Algorithm Engineering [2022 Sommer]  

Code IAE 
Name Algorithm Engineering 

LP 8 
Dauer one semester 
Angebotsturnus every summer semester 
Format Lecture 4 SWS + Exercise course 2 SWS 
Arbeitsaufwand 240h; thereof 90h lectures and tutorials, 15h exam preparations, 135h lecture wrapup and homework 
Verwendbarkeit M.Sc. Angewandte Informatik M.Sc. Data and Computer Science M.Sc. Scientific Computing 
Sprache English 
Lehrende Christian Schulz 
Prüfungsschema 
Lernziele  Students obtain a systematic understanding of algorithmic questions and solution approaches in the area of algorithm engineering. The students will be able to transfer the learned techniques onto similar problems and be able to interpret and understand current research topics in the area of algorithm engineering. Given a realworld problem, students are able to select appropriate algorithms to come up with and implement efficient solutions. In particular, students know realistic machine models and applications, algorithm design, implementation techniques, experimental methodology and can interpret of measurements. 

Lerninhalte  The listed abilities will be learned by concrete examples. In particular, we will almost always cover the best practical and theoretical methods. This methods often deviate a lot by the algorithms learned in the basic courses. To this end the lecture covers FPT/Kernelization in practice (independent set, vertex cover, (all) minimum cuts (NOI algorithm), clique cover, node ordering), multilevel algorithms (graph partitioning, modularity clustering, dynamic clustering, process mapping, spectral techniques, exact approaches), route planning (contraction hierarchies, arcflags, hublabel algorithm), dynamic graph algorithms (singlesource reachability, transitive closure, matching, minimum cuts, graph generation).  
Teilnahme voraus setzungen 
recommended are: Einführung in die Praktische Informatik (IPI), Programmierkurs (IPK), Algorithmen und Datenstrukturen (IAD), Mathematik für Informatiker 1 oder Lineare Algebra 1 (MA4), Algorithms and Data Structures 2 

Vergabe der LP und Modulendnote  The module is completed with a graded oral exam. The final grade of the module is determined by the grade of the exam. The requirements for the assignment of credits follows the regulations in section modalities for exams.  
Nützliche Literatur  Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: Introduction to Algorithms, 3rd Edition. MIT Press 2009, ISBN 9780262033848, pp. IXIX, 11292 Jon M. Kleinberg, Éva Tardos: Algorithm design. AddisonWesley 2006, ISBN 9780321372918, pp. IXXIII, 1838 Stefan Näher: LEDA, a Platform for Combinatorial and Geometric Computing. Handbook of Data Structures and Applications 2004 