Recommended textbooks

The following are two of the most popular database systems textbooks:

	A. Elmasri, H. Navathe, Fundamentals of Database Systems, 7th edition, Pearson, 2016 The textbook's table of contents. This button shows which chapters from this book cover a given topic. For example, if a topic is covered in Chapter 1, it will appear as: Ch1.
	A. Silberschatz, H. Korth, S. Sudarshan Database System Concepts, 7th edition McGraw-Hill, 2020 The textbook's table of contents. This button shows which chapters from this book cover a given topic. For example, if a topic is covered in Chapter 1, it will appear as: Ch1.

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%

Term Project Part 0 Team formation and role alignment

Term Project Part 1 Vision statement and project plan

For Part 1 of the term project, each team must produce a well-defined vision and scope statement that outlines the project’s motivation, intended platform, anticipated user base, preliminary interface ideas, and team structure. This document should clearly articulate the system’s purpose and overall direction, including each team member’s tentative roles, relevant skills, and contact information. A full description of this portion of the project, including the rubric, due date, and submission guidelines, is available on Canvas.

Term Project Part 2 Project requirements

For Part 2 of the term project, your team is expected to produce a requirements document that clearly defines the goals and functionalities of your proposed database system. This should include a concise description of the system’s primary objectives, a breakdown of essential features and capabilities, and a list of key stakeholders who will interact with or benefit from the database. A full description of this portion of the project, including the rubric, due date, and submission guidelines, is available on Canvas.

Term Project Part 3 Project conceptual model

Term Project Part 4 Logical relational model

Term Project Part 5 Physical design and data population

⚠️ This is the largest and most time-intensive part of the term project. It is not due until Week 15, but teams are strongly encouraged to begin work now.

For Part 5 of the term project, your team must implement a physical database derived from your logical design. This includes creating all necessary tables, constraints, and relationships using appropriate SQL syntax, and populating the database with meaningful and realistic sample data that reflects your project’s use cases. The completed database must undergo rigorous testing to ensure it meets all specified functional (and non-functional) requirements outlined in your original proposal. A detailed description of this part of the project, including the rubric, due date, and additional guidelines is available on Canvas.

Term Project Part 6 Project demonstrations

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:

• ACM Code of Ethics and Professional Conduct
• IEEE Code of Ethics

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."