Department of Computer Science | Institute of Theoretical Computer Science

CADMO - Center for Algorithms, Discrete Mathematics and Optimization

Algorithms Lab (6 CP)


Prof. Angelika Steger

Prof. Emo Welzl

Prof. Peter Widmayer


Please do not send email to any of the addresses below. Instead, for questions on exercises use the forums on the course homepage. For questions on the course formalities etc., use

Jan Hazla

Dr. Michael Hoffmann

Rajko Nenadov

Thomas Rast

Rastislav Sramek

Sebastian Stich

Time & Place

First tutorial: Wednesday Sep 19, 17-19, CAB G 61

Tutorials: Wednesday, 17-19, CAB G 61

Exercises: Monday, 17-19, CAB H 56, CAB H 57

see also:

Exam review (Prüfungseinsicht): Feb 27 & Mar 7, 14:15, CAB G15.2


The objective of this course is to learn how to solve a problem given by a textual description. This includes appropriate problem modeling, choice of suitable (combinatorial) algorithms, and implementing them using C/C++, STL, CGAL, and BGL.



The exercise sessions are meant to offer a place to ask questions and get help if you lack a necessary idea to solve a problem or if you struggle with any other kind of course related problem.

Attendance to the tutorials, as well as to the exercise sessions, is not mandatory. It has to be mentioned, though, that without attending the tutorials it might be more difficult to find the solutions to the exercises given during the course. Also potentially new problem solving strategies which are crucial for your success in this course will be presented.


In this course students learn how to solve algorithmic problems given by a textual description. We assume knowledge of elementary algorithms and data structures as they are typically taught on the Bachelor level; in tutorials we introduce more advanced algorithms and the usage of some standard libraries for combinatorial algorithms. Students are expected to practice their skills by solving weekly exercises. For that they will have to understand the problem setting, find an appropriate modeling, choose suitable algorithms, and implement them using C/C++, STL, CGAL, and BGL. The evaluation of the correctness and efficiency of their solutions will be performed by an online-judge which compiles the submitted source-code and runs it on a set of test instances. The response of the judge is one of the following: correct, partially correct (meaning that the program produced the correct answer for some of the test sets, but not for all), compilation error, run-time error, time limit error, memory excedance. While the goal is, of course, to write a program that passes all test instances (that is, even those which check extreme cases), in the exam - where the same online judge is used - partial credit will be given to programs that solve at least a standard problem set.


We will hand out weekly exercises each Monday. You are expected to hand in solutions, using the online-judge, by the following Monday.

During the exercise classes, we provide help with the current exercises. For some of them, we will discuss sample solutions during the tutorial classes two weeks after the exercise was announced. There is no formal testat requirement.


The grade of the course will be solely based on the final exam. This takes place as an online-exam on two days, 6 hours each, during the examination session. On each of the two days you'll get some problems in the spirit of the weekly exercises.


1. Fundamental Algorithms (Week 1-3)

Solving elementary problems using C/C++, STL, and the algorithms and data structures listed here.

Tutorial 1: Introduction to the working environment and the submission framework (online-judge) + Basics about how to program for this lab.

Tutorial 2: Repetition of essential data structures and algorithms.

Tutorial 3: Repetition of essential data structures and algorithms.

2. Algorithms on Graphs (Week 4-7)

Tutorial 4: Introduction to BGL

Tutorial 5: Flow algorithms - theory & BGL implementation

Tutorial 6: Planar graphs - theory & BGL implementation

3. Geometric Algorithms (Week 8-10)

Tutorial 7: Introduction to CGAL

Tutorial 8: Proximity structures

4. Linear Programming (Week 11)

Tutorial 9: Linear and quadratic programming - theory & CGAL implementation

5. Mixed Problems - practice sessions (Week 12-13)

The exercises of these weeks will be in the spirit of the exam.


T. Cormen, C. Leiserson, R. Rivest:
Introduction to Algorithms, MIT Press, 1990.

J. Hromkovic, Teubner:
Theoretische Informatik, Springer, 2004 (English: Theoretical Computer Science, Springer 2003).

J. Kleinberg, É. Tardos:
Algorithm Design, Addison Wesley, 2006.

H. R. Lewis, C. H. Papadimotriou:
Elements of the Theory of Computation, Prentice Hall, 1998.

T. Ottmann, P. Widmayer:
Algorithmen und Datenstrukturen, Spektrum, 2002.

R. Sedgewick:
Algorithms in C++: Graph Algorithms, Addison-Wesley, 2001.