- Michael T. Goodrich, Roberto Tamassia.
Algorithm Design: Foundations, Analysis, and Internet Examples.
John Wiley & Sons, Inc., Hoboken, NJ, 2002.
- Volker Heun.
Grundlegende Algorithmen: Einführung in den Entwurf und die Analyse effizienter Algorithmen.
2nd edition, Vieweg, Braunschweig-Wiesbaden, 2003.
- Thomas H. Cormen, Charles E. Leiserson, Ronald
L. Rivest, Clifford Stein.
Introduction to Algorithms.
2nd edition, MIT Press, Cambridge, MA, 2001.
- Jon Kleinberg, Eva Tardos.
Pearson Education, Boston, MA, 2005.
- Uwe Schöning.
Spektrum Akademischer Verlag, Heidelberg, 2001.
- Robert Sedgewick.
Algorithmen in Java. Teil 1-4.
3rd, revised edition, Pearson Education, München, 2003.
Fundamentals of Algorithms and Data Structures
Dr. Hanjo Tšubig
- Module: IN0007, TUMonline
Students in Bachelor of Science in Computer Science (compulsory course)
Students in Bachelor of Science in Business Informatics (compulsory course)
Students in Bachelor of Science in Bioinformatics (compulsory course)
Students with minor subject Computer Science
Students in Master of Applied Computer Science
Students in Postgraduate Studies of Computer Science
- Time and Place:
Tuesday, 14:00–16:00, lecture hall MI HS 1
Thursday, 12:00–13:00, lecture hall MI HS 1
2 hours per week exercises accompanying the lecture
Teaching assistant: Tobias Lieber
Students in Computer Science (Bachelor of Science)
Students in Bioinformatics (Bachelor of Science)
Students in Information Systems (Bachelor of Science)
- ECTS: 6 credits
Basic knowledge in computer science
- Recommended for:
Fundamental knowledge in topic Algorithms, Bioinformatics
During the course
See here for more information.
The lectures are planned to deal in particular with the following topics:
- Basic data structures
- Advanced data structures
- Sorting and selecting
- Algorithms on graphs
- Algorithms on texts
- Data compression
- Related and advanced lectures:
Efficient algorithms and data structures
Complementary and additional in-depth material can be taken from: