Malte Schwerhoff: Catalogue data in Autumn Semester 2021

Name	Dr. Malte Schwerhoff
Address	Dep. Informatik ETH Zürich, CAB H 31.2 Universitätstrasse 6 8092 Zürich SWITZERLAND
Telephone	+41 44 632 21 08
E-mail	malte.schwerhoff@inf.ethz.ch
Department	Computer Science
Relationship	Lecturer

Number	Title	ECTS	Hours	Lecturers
252-0232-AAL	Software Engineering Enrolment 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.	6 credits	13R	F. Friedrich Wicker, M. Schwerhoff
Abstract	This course introduces both theoretical and applied aspects of software engineering. It covers: - Software Architecture - Informal and formal Modeling - Design Patterns - Software Engineering Principles - Code Refactoring - Program Testing
Learning objective	The course has two main objectives: - Obtain an end-to-end (both, theoretical and practical) understanding of the core techniques used for building quality software. - Be able to apply these techniques in practice.
Content	While the lecture will provide the theoretical foundations for the various aspects of software engineering, the students will apply those techniques in project work that will span over the whole semester - involving all aspects of software engineering, from understanding requirements over design and implementation to deployment and change requests.
Literature	Will be announced in the lecture
252-0836-00L	Computer Science II	4 credits	2V + 2U	M. Schwerhoff, F. Friedrich Wicker
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.
Learning objective	An understanding of the analysis and design of fundamental and common algorithms and data structures. 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, 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). 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). 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 introduction to graph theory.
Lecture notes	tba
Literature	Cormen, 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.
Prerequisites / Notice	Prerequisite: Computer Science I
252-0864-00L	Engineering Tool: Parallel and Concurrent Programming in C++ All Engineering Tool courses are for MAVT-Bachelor students only.	0.4 credits	1K	M. Schwerhoff
Abstract	This course provides an introduction to parallel and concurrent programming, using C++. Basic challenges and concepts will be introduced and illustrated, and applied by students in small projects.
Learning objective	Students develop a basic understanding of the advantages and pitfalls of concurrency, and gain an overview of the field and its concepts. They learn how to solve small problems using concurrent programs.
Prerequisites / Notice	The course can only be passed if the projects are executed and submitted. If no or insufficient solutions are submitted, the course is considered failed ("drop out").
252-0865-00L	Preparatory Course in Computer Science	1 credit	1P	M. Schwerhoff
Abstract	The course provides an elementary introduction to programming with C++. Prior programming experience is not required.
Learning objective	Establish an understanding of basic concepts of imperative programming and how to systematically approach programming problems. Students are able to read and write simple C++ programs.
Content	This course introduces you to the basics of programming with C++. Programming means instructing a computer to execute a series of commands that ultimately solve a particular problem. The course comprises the following: - General introduction to computer science: development, goals, fundamental concepts - Interactive self-study tutorial that provides an introduction to C++ and covers the following topics: variables, data types, conditional statements and loops - Introduction to stepwise refinement as an approach to systematically solving programming problems - Two small programming projects, to practically apply the studied fundamentals
Lecture notes	All teaching material is available online; an online development environment is used for the the programmig projects.