusively for students with excused, documented, and approved absences, ensuring full support for those with qualifying circumstances.

Excused absence requests. Requests for excused absences must be submitted in advance and approved by the instructor, except in cases of emergency. Supporting documentation must accompany all requests. For emergencies, notify the instructor as soon as possible following the absence. Examples of excusable absences include:

  • Illness or injury
  • Verifiable personal mental health or medical crisis, or that of a relative
  • Unforeseen life event or compelling circumstances beyond the student's control (e.g., divorce, birth or adoption of a child, death, loss of employment, sexual assault, domestic violence)
  • Academic field trips or conferences
  • Participation in university activities at the request of university authorities (e.g., an approved concert or athletic event)
  • Jury duty or officially mandated court appearances

If a student experiences a confidential personal or family situation that does not fall under the above categories, they may consult CAPS or their academic advisor, who can then contact me on their behalf.

Make-up policy and integrity. For excused absences, quizzes and exams must be made up before the content is reviewed or the answer key is released. Labs, assignments, or homework are due within one week of the absence. Additional flexibility will be provided for special circumstances.

By taking a make-up assessment, you affirm that you have an excused absence and have not sought or received any information about its content from prior test-takers. Violating this pledge is academic misconduct (see above).

Responsibility for missed work. Students who miss class are responsible for obtaining any missed materials.

Common policies

Classroom conduct policy: Students are expected to arrive on time, remain attentive, and conduct themselves professionally. Please avoid behaviors that disrupt the learning environment or instructor presentations, and note that profanity is strictly prohibited. Additionally, students are encouraged to actively engage during class sessions by asking questions, contributing to discussions, and providing feedback.

Canvas announcements. Important course updates will be posted via Canvas Announcements. You are responsible for checking Canvas regularly; email notifications may also be sent depending on your account settings.

Email communications
As an engineering student at the University of Kansas, all written communications should reflect professional standards. Please note:

  • Subject lines: Must be descriptive and begin with EECS### for course-related messages.
  • Etiquette: Please follow standard professional email etiquette.
  • Format: Send text-only emails in text-only format. All classroom assignments, labs, or projects should be typeset and submitted on Canvas.
  • Attachments: Other documents (e.g., documents for an excusable absence) should be emailed in PDF or a well-known image format (e.g., JPG or PNG). Please choose a descriptive file name for the attachment (avoid file names like "image", "my document", etc.).

Grade and absence clarification or correction. We want to ensure your records are accurate and fair. If you believe a grade on an assignment, lab, quiz, or exam is incorrect, you must submit an grade correction request within one week of receiving the graded work. Similarly, if you need to submit documentation for an excused absence after the fact, you must do so within one week of the absence. Failure to address these matters within this one-week timeframe will result in the decision becoming final, ensuring timely resolution and consistency for the entire class.

Typographical errors. Any typographical errors on exams or other course materials, including those introduced by Canvas, will be resolved in favor of the students.

Technical problems. Submit a support request help at: https://tsc.ku.edu/request-support-engineering-tsc.

Electronic device policy: Cell phones must be silenced before entering the classroom. While laptops, tablets, and phones are welcome for note-taking and approved tools like iClicker, non-academic uses (such as social media or web surfing) must be avoided to prevent distractions. Audio should remain turned off. Additionally, devices may be used to photograph whiteboard notes or projects, provided the shots exclude the instructor and other students.

Incomplete grade policy. An Incomplete ("I") grade is reserved for exceptional circumstances beyond your control and must be resolved within the instructor's timeframe (up to one year before automatically converting to an "F" or "U"). For full details please review KU policies: here and here.

Accommodations for students with disabilities. The University of Kansas is committed to equal opportunity and accessible learning. Requests for special accommodations should be made through KU Student Access Services.

Nondiscrimination and equal opportunity. KU strictly prohibits discrimination based on protected characteristics across all programs and activities. For full institutional policies, please review KU's statements on nondiscrimination and the racial and ethnic harassment policy.

Sexual harassment. KU prohibits sexual harassment and is committed to preventing, correcting, and disciplining unlawful harassment and assault. Please review KU's statement on sexual harassment for details.

Mandatory reporter statement. As a faculty member and KU employee, I am a mandatory reporter required to share disclosures of discrimination, harassment, or sexual violence with the Office of Civil Rights and Title IX. For confidential support options (such as CAPS, Watkins Health Care, or the Ombuds Office), please review KU's statement on mandatory reporting.

Commercial note-taking ventures. Pursuant to KU's commercial note-taking policy, selling lecture notes or course materials for commercial gain is strictly prohibited and subject to disciplinary action. Note-taking provided as an official ADA accommodation for a student with a disability is exempt.

Concealed handguns. Individuals choosing to carry concealed handguns must do so safely and in strict compliance with state/federal laws and KU weapons policy, which requires that handguns remain under constant control, fully concealed, holstered with the trigger covered, and carried with the safety on and no round in the chamber.

The School of Engineering statement on EdTech

Professors and instructors at the KU School of Engineering are aware that students sometimes post or access course assignments, labs, and exam questions on EdTech platforms (such as Chegg).

Please note that agreeing to an EdTech service's "terms of service" does not protect you if an academic misconduct investigation is initiated. Platforms like Chegg retain and release traceable user data upon request.

Using these services constitutes academic misconduct, violates the School of Engineering Rules & Regulations, and can lead to a failing grade in the course, a transcript citation, and expulsion from the University of Kansas. Instead, please utilize authorized resources such as instructor office hours, TAs, and tutoring.

Ethical foundations for technical professionals

As computing and engineering professionals, you are expected to know and apply the professional codes of ethics throughout your academic and professional careers:

As the ACM preamble notes: "Computing professionals' actions change the world. To act responsibly, they should reflect upon the wider impacts of their work, consistently supporting the public good."