Course Information

Course Name	Turkish	Algoritma Mühendisliği
	English	Algorithms Engineering
Course Code	BBL 553E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Muhammed Oğuzhan Külekci Muhammed Oğuzhan Külekci
Course Objectives		1) Understanding the experimental algorithmics cycle 2) Finding the most appropriate solution for computation problems in real life 3) Learning to benefit from the features of the computing platforms 4) Understanding the differences between theory and practice of algorithms 5) Learning the fundamental techniques to make run algorithms fast in small space
Course Description		Experimental algorithms, the relation between the theory and practice of algorithms, algorithm engineering cycle, design of experiments for the performance analysis of algorithms, implementation techniques to make algorithms run fast with small memory footprint.
Course Outcomes		A student who completed this course successfully 1) will have a firm knowledge on the concept of experimental algorithmics. 2) will have a demostrable knowledge of the modelling of real life problems according to the theoretical foundations. 3) will have developed an understanding of the design of experiments and inputs for correct experimental analysis of performance. 4) will have developed an understanding of choosing the right algorithm among alternatives for a given real life problem. 5) will have a firm knowledge on the techniques to reduce instruction count in algorithm implementations. 6) will have a firm knowledge on the techniques to reduce instruction execution time in algorithm implementations. 7) will have a demonstrable knowledge of using theoretical results to solve a computational problem in the practical setting according to the available resources and requirements.
Pre-requisite(s)		Knowledge of basic algorithms and data structures Proficiency on a programming language
Required Facilities
Other
Textbook		1) McGeoch, C.C., A guide to experimental algorithmics, Cambridge University Press, 2012 2) Müller-Hannemann, M., Schirra, S., Algorithm Engineering, Springer, 2010 3) Bartz-Beielstein, T., Chiarandini, M., Paquete, L., Preuss, M., Experimental methods for the analysis of optimization algorithms, Springer, 2010 4) Kliemann, L., Sanders, P., Algorithm Engineering: Selected Results and Surveys. Springer, 2016
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