## Felix Friedrich Wicker: Catalogue data in Autumn Semester 2021 |

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 |

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. | ||||

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. 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++. 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. | ||||

252-0232-AAL | Software EngineeringEnrolment 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 | ||||

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. | ||||

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 | ||||

252-0846-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, R. Sasse | |

Abstract | Introduction to programming in Java. Procedural foundations of programming and outlook to object oriented programming. Variables, types, assignments, control structures (branch, loop), data structures, algorithms, line graphics, graphical user interface. Writing small programs. Working with a professional programming environment (Eclipse). | ||||

Objective | The students will be able to write simple programs and to modify existing programs. | ||||

Content | This course offers an introduction to variables, control structures (branch, loop), algorithms and data structures, as well as an outlook to modularisation and object oriented techniques. In the exercises students train programming skills (in the programming language JAVA). Students can solve the exercises on their own laptop or in the computer labs at ETH. The software used in this course runs on MS Windows, MacOS X and Linux. | ||||

Prerequisites / Notice | Prerequisites: 252-0845-00 Computer Science I (D-BAUG) | ||||

252-0847-00L | Computer Science | 5 credits | 2V + 2U | R. Sasse, F. Friedrich Wicker | |

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. | ||||

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 | ||||

252-0856-AAL | Computer Science Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 4 credits | 9R | F. Friedrich Wicker, R. Sasse | |

Abstract | Die Vorlesung bietet eine Einführung in das Programmieren mit einem Fokus auf systematischem algorithmischem Problemlösen. Lehrsprache ist C++. Es wird keine Programmiererfahrung vorausgesetzt. | ||||

Objective | Primäres Lernziel der Vorlesung ist die Befähigung zum Programmieren mit C++. Studenten beherrschen nach erfolgreichem Abschluss der Vorlesung die Mechanismen zum Erstellen eines Programms, sie kennen die fundamentalen Kontrollstrukturen, Datenstrukturen und verstehen, wie man ein algorithmisches Problem in ein Programm abbildet. Sie haben eine Vorstellung davon, was "hinter den Kulissen" passiert, wenn ein Programm übersetzt und ausgeführt wird. Sekundäre Lernziele der Vorlesung sind das Computer-basierte, algorithmische Denken, Verständnis der Möglichkeiten und der Grenzen der Programmierung und die Vermittlung der Denkart eines Computerwissenschaftlers. | ||||

Content | Wir behandeln fundamentale Datentypen, Ausdrücke und Anweisungen, (Grenzen der) Computerarithmetik, Kontrollanweisungen, Funktionen, Felder, zusammengesetze Strukturen und Zeiger. Im Teil zur Objektorientierung werden Klassen, Vererbung und Polymorhpie behandelt, es werden exemplarisch einfache dynamische Datentypen eingeführt. Die Konzepte der Vorlesung werden jeweils durch Algorithmen und Anwendungen motiviert und illustriert. | ||||

Lecture notes | Ein Skript in englischer Sprache wird semesterbegleitend herausgegeben. Das Skript und die Folien werden auf der Vorlesungshomepage zum Herunterladen bereitgestellt. | ||||

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. | ||||

252-0856-00L | Computer Science | 4 credits | 2V + 2U | F. Friedrich Wicker, R. Sasse | |

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. | ||||

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 | ||||

252-0863-00L | Engineering Tool: Advanced Programming with C++ All Engineering Tool courses are for MAVT-Bachelor students only. | 0.4 credits | 1K | F. Friedrich Wicker | |

Abstract | The programming model of C++ is discussed in some depth. In particular the mechanisms for efficient memory management and generic programming with C++ are covered. | ||||

Objective | Ability to implement memory-efficient data structures and efficient generic algorithms using C++. | ||||

Content | Vectors, pointers and iterators, range for, keyword auto, a class for vectors, subscript-operator, move-construction and iteration. RAII (Resouce Allocation is Initialization) Principle, Templates and Generic Programming, Functors and Lambda Expressions. | ||||

Lecture notes | Detailled, bilingual slides of the lectures will be made available. | ||||

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

Prerequisites / Notice | Lecture Series Informatik I 252-0832-00L or equivalent knowledge in programming with C++. Course can only be taken if the programming project is executed and submitted. If no solution to the programming project is submitted, the course is considered failed («no show»). |