Universität Wien

052100 VU Algorithms and Data Structures 2 (2025W)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Prüfungsimmanente Lehrveranstaltung
Moodle
Mo 17.11. 09:45-11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Montag 06.10. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 13.10. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 20.10. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 27.10. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 03.11. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 10.11. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 24.11. 09:45 - 11:15 Hörsaal I NIG Erdgeschoß
  • Montag 01.12. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 15.12. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 12.01. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 19.01. 09:45 - 11:15 Hörsaal 7 Hauptgebäude, Hochparterre, Stiege 7
  • Montag 26.01. 09:45 - 11:15 Hörsaal I NIG Erdgeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

**Unfortunately, we cannot accept any late registrations this semester, as the course is already overbooked. However, it will be offered again next semester.**

The main objective of this course is to learn some of the key techniques for designing and analyzing algorithms. We will study algorithmic paradigms and show concrete examples on how to use these paradigms to solve different optimization problems. This is a theoretical course, and we’ll largely be focusing on using mathematical tools to prove the correctness and the running time complexity of the algorithms.

At the end of the course, you should be able to recognize which paradigm you would need to use for solving new problems, as well as study the correctness and the time complexity of your suggested solutions.

Prerequisites:
- Discrete Mathematics – equivalent to 051110 VO Mathematical Foundations of Computer Science 1
- Introduction to Algorithms and Data Structures – equivalent to 051024 VU Algorithms and Data Structures 1

Topics:

* Proof Techniques

* Algorithmic Strategies:
- Dynamic Programming
- Greedy Algorithms

* Data Structures and Algorithms
- Maximum Flow
- Shortest Paths
- Hashing

Please note: The cluster Algorithms has two gatekeepers, this course *and* VU Numerical Algorithms, 3 ECTS. Both are required.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students can collect up to 100 regular points as follows:
- 2 online multiple choice quizzes (up to 10 points each)
- 2 written on-site exams (up to 35 points each)
- 10 questions of the day (mini-quizzes) (up to 1 point each)

In addition, up to 18 bonus points can be collected as follows:
- attending all classes (up to 4 points)
- online intro quiz (up to 4 points)
- 2 homework problems (up to 5 points each)

Exams/quizzes are closed-book, no resources/help is allowed.

*Tentative* dates for online quizzes: Nov 03, 2025 & Dec 15, 2026
*Tentative* dates for on-site written exams: Nov 24, 2025 & Jan 26, 2026

Mindestanforderungen und Beurteilungsmaßstab

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

Prüfungsstoff

Everything covered in the lecture, the reading material, the homework problems, and the quizzes.

Literatur

- Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford. Introduction to Algorithms. MIT Press, 2009/2022 (3rd & 4th edition).
- Kleinberg, Jon; Tardos, Éva. Algorithm Design. Pearson, 2006.
- Erickson, Jeff. Algorithms. Online resource: http://algorithms.wtf/

Further literature will be provided via Moodle.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Di 21.10.2025 11:45