Felix Friedrich Wicker: Catalogue data in Spring Semester 2020

Name	Dr. Felix Friedrich Wicker
Address	Dep. Informatik ETH Zürich, CAB H 33.3 Universitätstrasse 6 8092 Zürich SWITZERLAND
Telephone	+41 44 632 83 12
E-mail	felix.friedrich@inf.ethz.ch
Department	Computer Science
Relationship	Lecturer

Number	Title	ECTS	Hours	Lecturers
252-0002-AAL	Data Structures and Algorithms 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.	8 credits	15R	F. Friedrich Wicker
Abstract	This 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.
Learning objective	An 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++.
Content	Fundamental 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).
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. Maurice Herlihy, Nir Shavit, The Art of Multiprocessor Programming, Elsevier, 2012.
Prerequisites / Notice	Prerequisites: 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.
252-0002-00L	Data Structures and Algorithms	8 credits	4V + 2U	F. Friedrich Wicker
Abstract	This 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.
Learning objective	An 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++.
Content	Fundamental 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).
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++.
252-0216-00L	Rigorous Software Engineering	8 credits	4V + 2U + 1A	F. Friedrich Wicker, H. Lehner, M. Schwerhoff
Abstract	This course introduces both theoretical and applied aspects of software engineering and analysis. It covers: - Software Architecture - Informal and formal Modeling - Design Patterns - Code Refactoring - Program Testing - Dynamic Program Analysis - Static Program Analysis
Learning objective	The course has two main objectives: - Understand, end-to-end (theoretical and practical), the core techniques for building quality software - Understand how to apply these techniques in practice
Content	Some of the core technical topics covered will be: - modeling and mapping of models to code - common code design patterns - functional and structural testing - dynamic and static analysis
Literature	Will be announced in the lecture.
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, H. Lehner
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
252-0232-00L	Software Engineering	6 credits	2V + 1U	F. Friedrich Wicker, H. Lehner
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.
Lecture notes	no lecture notes
Literature	Will be announced in the lecture
252-0846-AAL	Computer Science II 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.	4 credits	9R	F. Friedrich Wicker, H. Lehner
Abstract	Together with the introductory course Informatics I this course provides the foundations of programming and databases. This course particularly covers algorithms and data structures and basics about design and implementation of databases. Programming language used in this course is Java.
Learning objective	Basing on the knowledge covered by lecture Informatics I, the primary educational objectives of this course are - constructive knowledge of data structures and algorithms amd - the knowledge of relational databases and When successfully attended the course, students have a good command of the mechanisms to construct an object oriented program. They know the typically used control and data structures and understand how an algorithmic problem is mapped to a sufficiently efficient computer program. They have an idea of what happens "behind the secenes" when a program is translated and executed. The know how to write database queries and how to design simple databases. Secondary goals are an algorithmic computational thinking, undestanding the possibilities and limits of programming and to impart the way of thinking of a computer scientist.
Content	We discuss the paradigm of object oriented programming, typical data structures and algorithms and design principles for the design and usage of relational databases. More generally, formal thinking and the need for abstraction and importance of appropriate modelling capabilities will be motivated. The course emphasizes applied computer science. Concrete topics are complexity of algorithms, divide and conquer-principles, recursion, sort- and search-algorithms, backtracking, data structures (lists, stacks, queues, trees) and data management in relational data bases.
Lecture notes	The slides will be available for download on the course home page.
Literature	Robert Sedgewick, Kevin Wayne, Introduction to Programming in Java: An Interdisciplinary Approach, Addison-Wesley, 2008 T. Cormen, C. Leiserson, R. Rivest, C. Stein, Introduction to Algorithms , 3rd ed., MIT Press, 2009
Prerequisites / Notice	Prerequisites are knowledge and programming experience according to course 252-0845-00 Computer Science I (D-BAUG).
252-0846-00L	Computer Science II	4 credits	2V + 2U	F. Friedrich Wicker, H. Lehner
Abstract	Together with the introductory course Informatics I this course provides the foundations of programming. This course particularly covers algorithms and data structures. Programming languages used in this course are Java and Python.
Learning objective	Basing on the knowledge covered by lecture Informatics I, the primary educational objectives of this course are constructive knowledge of data structures and algorithms. When successfully attended the course, students have a good command of the mechanisms to construct an object oriented program. They know the typically used control and data structures and understand how an algorithmic problem is mapped to a sufficiently efficient computer program. Secondary goals are an algorithmic computational thinking, undestanding the possibilities and limits of programming and to impart the way of thinking of a computer scientist.
Content	We discuss typical data structures and algorithms. More generally, formal thinking and the need for abstraction and importance of appropriate modeling capabilities will be motivated. Concrete topics are complexity of algorithms, divide and conquer-principles, recursion, sort- and search-algorithms, elementary dynamic data structures, algorithms on graphs. The concepts of the lectures will be motivated with applications. The programming languages used in the lectures and the practical exercises are Java and Python. For the exercises an online-compiler and online-submission system is used.
Lecture notes	The slides will be available for download on the course home page.
Literature	Robert Sedgewick, Kevin Wayne, Introduction to Programming in Java: An Interdisciplinary Approach, Addison-Wesley, 2008 T. Cormen, C. Leiserson, R. Rivest, C. Stein, Introduction to Algorithms , 3rd ed., MIT Press, 2009
Prerequisites / Notice	Prerequisites are knowledge and programming experience according to course 252-0845-00 Computer Science I (D-BAUG).
252-0856-AAL	Computer Science 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.	4 credits	9R	F. Friedrich Wicker, M. Schwerhoff
Abstract	The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required.
Learning objective	Primary educational objective is to learn programming with C++. After having successfully attended the course, students have a good command of the mechanisms to construct a program. They know the fundamental control and data structures and understand how an algorithmic problem is mapped to a computer program. They have an idea of what happens "behind the scenes" when a program is translated and executed. Secondary goals are an algorithmic computational thinking, understanding the possibilities and limits of programming and to impart the way of thinking like a computer scientist.
Content	The course covers fundamental data types, expressions and statements, (limits of) computer arithmetic, control statements, functions, arrays, structural types and pointers. The part on object orientation deals with classes, inheritance and polymorphism; simple dynamic data types are introduced as examples. In general, the concepts provided in the course are motivated and illustrated with algorithms and applications.
Lecture notes	English lecture notes will be provided during the semester. The lecture notes and the lecture slides will be made available for download on the course web page. Exercises are solved and submitted online.
Literature	Bjarne Stroustrup: Einführung in die Programmierung mit C++, Pearson Studium, 2010 Stephen Prata, C++ Primer Plus, Sixth Edition, Addison Wesley, 2012 Andrew Koenig and Barbara E. Moo: Accelerated C++, Addison-Wesley, 2000
Prerequisites / Notice	This virtual self-study course is also offered physically in the autumn semester. We recommend to visit the classes of the course 252-0856-00L (or that of the equivalent course 252-0847-00L). While the classes are only offered in German, there are English spoken Exercises. All exercises and exams are offered bilingual (German and English).