Semester  
Module #  INFALG05 
Event #  INFALG009, INFALG010 
Programmes  Master Informatik, Master Wirtschaftsinformatik 
IBR Group  ALG (Prof. Fekete) 
Type  Vorlesung/Übung 
Lecturer  Dr. Victor Alvarez Ehemaliger Wissenschaftlicher Mitarbeiter 
Assistant  Dr. Victor Alvarez Ehemaliger Wissenschaftlicher Mitarbeiter 
Credits  5 
Hours  2+1+1 
Time & Place  Lecture: Wednesday, 13:15  14:45 hrs., PK 3.1 Tutorial: Tuesdays, 15:00  16:30 hrs., IZ 161, biweekly Small Tutorial: Tuesdays, 15:00  16:30 hrs., IZ 161, biweekly. 
Start  First Lecture: Wednesday, 13.04.2016 First Tutorial: Tuesday, 26.04.2016 First Small Tutorial: Tuesday, 03.05.2016 
Prerequisites  Basic knowledge of analysis of Algorithms and Data Structures (AuD), and Graph Algorithms (NWA). Elementary knowledge of probability is useful but not required. 
Language  English 
Certificates  Homework assignments during the semester (=Studienleistung) and one exam at the end. 
Content  Algorithm Engineering has recently emerged as an interesting field of research. Traditionally, an algorithm is regarded efficient whenever its running time is polynomial in its input size (polynomialtime algorithm). Furthermore, when speaking about running times of algorithms, we tend to speak in terms of Onotation — which not only ignores lowerdegree terms, but also ignores the constants preceding the terms. This situations tend to produce certain degree of doubt among practitioners as they cannot be sure whether a (theoretical) algorithm is usable at all in practice. This discrepancy produces a gap between theory and practice that Algorithm Engineering tries to bridge by designing algorithms that indeed exhibit fast execution times, but for which theoretical guarantees regarding performance can be proven. That is, Algorithm Engineering lives at the amazing intersection between Theoretical and Practical Computer Science. In this course we will cover topics regarding:

References  The course will be mostly based on recent research papers. All references will be given at the appropriate time. However, the following two books are excellent references about Algorithm Engineering:

General Information
