CS360

Copyright @ CMPUT301 - University of Alberta

Course Outline Spring 2026

Dr. Suleman Shahid and Dr. Abdul Ali Bangash, Department of Computing Science, LUMS (2026). Dr. Hazel Campbell, Department of Computing Science, University of Alberta (2019, 2023, 2024). Dr. Abram Hindle, Department of Computing Science, University of Alberta (2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023). Alexander Wong, 2019. status: published summary: Lecture, Labs, Contact Information, Lecturer, Teaching Assistants, Course Content, Course Description, Prerequisites, Objectives and Learning Outcomes, Course Topics, Learning Resources, Course Schedule, Required Textbook and/or Other Major Course Materials, Recommended or Optional Learning Resources, Course Fees, On-Line Homework Disclaimer, Academic Success Centre, Faculty of Science Student Services, Grade Evaluation, Letter Grades, Statement of Expectations for AI Use, Re-Evaluation of Term Work, Re-examination, Past or Representative Evaluative Material, Labs, Participation, Policies for Late and Missed Work, Late Policy, Non-medical Protected Grounds, Missed Term Work: Assignments, Labs, Quizzes, Project Parts, Midterm Exams, Missed Term Work: Participation, Deferred Final Examination, Required Technology, Labs Assignments and Project, Lecture Participation, Remote Delivery Considerations, Technology Requirements, Recordings of Synchronous Activities, Home-Based Lab Activities, Student Resources for Remote Learning, Student Responsibilities, Academic Integrity and Student Conduct, Contract Cheating and Misuse of University Academic Materials or Other Assets, Contract Cheating: CS Courses, Academic Integrity Issues Related to Minor Formative Assessments, Appropriate Collaboration, Citation, Solo Effort: Participation Exercises, Quizzes, Exams, Confidential: Exams, Consultation: Assignments, Labs, Teamwork: Group Projects, Intellectual Violence, Exam Conduct, Lecture Conduct, Students Eligible for Accessibility-Related Accommodations, Recording and/or Distribution of Course Materials, On-Campus Computer Labs, Recording and/or Distribution of Course Materials, Learning and Working Environment, Feeling Stressed, Anxious, or Upset?, Student Self-Care Guide, Land Acknowledgement, Administrative, Policy about Course Outlines, Disclaimer, Update History, Copyright

CS360: Software Engineering
Spring 2026

Course Instructors

Dr. Abdul Ali Bangash
Dr. Suleman Shahid
Safa Salam

Lecture Information

Teaching Assistant(s): Available on LMS

Labs: Online 6:15pm to 8:30pm Wed/Thur

COURSE CONTENT

Calendar Description:
As an introduction to software engineering, this course is about building software effectively. You will apply good practices, effective design techniques, and development tools within a team project to create an application with a graphical user interface.

The focus is largely practical, with broad coverage in topics such as: object-oriented design, user interfaces, unit testing, design patterns, and refactoring.

Communication skills, team dynamics, working with a "customer", and creativity are also important factors in the course project. The knowledge, skills, and experience you gain will be invaluable in your future software development projects.

Course Objectives and Expected Learning Outcomes:
We will learn about applying software engineering concepts to design and implement interactive applications.

One effective way to build such applications is to apply object-oriented design and use software components. To be useful to end users, the design of these applications must also be guided by usability principles. The course involves a team project in building a well-designed Java/Android application with a sophisticated graphical user interface.

By the end of this course, you will have a strong background in basic software engineering concepts. Also, you will have the skills to implement interactive applications in Android. You will learn to propose and think critically about software and user interface designs.

Students are expected to participate in all classes and labs.

LEARNING RESOURCES

Required Course Materials:
This course does not have a required textbook. There are a number of excellent resources for this course, available as electronic books or through open access on the Web. See the course LMS for links.

Images reproduced in lecture slides have been included under section 29 of the Copyright Act, as fair dealing for research, private study, criticism, or review. Further distribution or uses may infringe copyright on these images.

