Universität Wien
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051024 VU Algorithms and Data Structures 1 (2026S)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
Moodle
We 02.09. 09:45-13:00 Auditorium Maximum Tiefparterre Hauptgebäude Stiege 10

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. 50 participants
Language: German, English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 03.03. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 10.03. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 17.03. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 24.03. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 14.04. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 21.04. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 28.04. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 05.05. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 12.05. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 19.05. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 26.05. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 02.06. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 09.06. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 16.06. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 23.06. 08:00 - 11:15 Hörsaal 1, Währinger Straße 29 1.UG
  • Tuesday 30.06. 08:00 - 09:30 Auditorium Maximum Tiefparterre Hauptgebäude Stiege 10

Information

Aims, contents and method of the course

Learning goals
• Develop a clear understanding of the computational model (via C++).
• Analyze running time through the study of sorting algorithms.
• Build clean mental models of fundamental data structures and gain fluency with standard implementations.
• Deepen algorithm design and analysis skills through graph and optimization problems.

Contents
• Introduction to the computational model
• Sorting algorithms
• Lists, stacks, and queues
• Hashing
• Trees: heaps and search trees
• Graphs: terminology review, key algorithms, and proofs of correctness

Language and attendance
• The course will be taught in English.
• On-site in-class attendance at the first lecture is mandatory.
– You will either sign on an attendance sheet or mark it via Moodle.
– In case it's done via Moodle, you will need to use your phone/tablet/laptop, and attendance-marking procedure will be demonstrated in class.

Tutorials and homework
• Homework will be solved independently and discussed in tutorials.
• Tutorial time slots will be chosen by student vote during the first week.
• Whether tutorials are online or on-site will be announced later.
• While voluntary, attending the tutorial is strongly recommended to consolidate course concepts.

Prerequisites
• Basic knowledge of mathematics and C++ programming as taught in the StEOP.

Mathematics prerequisites (MG1)
• Functions
• Proofs
• Induction
• Graph theory

Programming prerequisites (PR1)
• Basic C++
• Understanding the computational model for a C++ program:
– Control flow
– Function calls
– Local variables
– Loops (and related constructs)

Assessment and permitted materials

During the semester, there will be four short online exams, each lasting 45 minutes. These will be conducted via Moodle and can be taken within a fixed, almost-24-hour, window announced for each exam. Each exam is graded binary: 0 or 2 points. An on-time serious attempt earns 2 points. An attempt is said to be a serious attempt when ALL questions are attempted. There is no minimum points requirement beyond making a serious attempt to earn 2 points in a short exam. To qualify for the final exam, you must earn at least 6 out of 8 points from the short exams, i.e., seriously attempt at least 3 short exams. The short exams are scheduled as follows:

• Short Exam 1: Monday 23.03, 00:01–23:59 (Moodle, online)
• Short Exam 2: Monday 04.05, 00:01–23:59 (Moodle, online)
• Short Exam 3: Monday 01.06, 00:01–23:59 (Moodle, online)
• Short Exam 4: Monday 22.06, 00:01–23:59 (Moodle, online)

The same rules apply to the short exams and the final exam: no lecture notes, books, or other helping materials are permitted. You are not allowed to get any help from anyone in any form.

Additionally, there will be:

• 4 coding exercises on data structures and algorithm implementation (all test cases provided), each worth 2 points (total: 8 points).
• 4 written homeworks, each worth 2 points, grading is ternary (0, 1, or 2 points). We check only whether each answer represents a serious attempt, not for correctness (total: 8 points).

The written final exam is planned to be during the last lecture of the course:

• Final Exam: on 30.06 from 08:00 to 9:30 at Auditorium Maximum Tiefparterre Hauptgebäude Stiege 10.

Those who qualify for the final exam but fail the course after attempting the final exam will have a chance to appear for the retake exam. Students who do not qualify for the final or who qualify but do not show up for the final receive a failing grade and are not eligible for the retake. The retake exam is planned to be during the first week of September:

• Retake Exam: TBA (as soon as we book the rooms)

The final/retake exam is worth 76 points, and no lecture notes, books, or other helping materials are permitted. The total score for the course is 100 points.

• 8 points for the short exams
• 8 points for the coding exercises
• 8 points for the homework sheets
• 76 points for the final/retake exam

You need to score at least 38 points out of 76 in the final/retake exam to pass the course. There is also an overall scoring requirement as mentioned below.

Minimum requirements and assessment criteria

To pass the course, students must achieve all of the following:
• At least 6 out of 8 points in the short exams (requirement to be eligible for the final/retake exam).
• At least 38 out of 76 points in the final/retake exam.
• At least 50 out of 100 points overall.

Grading scale
• Grade 1: more than 88 points (> 88)
• Grade 2: more than 75 points and up to 88 points (> 75 and ≤ 88)
• Grade 3: more than 62 points and up to 75 points (> 62 and ≤ 75)
• Grade 4: at least 50 points and up to 62 points (≥ 50 and ≤ 62)
• Grade 5: less than 50 points (< 50)

Examination topics

All topics discussed in the course are examinable.

Reading list

Course textbook: Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, published by MIT Press, 2009 (3rd Edition in English, corresponds to 4th Edition in German, available online as pdf in Universitätsbibliothek).

Association in the course directory

Module: ADS UF-INF-09

Last modified: Mo 06.07.2026 10:06