EECS448: Software Engineering -- Fall 2022 (10794)
Tuesdays and Thursdays, 2:30 pm - 3:45 pm, Eaton 2
Teaching website: people.eecs.ku.edu/~saiedian/Teaching
M 01:00 - 02:50 PM EATN 1005C
Tu 09:00 - 10:50 AM EATN 1005C
W 09:00 - 10:50 AM EATN 1005C
W 02:00 - 03:50 PM EATN 1005A
Th 09:00 - 10:50 AM EATN 1005C
Th 12:00 - 01:50 PM EATN 1005A
F 02:00 - 03:50 PM EATN 1005C
Professor Hossein Saiedian
Office: Eaton Hall 3012
Telephone: 785-864-8812
E-Mail: saiedian AT ku.edu
WWW: people.eecs.ku.edu/~saiedian
Office Hours: Tuesdays and Thursdays, 1:00-2:00 PM (and by appointment)
Arnab Mukherjee (arnabmukherjee91 AT ku.edu)
Anjali Pare (anjali.pare AT ku.edu)
Liangqin Ren (liangqinren AT ku.edu)
This course is an introduction to software engineering, and it covers the systematic development of software products. It outlines the scope of software engineering, including life-cycle models, software process, teams, tools, testing, planning, and estimating. It concentrates on requirements, analysis, design, implementation, and maintenance of software products. The laboratory covers CASE tools, configuration control tools, UML diagrams, integrated development environments, and project specific components. Prerequisite: EECS 268 and upper-level EECS eligibility.
The course outcomes are as follows:
The first textbook is a required textbook and other textbooks are excellent references.
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Ian Sommerville Engineering Software Products: An Introduction to Modern Software Engineering, Pearson, 2020. |
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Martin Fowler UML Distilled: A Brief Guide to the Standard Object Modeling Language 3rd edition, Pearson, 2004. |
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Roger Pressman and Bruce Maxim Software Engineering: A Practitioner's Approach 9th edition, McGraw-Hill, 2020. |
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Ian Sommerville Software Engineering 10th edition, Pearson, 2016. |
Students are responsible for lecture notes, reading assignments, as well as items distributed during the classroom sessions. Important reading materials as well as lecture slides will be placed on the class website.
Lecture notes
Readings
Project resources
Students will be evaluated as follows:
Exams and quizzes: 50%
Term project: 30%
Homework labs: 20%
Grading scale:
A = 90%..100%
B = 80%..89%
C = 70%..79%
D = 60%..69%
Exams and quizzes will be closed book and notes and on Canvas. Always bring a device that allows you to connect to Canvas and take the exam or quiz. No other devices is to be used other than the device used for connecting to Canvas. No other app other than Canvas should be used.
All written work must be typeset and submitted on Canvas.
Term project. The term project will be team-based (teams of 4-6 individuals). The team project requirements will be discussed in-depth in class. The student teams will have to decide what computing platform and programming language to choose. The TAs will provide direction and support for the project artifacts or labs but are not expected to be expert on programming, programming languages, or computing platforms. Project code should be maintained on GitHub.
Technical problems. If you experience technical problems with your EECS account or the EECS servers or the lab equipment, please submit a support request help at: https://tsc.ku.edu/request-support-engineering-tsc.
Attendance. Attendance is important and required. Throughout the semester, attendance may randomly be taken; three absences or three zeros on lab assignments will result in a failing grade for the course. Furthermore, if a student misses a class session, he or she will be entirely responsible for learning the materials missed without the benefit of a private lecture on the instructor's part. Furthermore, the student will be responsible for finding out what assignments may have been given and when they are due, any updates to the project, schedule or the course syllabus.
Week 1: August 23 and August 25
Overview of the course
Striving for Successful Team (Intro to Git and GitHub)
Software Life Cycle
All lecture notes (slides) are on Canvas
Week 2: August 30 and September 1
Software Development Models
Chapter 1: Sofftware Products
Chapter 2: Agile Software Engineering
Agile Software Development
Lab 1: Git and GitHub
[Check out Github's education pack]
All lecture notes (slides) are on Canvas
Week 3: September 6 and September 8
Agile Development (lecture notes)
Chapter 2: Agile Software Engineering
Minimal Product (Project) Management
Domain Engineering
Requirements Engineering
Project part 1: Team profiles
All lecture notes (slides) are on Canvas
Week 4: September 13 and September 15
Why Modeling
Modeling with UML
UML Use Case Modeling
Chapter 3: Features, Scenarios, and Stories
Project: Vision statement
All lecture notes (slides) are on Canvas
Week 5: September 20 and September 22
UML class modeling
UML state transition modeling (will be covered at later time)
Thursday September 22: Exam 1
Lab: Use case modeling
All lecture notes (slides) are on Canvas
Week 6: September 27 and September 29
More on UML class modeling
From requirements to design: architectural selection
All lecture notes (slides) are on Canvas
Week 7: October 4 and October 6
Chapter 4: Software Architecture
Week 8: October 11 and October 13
Tuesday October 11: No class (last day of fall break)
The SDLC revisited: The Unified ProcessAll lecture notes (slides) are on Canvas
Week 9: October 18 and October 20
Detailed-design concepts: Modular design, object-oriented design,
design patterns
Thursday October 20: Exam 2
All lecture notes (slides) are on Canvas
Week 10: October 25 and October 27
Detailed-design concepts: Modular design, object-oriented design,
design patterns
Concepts related to writing programs (documentation, self-describing programs, coding conventions, pre- and post-conditions, interpreters vs compiled programs, the compilation process, "make" and "git")
All lecture notes (slides) are on Canvas
Week 11: November 1 and November 3
Chapter 5. Cloud-based Software
Chapter 6. Microservices Architecture
All lecture notes (slides) are on Canvas
Week 12: November 8 and November 10
Software quality assurance
Chapter 9. Software Testing
Testing coverage criteria
Black box test case generation techniques
All lecture notes (slides) are on Canvas
Week 13: November 15 November 17
White box test case generation techniques (continued)
Chapter 9. Software Testing
All lecture notes (slides) are on Canvas
Week 14: November 22 and November 24
Examples of code-based testingThursday November 24: No class (Thanksgiving break)
All lecture notes (slides) are on Canvas
Week 15: November 29 and December 1
Chapter 8. Reliable Programming
Chapter 7. Security and Privacy
All lecture notes (slides) are on Canvas
Week 16: December 5 and December 7
UML revisited: modeling behavioral properties
Chapter 10. DevOp and Code Management
Emerging trends in software engineering
All lecture notes (slides) are on Canvas
Week 17: December 12
Comprehensive final December 14 1:30-4:00 pm
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: 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.
Attendance, late work, and makeup 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
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.
Common policies
As an engineering student at the University of Kansas,
all written communications should reflect professional
standards. Please note:
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.
LLM and generative AI tools
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.
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:
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:
Code of student rights and responsibility: Code of Student Rights and Responsibilities
Professor Hossein Saiedian
Electrical Engineering & Computer Science
Eaton Hall 3012
University of Kansas
1520 W 15th St
Lawrence, KS 66045-7621
+1 785 864-8812
saiedian at eecs.ku.edu