In addition to fair dealing, the Copyright Act specifically exempts projected displays by educational institutions for the purposes of education or training on the premises of the education institution.

Copyright regulations, however, prohibit me from distributing complete copies of the lecture slides on the course site.

You may assume that any code examples we provide to you are public domain and free for you to take without attribution, unless they are licensed.

Recommended or Optional Learning Resources:
See the resources page on the course webpage.

Course Schedule & Assigned Readings:
See the online live schedule here: https://docs.google.com/spreadsheets/d/1WXOvrmoseOKpqhYd16F1AkesHH3Ew_GlPVFuwbTS_4Y/edit?usp=sharing

Other Course Fees:
Students will be required to use the online service Firebase in order to complete the coursework and course project. The expected fees are $0, however, Firebase may assess fees if storage, bandwidth, user, or operation limits are exceeded. One member of the group will be required to supply payment information. It is the responsibility of the student to pay for any Firebase charges. If you are unable to pay these fees, you must contact your TA and instructor immediately.

On-Line Homework Disclaimer:

REMOTE DELIVERY CONSIDERATIONS

Hybrid Synchronous Delivery:
There are no online lectures or recorded lectures. Lectures are in person.

GRADE EVALUATION

Assessment Weight Collaboration Policy Date
Participation 8% Solo Effort Most Lectures
Labs 5% Consultation Tuesdays 5:00pm
Assignment 0 1% Consultation ~ Week 3 - 2026-02-05 5pm
Project Part 0 1% Teamwork ~ Week 3 - 2026-02-05 5pm
Assignment 1 8% Consultation ~ Week 5 - 2026-02-17 5pm
Project Part 1 1% Teamwork ~ Week 5 - 2026-02-16 5pm
Project Part 2 5% Teamwork ~ Week 8 - 2026-03-10 5pm
Project Part 3 10% Teamwork ~ Week 10 - 2026-03-26 5pm
Project Part 4 16% Teamwork ~ Week 14 - 2026-04-19 5pm
Midterms 45% Confidential MT1 - 20% - 2026-03-12
MT2 - 25% - 2026-04-23

Grades are unofficial until approved by the Department and/or Faculty offering the course.

Midterm Dates

50 minute exams at:

Re-examination:
There is no possibility of a re-examination in this course.

Course Grades Obtained by Undergraduate Students:
This table reflects the GPA Point Value and Descriptor (e.g., Excellent, Good) for each Letter Grade.

Descriptor Letter Grade Grade Point Value
Excellent A+ 4.0
Excellent A 4.0
Excellent A- 3.7
Good B+ 3.3
Good B 3.0
Good B- 2.7
Satisfactory C+ 2.3
Satisfactory C 2.0
Satisfactory C- 1.7
Poor D+ 1.3
Minimal Pass D 1.0
Failure F or F4 0.0

Note: F4 denotes eligibility of a student to apply for a re-examination in a course.

Course Grades Obtained by Graduate Students:
This table reflects the GPA Point Value and Descriptor (e.g., Excellent, Good) for each Letter Grade.

Descriptor Letter Grade Grade Point Value
Excellent A+ 4.0
Excellent A 4.0
Excellent A- 3.7
Good B+ 3.3
Good B 3.0
Satisfactory B- 2.7
Satisfactory C+ 2.3
Failure C 2.0
Failure C- 1.7
Failure D+ 1.3
Failure D 1.0
Failure F 0.0

Statement of Expectations for AI Use:
You MUST not submit work by LLMs as your own, that is plagiarism. This also applies to other "AI" and Generative Models: ChatGPT, Lex, Page, DALL-E2, Google BARD/Gemini, Microsoft Bing/Copilot, and others. If you use LLMs you must cite it. This includes the corporation that made the AI, the AI, Subject, and Date. For example:

// The following function is from Microsoft, Copilot, "How do I write a merge sort in JavaScript?", 2023-08-31

function mergeSort(array) {

If you use LLMs you must cite it, but it's probably better to Google what it tells you and find a real citation because:

LLMs like ChatGPT are wrong a lot. It does not understand computer science. It understands how to form sentences and paragraphs well enough to be convincing, but it doesn't actually understand what anything it is saying means. When it has the choice between two answers, with opposite meanings, it will pick the answer that looks more like things it has seen before, not the answer that is more correct. This means you need to double-check that what it tells you is actually correct.

