CS240 Spring 2024 Course info

Skip to: Course Components, Marks, Missed Deadline, 48-Hour Absence, Return Policy, Final Exam -- Failure to write , Academic Dishonesty, Academic Integrity, Intellectual Property, Students with Disabilities


Information on this page is currently copied over from previous offerings and may still change

Course Components


The primary components of the course are lectures, assignments, and exams, and the policies and procedures for each of these are outlined on their respective pages. There are also tutorials, some materials for which are posted on the Tutorials page.

This website will be the primary means of distribution of materials for the course. A broader forum for course-related communication will be Piazza, as discussed on the resources page. Textbooks used in the course are also listed on that page, although the primary source for information will be the lectures and the course notes.


Marks


The final course grade will be determined as follows:

Course Component Weight
5 Assignments25% (5% each)
2 Programming Questions6% (3% each)
Midterm (in-person)24%
Final exam (in-person)45%

Students must pass the weighted average of the Midterm and Final Exams in order to pass the course.

A summary of grades for previous assignments and midterms indicates what we have as of the date shown in the linked page. NOTE: This information is only updated periodically.
MarkUs has the detailed assignment results as well as any mark changes between the last summary of grades update and the next one. If the grade on this website is incorrect right after an update, please contact the Instructional Support Assistant (ISA) at cs240 [AT] uwaterloo [DOT] ca

Missed Deadlines


Late Policy

Assignments will be due by 5:00pm on the due date, however, we do offer a grace period until 11:59pm on the date the assignment is due to be submitted.

Note that since a significant grace period is being offered, there will be no exceptions for late submissions, no matter the reason (e.g. internet connectivity issues, problems with formatting answers etc.). The grace period exists to accommodate precisely these difficulties when attempting to submit an assignment before 5:00pm. Students are responsible for treating the 5:00pm deadline as final, and getting their answers ready before this time. Students should also not expect instructor/ISA assistance after the 5:00pm deadline, as the assignment is already "due". No answers submitted from 11:59:01pm onwards will be accepted.


Start assignments as soon as they come out. If some material on the assignment has not been covered in lecture yet, it will be in the next lectures so you can watch for it and save time (and learn the material better with longer retention) by applying it to the assignment while it is fresh in your mind.

Set the deadline in your calendar to be at least 1-2 days before it is due and aim for the earlier deadline and submit what you have then. This gives you a buffer for unforeseen circumstances (e.g. needing to seek help from course personnel, computer crash, internet issues, illness, forgetting to submit by deadline, etc.)

48-Hour Self-Declared Absence on Quest

As of Fall 2022, the University introduced the option for students to self-declare a 48-hour absence on Quest during the Formal Lecture Period for any reason. If an absence happens to overlap with an assignment's official deadline or the Midterm, we offer the following accommodations:

Note: For a 48-hour absence self-declaration on Quest for a written assignment, you must notify the ISAs within the grace period that you used the 48-hour absence to ensure it is marked.

You may declare a 48-hour absence by filling out This Form

You can read more about declaring a 48-hour absence on Quest here.

Doing, without excessive collaboration, all assignments in this course is vital to developing long-term understanding of the course material.

COVID-like Symptoms Self-Declared Absence on Quest or VIF submitted on-line through MUO

A self-declaration on Quest of COVID-like symptoms or a Verification of Illness (VIF) submitted on-line through MUO, that covers the official due date and time of an assignment or the midterm will be excused as described under the 48-Hour Self-Declared Absence on Quest described above.

For other absences, contact the ISC (Karen Anderson, kaanders at uwaterloo.ca) to determine what documentation is needed.

Note:

This is to ensure we have enough submitted work to assess student knowledge and experience for final grades and to make sure students have practice to deepen course knowdedge and learning. If more than this has verification for non-submittal, then it will be considered on a case-by-case basis.

Students who don't submit assignments by deadlines should still do the missed assignment, submit to MarkUs or Marmoset, as appropriate, and email the ISAs (cs240 at uwaterloo.ca) to get feedback. Students who miss assignments or excessively collaborate on them tend to do worse on exams without this practice and the understanding gained.

Return Policy

Assignments and Midterm: There will be an announcement on the course website and Piazza when marking for an assignment or the midterm is available for MarkUs (assignments) or Crowdmark (midterm) viewing.

Final Exams: Final exams are not returned. Students wishing to view their final exam may do so by contacting the Instructional Support Coordinator, Karen Anderson, at kaanders [AT] uwaterloo [DOT] ca after the final exam period is over.

Mark Appeals

We take great care to ensure that all marks are recorded properly in our database. Nevertheless, please ensure that your mark was recorded properly by regularly checking your record in the grade lookup system. Any discrepancies should be reported immediately to the instructional support assistant.

