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252-0002-00L 8 Credits BSC , DR , MSC D-PHYS , D-MATH , D-INFK

Data Structures and Algorithms

Datenstrukturen & Algorithmen

Lecturers & Examiners: Dr. Felix Friedrich Wicker, Dr. Manuela Fischer
VVZ CR n/a

Last Updated: 2026-06-03 00:14:30

Abstract

The course provides the foundations for the design and analysis of algorithms.Classic 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.

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, sweep-line method, 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 (e.g. amortized analysis). The relationship and tight coupling between algorithms and data structures is illustrated with geometric problems (convex hull, line intersections, closest point pairs) graph algorithms (traversals, topological sort, transitive closure, shortest paths, minimum spanning trees, max flow). Programming model of C++: correct and efficient memory handling, generic programming with templates, functional approaches with functors and lambda expressions. Parallel programming: 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). 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.

Resources

Literature

(available from the course website)

Learning Materials (Links)

General Information

Language
German
Levels
BSC , DR , MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 150 minutes
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
The exam takes place on devices provided by ETH Zurich.
Die Prüfung findet voraussichtlich in hybrider Form (auf Papier und am Computer) statt.

Course Components

Type Title Time & Place Hours
lecture Datenstrukturen & Algorithmen
  • Mon 10:15-12:00 (HG G 3)
  • Fri 08:15-10:00 (HG G 3)
4 h weekly
exercise Datenstrukturen & Algorithmen
Zusätzlich wird ein Study Center angeboten: Freitags von 12 - 14 Uhr in LFW C1.
No time listed 2 h weekly

Offered In