StackOverflow is always a better resource than Large Language Models such as ChatGPT, Copilot, Bard/Gemini, etc., but of course if you use code from StackOverflow or any other website, you must cite it. This is because other human programmers will usually check and downvote, remove, or fix bad information on StackOverflow. No one is checking the output of LLMs: if an LLM lies to you, no one will ever know.

ChatGPT and similar services are recording everything you tell it, and tracking you. Using ChatGPT/Bing/Bard etc. they are recording everything you say and how the LLM responds to you. There is no privacy.

Re-evaluation of Term Work:
Any questions or concerns about marks on a particular assignment must be brought to the attention of the instructor (not a TA) within 7 calendar days of its return date. After that, we will not consider remarking or re-evaluating the work. So do not expect anyone to re-evaluate all the work you did all term long in the hopes of getting a higher final grade.

However, clerical errors such as incorrectly computing or recording a mark may be raised at any time prior to 2 business days following the final exam. It is the student's responsibility to confirm that their term work has been recorded properly.

POLICIES FOR LATE AND MISSED WORK

Late Policies:

Missed Term Work/Final Exam Due to Non-medical Protected Grounds (e.g., religious beliefs):
When a term assessment or final exam presents a conflict based on non-medical protected grounds, students must apply for a petition from OSA. Students can review their eligibility and choose the application process specific for Accommodations Based on Non-medical Protected Grounds.

It is imperative that students review the dates of all course assessments upon receipt of the course syllabus, and apply AS SOON AS POSSIBLE to ensure the timely application of the accommodation. Students who apply later in the term may experience unavoidable delays in the processing of the application, which can affect the accommodation.

Missed Labs:
Labs are due Friday at 5PM on the same week the lab was presented. Project meetings are due at the time of the meeting, and they are included in the lab mark. Failure to attend and actively participate in project meetings will result in a lab mark of zero.

The 2 lowest marks for Labs (including project meetings) will be dropped when calculating the course mark. No late labs will be accepted. Failure to complete a lab (or to attend a project meeting) on time for any reason will result in a mark of zero. Please note that you can miss 2 labs (or project meetings) without penalty.

Missed Lecture Participation:
Participation exercises will be available at most lectures.

The 6 lowest marks for lecture participation will be dropped when calculating the course mark. No late participation will be accepted. Failure to complete a participation exercise on time for any reason will result in a mark of zero. Please note that you can miss 6 lectures without penalty.

Missed Assignments, Project Parts, Quizzes, Midterm Exams:
A student who cannot complete an assignment, project part, quiz, or midterm exam, due to incapacitating illness, severe domestic affliction or other compelling reasons must contact the instructor within two business days of missing the assessment, or as soon as possible, to request an excused absence using the absence form. If an excused absence is granted, then the deliverable weight will be split and shared over other deliverables in the same category. If a Midterm exam is missed, then its weight will be split and shared over the other Midterm exams. An excused absence is a privilege and not a right. There is no guarantee that an absence will be excused. Misrepresentation of facts to gain an excused absence is a serious breach of the Student Academic Integrity Policy. In all cases, instructors may request adequate documentation to substantiate the reason for the absence at their discretion.

Failure to complete an assignment or contribute to a project part without an excused absence will result in a raw score of zero or a proportional score reduction.

Additional information regarding missed Midterm Exams: If Midterm 3 is missed, then it will be replaced by a deferred exam that will include an oral examination component. The time of this deferred + oral exam will be determined individually between student and instructor.

