Universität Wien

262014 VU Algorithms and Data Structures for Computational Science (2026S)

4.00 ECTS (3.00 SWS), SPL 26 - Physik
Continuous assessment of course work
Moodle
Th 28.05. 15:00-16:30 Seminarraum 9, Kolingasse 14-16, OG01

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Please note: (1) This course will start on March 10, 2026, i.e., there are no classes in the first week of March. (2) u:find currently shows more dates than we need for the course. There will be two classes per week until the midterm exam (planned: May 7), and one class per week afterwards (usually Tuesdays).

  • Tuesday 10.03. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 17.03. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 19.03. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 24.03. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 26.03. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 14.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 16.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 21.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 23.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 28.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 30.04. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 05.05. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 07.05. 15:00 - 16:30 Seminarraum 4, Währinger Straße 29 1.UG
    Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 12.05. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 19.05. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 28.05. 16:45 - 18:15 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 02.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 09.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 11.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 16.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 18.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Tuesday 23.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01
  • Thursday 25.06. 15:00 - 16:30 Seminarraum 9, Kolingasse 14-16, OG01

Information

Aims, contents and method of the course

We will study some more advanced topics in algorithms and data structures, such as:
- design and analysis of algorithms especially for graph and clustering problems
- efficient exact and approximation algorithms for optimization problems (greedy algorithms, Linear Programming)
- algorithms for big data (online algorithms, streaming algorithms, external memory algorithms)

On successful completion of this course, you will be familiar with the above concepts and methods and able to use them on your own in practice.

The schedule consists of interactive lectures as well as homework presentations and discussions.

Students are expected to have acquired basic knowledge in algorithms and data structures, e.g. 051024 VU Algorithms and Data Structures 1, prior to taking this course. See also the Extension Curriculum Basic Knowledge in Computational Sciences.

If you are unsure whether you meet these prerequirements, please contact the lecturer(s).

Assessment and permitted materials

A total of 100 regular points (100%) can be reached as follows:

- 2 written exams (midterm/final, 90 minutes): 35 points each
- 12 mini-quizzes: 1 point each
- presentation of a homework problem: 6 points
- written solution of a homework problem: 3 points
- submitted solution to problems on HW sheets other than presenting one: 9 points

At least three problems on each homework sheet need to be solved and the solution handed in. Every student needs to present a solution to a homework problem once during the semester, selected by a random process.

No materials are allowed for the written exams.

Up to 16 bonus points can be reached:
- 5 bonus points if you miss at most 2 classes (-1 for every further missed class)
- up to 8 bonus points for solving bonus problems on homework sheets
- up to 3 points for solving the online intro quiz on Moodle

Minimum requirements and assessment criteria

You need to score *at least 30 points in sum in the written on-site exam* to pass the course.

Then, if P is the sum of regular and bonus points received, your grade will be:

1, if P >= 89,
2, if P >= 76,
3, if P >= 63,
4, if P >= 50,
5, otherwise.

Presence is mandatory for the first lecture. Otherwise, it is not a requirement, but strongly recommended.
If you fail to show up for an exam, you will receive 0 points for this exam.

Homework sheets must be submitted before the deadline to be eligible for presentation in class. You can indicate for each problem on a homework sheet whether you would be willing to present it. The presenter for each problem is chosen by the instructors among all those that are willing to present, with ties broken randomly. There will be enough problems so that each student can present twice if everyone is willing to present all problems. If you fail to submit a homework sheet or are not chosen for presentation because you were unwilling to present many of the subproblems or are chosen to present but don't show up, you will receive 0 points.

Examination topics

- all material presented and discussed in class
- contents and discussion of all exercise sheets
- reading material as provided on Moodle

Reading list

Literature will be announced in class and (as far as possible) made available on Moodle.

Association in the course directory

PM-ADS

Last modified: Tu 19.05.2026 11:47