There are 3 mandatory assignments (numbered 1 to 3 below, whose statements will appear in due time), worth 3 higher-education credits (ECTS credits) in total. The main objective of the assignments, which are to be done in teams, is to exercise the theoretical knowledge gained in the lectures, on carefully selected problems of our choice. We are not just interested in sufficiently correct and efficient models, but also in explanations and experimental evaluations, hence a report is also required for each assignment and its quality has an impact on your score.
For each assignment, the assistants supervise 3 optional (but highly recommended) help sessions for troubleshooting in the preparation of your reports. Assignment 1 is scored pass / fail in order to get started gently, and each other assignment gets an assignment score in the integer interval 0..5. The report must be briefly presented orally in a mandatory grading session. Solutions and collective feedback are given in an optional (but highly recommended) solution session.
PhD students do either just the assignments (solo), or just the project (solo; possibly in connection with their PhD research; but they are highly encouraged to do the assignments nevertheless), or both: contact the head teacher.
The objective of a help session is only for the assistants to help you prepare an acceptable report for the assignment with the closest upcoming deadline. Each assignment will normally be published at least one week prior to its first help session. Also, the necessary course material will normally have been presented in lectures at least one week prior to the first help session. You are thus able and even strongly encouraged to prepare your report as far as possible until the help sessions and to attend them, in order to make best use of that reserved time span of personal attention by the assistants.
Note that no further tutoring on lecture topics, such as exercises whose solutions are given or to be handed in at the end of the session, will be performed by the assistants at the help sessions.
The initial score, in the integer interval 0..5 (or pass / fail for Assignment 1), of your assignment report will normally be announced by 16:00 of the day before the grading and solution sessions for that assignment. Toward this, the assistants run your model on the provided instances and examine your report.
The objective of a grading session is to determine the final score of each teammate for the submitted report to the assignment of the previous deadline. Each team is given a time slot, during which they must briefly present their report and answer questions about it. A team with an initial score in the set {1,2} (or pass for Assignment 1) might be given the opportunity of correcting their mistakes, provided they are minor, and thereby possibly increasing their initial score by one point. The initial score is the final score, unless (a) the teammates perform differently at the grading session, in which case the weaker teammate gets one point less (or possibly fail for Assignment 1), or (b) a suspicion of freeloading (with the teammate or generative AI) or plagiarism arose, in which cases no final score is given.
Time slots are strict. Exceptions must be negotiated in due time during work hours with the head teacher, upon reporting a convincing case of force majeure.
The objective of a solution session is only to give collective feedback and discuss acceptable solutions to the assignment of the previous deadline. No models will be handed out. The first two solution sessions are merged with the initial help sessions to the next assignment.
Some comments on your submitted report can be found at Studium, as comments in the textbox or as annotations to the report; more detailed feedback can be obtained orally from the assistants upon appointment.
Note that no further tutoring on lecture topics, such as exercises whose solutions are given or to be handed in at the end of the session, will be performed by the assistants at the solution sessions.
| Assignment | Help session a | Help session b | Help session c | Deadline | Grading session (mandatory) | Solution session |
|---|---|---|---|---|---|---|
| warmup-MiniZinc.pdf, exercises on comprehensions (no hand-in), and warmup-LaTeX.pdf (the links will work in due time) | Fri 06 Nov | none | none | none | none | none |
| assignment1.pdf (the link will work in due time) | Fri 06 Nov | Tue 10 Nov | Thu 12 Nov | Fri 13 Nov at 13:00 | Thu 19 Nov | Thu 19 Nov |
| assignment2.pdf (the link will work in due time) | Thu 19 Nov | Tue 24 Nov | Wed 25 Nov | Fri 27 Nov at 13:00 | Thu 03 Dec | Thu 03 Dec |
| assignment3.pdf (the link will work in due time) | Thu 03 Dec | Mon 07 Dec | Thu 10 Dec | Fri 11 Dec at 13:00 | Thu 17 Dec | Thu 17 Dec |
All assignment reports must follow the assignment-specific skeleton report and skeleton model(s). See the demo report for generic instructions and the expected quality of each part of the provided skeleton report. Submission is via Studium. Submission deadlines are hard. Exceptions must be negotiated in due time during work hours with the head teacher, upon reporting a convincing case of force majeure. Grading will only start after a deadline, so you can submit multiple times until then.