STUDENT RESPONSIBILITIES

Academic Integrity and Student Conduct:
LUMS is committed to the highest standards of academic integrity and honesty, as well as maintaining a learning environment that fosters the safety, security, and inherent dignity of each member of the community, ensuring students conduct themselves accordingly. Students are expected to be familiar with the standards of academic honesty and appropriate student conduct, and to uphold the policies of the University in this respect.

Students are particularly urged to familiarize themselves with the academic policy, and avoid any behaviour that could potentially result in suspicions of academic misconduct (e.g., cheating, plagiarism, misrepresentation of facts, participation in an offence) and non-academic misconduct (e.g., discrimination, harassment, physical assault). Academic and non-academic misconduct are taken very seriously and can result in suspension or expulsion from the University.

All forms of academic dishonesty are unacceptable at the University. Unfamiliarity of the rules, procrastination or personal pressures are not acceptable excuses for committing an offence. Listen to your instructor, be a good person, ask for help when you need it, and do your own work -- this will lead you toward a path to success. Any academic integrity concern in this course will be reported to the College of Natural and Applied Sciences.

"Integrity is doing the right thing, even when no one is watching" -- C.S. Lewis

Contract Cheating and Misuse of University Academic Materials or Other Assets:
Contract cheating describes the form of academic dishonesty where students get academic work completed on their behalf, which they submit for academic credit as if they had created it themselves. Contract cheating may or may not involve the payment of a fee to a third party, who then creates the work for the student.

Examples include:

  1. Getting someone to write an essay or research paper for you.
  2. Getting someone to complete your assignment or exam for you.
  3. Posting an essay, assignment, or exam question to a tutorial or study website; the question is answered by a "content expert", then you copy it and submit it as your own answer.
  4. Posting your solutions to a tutorial/study website, public server, or group chat and/or copying solutions that were posted to a tutorial/study website, public server, or group chat.
  5. Sharing your login credentials to the course management system (e.g., Canvas) and allowing someone else to complete your assignment or exam remotely.
  6. Using an artificial intelligence bot or text generator tool to complete your essay, research paper, assignment, or exam solutions for you (without the instructor's permission).
  7. Using an online grammar checker to "fix" your essay, research paper, assignment, or exam solutions for you (without the instructor's permission).

Contract cheating companies thrive on making students believe that they cannot succeed without their help; they attempt to convince students that cheating is the only way to succeed.

Uploading the instructor's teaching materials (e.g., course outlines, lecture slides, assignment, or exam questions, etc.) to tutorial, study, or note-sharing websites or public servers is a copyright infringement and constitutes the misuse of University academic materials or other assets. Receiving assignment solutions or answers to exam questions from an unauthorized source puts you at risk of receiving inaccurate information.

Receiving assignment solutions or answers to exam questions from an unauthorized source puts you at risk of receiving inaccurate information.

Additional Examples of Contract Cheating:

Logging in as someone else Sharing your login credentials Sharing your anonymous ID Using someone else's anonymous ID Allowing someone else to log in as you Representing yourself as someone else Having someone else represent themselves as you On other LUMS services and linked services: Zoom gmail Google Chat, Drive, ... Lab computers Wi-Fi ... On an external service, website, or app: repository hosting services: GitHub, GitHub Classroom, Bitbucket, GitLab, ... live quiz services: Mentimeter, ... Textbook websites/apps KnowledgeTree/MasteryGrids online tutorials online practice systems online homework systems

Appropriate Collaboration:
Students need to be able to recognize when they have crossed the line between appropriate collaboration and inappropriate collaboration. If students are unsure, they need to ask instructors to clarify what is allowed and what is not allowed.

