252-0002-00L Data Structures and Algorithms
| Semester | Spring Semester 2021 |
| Lecturers | F. Friedrich Wicker |
| Periodicity | yearly recurring course |
| Language of instruction | German |
Courses
| Number | Title | Hours | Lecturers | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 252-0002-00 V | Datenstrukturen & Algorithmen | 4 hrs |
| F. Friedrich Wicker | ||||||||||||||||||
| 252-0002-00 U | Datenstrukturen & Algorithmen | 2 hrs |
| F. Friedrich Wicker |
Catalogue data
| Abstract | The course provides the foundations for the design and analysis of algorithms. Classical problems ranging from sorting up to problems on graphs are used to discuss common data structures, algorithms and algorithm design paradigms. The course also comprises an introduction to parallel and concurrent programming and the programming model of C++ is discussed in some depth. |
| Learning objective | An understanding of the analysis and design of fundamental and common algorithms and data structures. Deeper insight into a modern programming model by means of the programming language C++. Knowledge regarding chances, problems and limits of parallel and concurrent programming. |
| Content | Data structures and algorithms: mathematical tools for the analysis of algorithms (asymptotic function growth, recurrence equations, recurrence trees), informal proofs of algorithm correctness (invariants and code transformation), design paradigms for the development of algorithms (induction, divide-and-conquer, backtracking and dynamic programming), classical algorithmic problems (searching, selection and sorting), data structures for different purposes (linked lists, hash tables, balanced search trees, quad trees, heaps, union-find), further tools for runtime analysis (generating functions, amortized analysis. The relationship and tight coupling between algorithms and data structures is illustrated with graph algorithms (traversals, topological sort, closure, shortest paths, minimum spanning trees, max flow). Programming model of C++: correct and efficient memory handling, generic programming with templates, exception handling, functional approaches with functors and lambda expressions. Parallel programming: structure of parallel architectures (multicore, vectorization, pipelining) concepts of parallel programming (Amdahl's and Gustavson's laws, task/data parallelism, scheduling), problems of concurrency (data races, bad interleavings, memory reordering), process synchronisation and communication in a shared memory system (mutual exclusion, semaphores, monitors, condition variables), progress conditions (freedom from deadlock, starvation, lock- and wait-freedom). The concepts are underpinned with examples of concurrent and parallel programs and with parallel algorithms, implemented in C++. In general, the concepts provided in the course are motivated and illustrated with practically relevant algorithms and applications. Exercises are carried out in Code-Expert, an online IDE and exercise management system. All required mathematical tools above high school level are covered, including a basic introduction to graph theory. |
| Literature | Cormen, Leiserson, Rivest, and Stein: Introduction to Algorithms, 3rd ed., MIT Press, 2009. ISBN 978-0-262-03384-8 (recommended text) Maurice Herlihy, Nir Shavit, The Art of Multiprocessor Programming, Elsevier, 2012. B. Stroustrup, The C++ Programming Language (4th Edition) Addison-Wesley, 2013. |
| Prerequisites / Notice | Prerequisites: Lecture Series 252-0835-00L Informatik I or equivalent knowledge in programming with C++. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| In examination block for | Bachelor's Degree Programme in Computational Science and Engineering 2016; Version 27.03.2018 (First Year Examination Block 2) Bachelor's Degree Programme in Computational Science and Engineering 2018; Version 13.12.2022 (First Year Examination Block 2) Bachelor's Programme in Computational Science and Engineering 2012; Version 13.12.2016 (Examination Block) |
| ECTS credits | 8 credits |
| Examiners | F. Friedrich Wicker |
| Type | session examination |
| Language of examination | German |
| Repetition | The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit. |
| Mode of examination | written 150 minutes |
| Additional information on mode of examination | Durch Bearbeitung der wöchentlichen Übungsserien kann ein Bonus von maximal 0.25 Notenpunkten erarbeitet werden, der an die Prüfung mitgenommen wird. Der Bonus ist proportional zur erreichten Punktzahl von speziell markierten Bonus-Aufgaben, wobei volle Punktzahl einem Bonus von 0.25 entspricht. Die Zulassung zu speziell markierten Bonusaufgaben kann von der erfolgreichen Absolvierung anderer Übungsaufgaben abhängen. Der erreichte Notenbonus verfällt, sobald die Vorlesung neu gelesen wird. Die Prüfung findet voraussichtlich in hybrider Form (auf Papier und am Computer) statt. |
| Written aids | Sie dürfen maximal 4 A4-Blätter mit in die Prüfung nehmen. Inhaltliche und formale Anforderungen (Text, Bilder, ein-/doppelseitig, Ränder, Schriftgrösse, etc.) bestehen nicht. Elektronische Geräte bzw. digitale Unterlagen sind nicht erlaubt. |
| Digital exam | The exam takes place on devices provided by ETH Zurich. |
| Distance examination | It is not possible to take a distance examination. |
| If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block. This information can be updated until the beginning of the semester; information on the examination timetable is binding. | |
Learning materials
| Main link | Webseite zur Vorlesung |
| Only public learning materials are listed. | |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