For pedagogic and resource reasons, every assignment report and project deliverable must be prepared by a team of 2 students, both being first-time students or both being non-first-time students of this course. No permission will ever be granted for teams of three or more students.
Until 23:59 of Sun 8 Nov 2026, you can declare a team at Studium: both teammates must consent to forming a team. If you are not formally registered yet, then you can declare your team by email to the helpdesk by that hard deadline.
You are strongly encouraged to advertise your search for a teammate at a course event or by using the Teammate Search discussion at Studium, so as to find somebody:
with the same level of ambition for this course,
with complementary skills (mathematics, LaTeX, English/Swedish/..., etc),
with compatibility on the preferred software platform (Linux/macOS/Windows) and preferred meeting locations and hours,
and, for the international students, ideally not of the same home university or country.
If you are however fine with a randomly assigned teammate, then either sign up for one of the Random Teams at Studium or declare this by email to the helpdesk by that hard deadline: you might not get any teammate, because you are the odd one out or because the assigned one drops the course on short notice, so start working solo on Assignment 1 in order to guard against this possibility.
All students who have done neither of those actions by that hard deadline will be considered to have dropped the course, but will not be unregistered by us: their submitted deliverables will normally not be graded.
Teams may change between assignments: permission will be granted, as long as you inform the helpdesk in advance and the number of teams does not increase.
Only one teammate of each team needs to submit each assignment report or project deliverable.
Exceptions for solo work must be negotiated in due time, during work hours, with the head teacher, upon reporting a convincing case of force majeure. The assignments are calibrated somewhat smaller for those students. Such an exception is only valid for the assignment(s) it was negotiated for.
The legislation on plagiarism and cheating of Uppsala University will be rigorously applied, without exceptions. This disallows using a public repository (such as at GitHub, where you should use a free private student repository) for code management within your team. We reserve the right to use plagiarism detection tools and point out that they are extremely powerful.
When submitting you implicitly certify that your report and all its uploaded attachments were produced solely by your team, except where explicitly stated otherwise and clearly referenced, that each teammate can individually explain any part at the mandatory grading session, and that your report and attachments are not freely accessible on a public repository.
Every report has a mandatory section for disclosure on the use of generative AI tools other than for grammar, spelling, punctuation, and accessibility purposes. There is absolutely no need to use generative AI tools beyond those purposes. The following cases exist:
No use of generative AI: encouraged.
Use of generative AI as support: allowed. Generative AI tools have been used to support the working process or learning. What is submitted is the team's own reasoning and approach to the questions: generative AI tools have been an aid along the way, but not the source of the submitted answers.
Use of generative AI output in the report: disallowed. What is submitted relies to a substantial extent on the reasoning, approach, or conclusions of generative AI tools, regardless of whether the material is reproduced verbatim, has been edited, or has been reworded by the team.
We reserve the right to give different assignment scores to the teammates of a team, depending on the performance at the mandatory grading session.
Please report any problems within a team to the head teacher, who will handle the case in confidence, in the best interest of both teammates, keeping the ethics dimension in mind.
One higher-education credit (ECTS credit) translates under Swedish university law into an expected 26.67 hours of work for the average student.
The assignments are worth 3 credits: discounting about half of the 21 hours spent on the lectures (the other half being similarly discounted on the 2 project credits), the assignments are calibrated to take about 21 hours of work on average by the average student, for each teammate, including the help, grading, and solution sessions.
All this does not clash with other courses you are taking, as university studies are legally defined to take 400 hours of work per study period (normally 10 weeks), and the standard 15 credits targeted in a study period are calibrated to reach that total.
The assignment grade is determined by a published scale, depending on the assignment scores.
The overall grade is determined by a published scale, depending on the assignment scores and the project score.
These rules are effective as of Mon 2 Nov 2026. The head teacher reserves the right to modify them at any moment, should special circumstances call for this.