Here are some tips to avoid copying on assessments:

  1. Do not write down something that you cannot explain to your instructor.
  2. When you are helping other students, avoid showing them your work directly. Instead, explain your solution verbally. Allowing your work to be copied is also considered inappropriate collaboration.
  3. It is also possible that verbally discussing the solution in too much detail may result in written responses that are too similar. Try to keep discussions at a general or higher level.
  4. If you find yourself reading another student's solution, do not write anything down. Once you understand how to solve the problem, remove the other person's work from your sight and then write up the solution to the question yourself. Looking back and forth between someone else's paper and your own paper is almost certainly copying and considered inappropriate collaboration.
  5. If the instructor or TA writes down part of a solution in order to help explain it to you or the class, you cannot copy it and hand it in for credit. Treat it the same way you would treat another student's work with respect to copying, that is, remove the explanation from your sight and then write up the solution yourself.
  6. There is often more than one way to solve a problem. Choose the method that makes the most sense to you rather than the method that other students happen to use. If none of the ideas in your solution are your own, there is a good chance it will be flagged as copying.

For programming assignments, powerful software tools are used to detect plagiarism. When the software tools indicate that there is similarity between two submissions, the submissions are reviewed by the instructor or teaching assistant. If the possibility that the standards for academic honesty were violated is confirmed, an investigation is started. Eventually the submitted solutions may be forwarded to the Faculty of Science Associate Dean of Students for further investigation and eventual sanctions.

All suspected cases of plagiarism and other forms of cheating are immediately referred to the Disciplinary Committee. Please do not put yourself or us into such an unpleasant situation.

Citations:
If you include code or ideas from someone who isn't you (including from a Generative AI or LLM) you must cite it. Here are examples of an appropriate citation:

// The following function is from Microsoft, Copilot, "How do I write a merge sort in JavaScript?", 2023-08-31

function mergeSort(array) {

To cite something written by an entity such as a real person you must include the name of the author, the name of the resource, directions to the resource (like a URL). 

/* This function was made by Gerald <gerald@example.com> in lib/X.c at https://example/libX/src/lib/X.c 2015 */

void scrambleEggs() {

Stackoverflow recommends you cite the author, the license, the title of the question, the url to the answer.

/* 
   Author: Felix Too https://stackoverflow.com/users/4083076/felix-too
   Title: "Failed to install the following Android SDK packages as some licences have not been accepted" error
   Answer: https://stackoverflow.com/a/55641042
   Date: 2019-04-11
   License: CC-BY-SA 4.0 (International)
*/

Collaboration policy definitions:
The following are definitions for the different collaboration policies used in this course

Solo Effort:
Participation exercises fall under the department's Solo Effort model unless announced by the instructor. Solo Effort must be completed by the student registered in the course without external assistance from any individual or organization.

Confidential:
Midterms and Final Exams are also Confidential in addition to Solo Effort as listed above.

Consultation:
Individual assignments and labs are under the department's Consultation model. That means you may discuss the labs with others, but you must create and submit a solution that is entirely your own work. If you consult with other students, you must list their names in a comment at the top of your submission or in your repository README, along with a brief description of the part(s) of the assignment you discussed.

How to consult with other students without plagiarizing:

Examples of consultation:

Teamwork:

Intellectual Violence:
In this course, Intellectual Violence is considered bullying. Intellectual violence is when one teammate uses their skill, knowledge, or experience, to intimidate or control the other teammate(s) rather than sharing and helping them learn. Examples of Intellectual Violence

Exam Conduct:

Some key points to be aware of:

Recording and/or Distribution of Course Materials:
Audio or video recording, digital or otherwise, of lectures, labs, seminars or any other teaching environment by students is allowed only with the prior written consent of the instructor or as a part of an approved accommodation plan. Student or instructor content, digital or otherwise, created and/or used within the context of the course is to be used solely for personal study, and is not to be used or distributed for any other purpose without prior written consent from the content authors.

Disclaimer:
Any typographical errors in this syllabus are subject to change and will be announced in class and/or posted on the course website. The date of final examinations is set by the Registrar and takes precedence over the final examination date reported in the syllabus.

Copyright: