MTAT.03.083 Systems Modelling
Coordinator: Anastasija Nikiforova (anastasija.nikiforova at ut . ee)
- Lectures - Tue. 14.15 - 16.00, week 2-16, Narva mnt 18 - 1019 (for online attendees, Zoom link)
- Practical Sessions - Tue. 16.15 - 18.00 & Tue. 18.15 - 20.00 week 2-16, Narva mnt 18 - 1022 (group #2 is also available online, Zoom link)
- Exam - 12.12.2023, 16.01.2024 14:15-18:50
For questions, please use the Slack workspace
This course aims at imparting knowledge of modelling languages for software-intensive systems. The course will also impart methodological skills for using models to analyse, develop, test and simulate software systems, as well as will learn to critically reflect on adequate abstraction levels to describe different aspects of software systems.
Note: more detail see in the SIS. Please attend the first lecture and the first lab for more instructions.
- Anastasija Nikiforova (anastasija.nikiforova at ut . ee)
- Ahmed Mahmoud - teaching assistant
- Deepika Uttam Sambrekar - teaching assistant, 2nd practical session
- experts from the industry as guest lecturers
The course is delivered in the form of 16 workshops of 4 academic hours each. A workshop includes lecture time and classwork to be completed in teams. The course - lectures and practical labs - takes place in class. Please attend the first lecture and the first lab for more instructions.
Homeworks & project worth 40 points done in teams («portfolio» submission 3 times during the semester (mandatory) & one big homework (mandatory)), participation in the practical labs AND presenting the developed project (during practical labs) worth 20 points in total (optional), and a final exam worth 40 points (mandatory).
Total: 100 points
Homeworks and exam have to have a total of 40% of their possible points. Not reaching 40% in the respective part will lead to a grade of F regardless of the number of points in other parts.
- Final exam = 40 points - exam, consisting of a test (45 min) AND the final version of the "portfolio" with assignments completed during the semester is assessed AND a student is asked several questions on the topics covered during the course. Depending on the quality of the portfolio from 1 to 3 questions are asked based on the individual portfolio and the list of predefined questions announced shortly prior the exam.
All components are mandatory. All deadlines are strict.
There will be an opportunity to get a feedback and prospective grade for each assignments on a weekly basis (non-mandatory).
During the course additional optional / non-mandatory tasks for bonus points will be announced. A student is eligible and welcome to propose a task of interest (for instance, inspect what types of modelling techniques are used [in a particular sector] [in Estonia]? or what executable modelling / source code generation techniques / features / tools exist and what are their strengths and weaknesses? - comparative analysis of several alternative options or an extensive analysis of a selected technique (for a def. of "extensive" refer to the coordinator of the course), what are the current capabilities of ChtGPT for SM?) and, if confirmed with one of lecturers, it can also give additional points to the grade. The amount of points depends on the complexity of the task and the quality of the solution;
In order to pass the course, the student must have at least 51 point (grade E) in total and get no less than 31% out of 60% practical assignment points and 20% (out of 40%) points for the exam. A grade of 20 points or less in the final exam will be mapped into a fail grade (F).
The final grade will be mapped to a grade between A and F using the standard University scale.
- A final grade of 50 points or less will be mapped into a fail grade (F).
- A final grade of 51-60 points will be mapped into a grade (E).
- A final grade of 61-70 points will be mapped into a grade (D).
- A final grade of 71-80 points will be mapped into a grade (C).
- A final grade of 81-90 points will be mapped into a grade (B).
- A final grade of 91-100 points will be mapped into a grade (A).
The links on the left will take you to the pages containing the lecture slides, lecture video recordings and exercises used in this course.