All mark appeals (for assignments and midterm) must be made within 10 days of the date of initial release of marking and post mortem to students or before the final exam, whichever is earlier. Note that as a result of closer scrutiny of your work (possibly all questions), marks may go up or down if the marking is inconsistent with the standards used to mark everyone else.

Final Exam -- Failure to Write

In the Faculty of Mathematics, students who fail to write a final exam [of a Math Faculty course] are given either a DNW (Did Not Write) or an INC (incomplete). A DNW is equal to a 32 and is a failing grade. An INC is essentially permission to complete the course at a later date, usually by writing the final exam with the next term's CS240 class or with the CS240 class of the term after that.

Whether or not you are given an INC is strongly dependent on your performance during the term. A student with a medical reason may not be granted an INC because they have not performed sufficiently well during the academic term.

An INC will be granted ONLY if there is a strong reason for missing the exam (generally a serious medical issue verified by a doctor's note) AND a satisfactory performance during the term (both assignments and midterm).

Academic Dishonesty

All work in CS240 is to be done individually and be your own work. MOSS (Measure of Software Similarities) is used in this course as a means of comparing student programming assignments to ensure academic integrity. Cheating includes not only copying the work of another person (or letting another student copy your work), but also excessive collaboration. Such cases will be dealt with severely. We will follow the cheating policy of the Math Faculty, which usually means a grade of 0 on the assignment you cheated on, and a deduction of 5% from your course grade. You will also be reported to the Academic Integrity Officer, Faculty of Mathematics.

Academic Integrity

Academic Integrity: In order to maintain a culture of academic integrity members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility.

Grievance: A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70, Student Petitions and Grievances, Section 4. When in doubt please be certain to contact the department's administrative assistant who will provide further assistance.

Discipline: A student is expected to know what constitutes academic integrity, to avoid committing an academic offence, and to take responsibility for his/her actions. A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about 'rules' for group work/collaboration should seek guidance from the course instructor, academic advisor, or the undergraduate Associate Dean. For information on categories of offences and types of penalties, students should refer to Policy 71, Student Discipline. For typical penalties check Guidelines for the Assessment of Penalties.

Appeals: A decision made or penalty imposed under Policy 70 (Student Petitions and Grievances) (other than a petition) or Policy 71 (Student Discipline) may be appealed if there is a ground. A student who believes he/she has a ground for an appeal should refer to Policy 72 (Student Appeals).

Intellectual Property

Students should be aware that this course contains the intellectual property of their instructor, TA, and/or the University of Waterloo. Intellectual property includes items such as:

Course materials and the intellectual property contained therein, are used to enhance a student's educational experience. However, sharing this intellectual property without the intellectual property owner's permission is a violation of intellectual property rights. For this reason, it is necessary to ask the instructor, TA and/or the University of Waterloo for permission before uploading and sharing the intellectual property of others online (e.g., to an online repository). Permission from an instructor, TA, or the University is also necessary before sharing the intellectual property of others from completed courses with students taking the same/similar courses in subsequent terms/years. In many cases, instructors might be happy to allow distribution of certain materials. However, doing so without expressed permission is considered a violation of intellectual property rights.

Please alert the instructor if you become aware of intellectual property belonging to others (past or present) circulating, either through the student body or online. The intellectual property rights owner deserves to know (and may have already given their consent).

Note for Students with Disabilities

The AccessAbility office, located in Needles Hall Room 1401, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with AccessAbility Services at the beginning of each academic term.

Generative AI

This course includes the independent development and practice of specific skills. Therefore, the use of Generative artificial intelligence (GenAI) trained using large language models (LLM) or other methods to produce text, images, music, or code, like Chat GPT, DALL-E, or GitHub CoPilot, is not permitted in this class. Unauthorized use in this course, such as running course materials through GenAI or using GenAI to complete a course assessment is considered a violation of Policy 71 (plagiarism or unauthorized aids or assistance). Work produced with the assistance of AI tools does not represent the author’s original work and is therefore in violation of the fundamental values of academic integrity including honesty, trust, respect, fairness, responsibility and courage (ICAI , n.d.).

You should be prepared to show your work. To demonstrate your learning, you should keep your rough notes, including research notes, brainstorming, and drafting notes. You may be asked to submit these notes along with earlier drafts of their work, either through saved drafts or saved versions of a document. If the use of GenAI is suspected where not permitted, you may be asked to meet with your instructor or ISAs to provide explanations to support the submitted material as being your original work. Through this process, if you have not sufficiently supported your work, academic misconduct allegations may be brought to the Associate Dean. In addition, you should be aware that the legal/copyright status of generative AI inputs and outputs is unclear. More information is available from the Copyright Advisory Committee

Students are encouraged to reach out to campus supports if they need help with their coursework in general including: