252-0002-AAL  Data Structures and Algorithms

SemesterSpring Semester 2020
LecturersF. Friedrich Wicker
Periodicityevery semester recurring course
Language of instructionEnglish
CommentEnrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.


252-0002-AA RData Structures and Algorithms
Self-study course. No presence required.
210s hrsF. Friedrich Wicker

Catalogue data

AbstractThis course is about fundamental algorithm design paradigms (such as induction, divide-and-conquer, backtracking, dynamic programming), classic algorithmic problems (such as sorting and searching), and data structures (such as lists, hashing, search trees). Moreover, an introduction to parallel programming is provided. The programming model of C++ will be discussed in some depth.
ObjectiveAn understanding of the design and analysis of fundamental algorithms and data structures. Knowledge regarding chances, problems and limits of parallel and concurrent programming. Deeper insight into a modern programming model by means of the programming language C++.
ContentFundamental algorithms and data structures are presented and analyzed. Firstly, this comprises design paradigms for the development of algorithms such as induction, divide-and-conquer, backtracking and dynamic programming and classical algorithmic problems such as searching and sorting. Secondly, data structures for different purposes are presented, such as linked lists, hash tables, balanced search trees, heaps and union-find structures. The relationship and tight coupling between algorithms and data structures is illustrated with geometric problems and graph algorithms.

In the part about parallel programming, parallel architectures are discussed conceptually (multicore, vectorization, pipelining). Parallel programming concepts are presented (Amdahl's and Gustavson's laws, task/data parallelism, scheduling). Problems of concurrency are analyzed (Data races, bad interleavings, memory reordering). Process synchronisation and communication in a shared memory system is explained (mutual exclusion, semaphores, monitors, condition variables). Progress conditions are analysed (freedom from deadlock, starvation, lock- and wait-freedom). The concepts are underpinned with examples of concurrent and parallel programs and with parallel algorithms.

The programming model of C++ is discussed in some depth. The RAII (Resource Allocation is Initialization) principle will be explained. Exception handling, functors and lambda expression and generic prorgamming with templates are further examples of this part. The implementation of parallel and concurrent algorithm with C++ is also part of the exercises (e.g. threads, tasks, mutexes, condition variables, promises and futures).
LiteratureCormen, Leiserson, Rivest, and Stein: Introduction to Algorithms, 3rd ed., MIT Press, 2009. ISBN 978-0-262-03384-8 (recommended text)

B. Stroustrup, The C++ Programming Language (4th Edition) Addison-Wesley, 2013.

Maurice Herlihy, Nir Shavit, The Art of Multiprocessor Programming, Elsevier, 2012.
Prerequisites / NoticePrerequisites:
Lecture Series 252-0856-00L Computer Science or equivalent knowledge in programming with C++.

Please note that this is a self study (virtual) course, which implies that (in the autumn semester) there are no physical lectures or exercise sessions offered. If you want to attend the real course, please go to 252-0002-00L in the spring semester.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits8 credits
ExaminersF. Friedrich Wicker
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 150 minutes
Additional information on mode of examinationBy doing the weekly exercise series a bonus of maximally 0.25 of a grade point can be achieved. This bonus will be taken along to the exam. The bonus is proportional to the achieved points of specially marked bonus-task. The full number of points corresponds to a bonus of 0.25 of a grade point. The admission to the specially marked bonus tasks can depend on the successul completion of other exercise tasks. The achieved grade bonus expires as soon as the course has been given again.

The exam might be performed at a computer.
Written aidsFour A4-pages (two A4-sheets of paper), either handwritten or 11 point
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

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No information on groups available.


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Offered in

Computational Biology and Bioinformatics MasterCourse Units for Additional Admission RequirementsE-Information