Contents

• foundations of computability:
  • universal register machines
  • syntax and operational semantics of imperative programming languages
• formal methods for the specification and verification of imperative programs:
  • assertions,
  • Hoare-calculus, partial correctness, termination
• imperative and object-oriented programming concepts (Java):
  • primitive and composite data types,
  • methords (procedures and functions). calling conventions, overloading
  • modules, classes, objects
  • class hierarchies, inheritance, polymorphism
  • abstract classes, interfaces
• programming methods:
  • stepwise refinement
  • divide and conquer
  • backtracking
• analysis of time and space requirements:
  • O-notation
  • recursion and iteration
  • analysis of algorithms for sorting and searching
  • algorithms, data structures, data abstraction

• Concepts of Programming Languages, Robert Sebesta, Pearson Education , 10th Edition, 2012, ISBN: 0131395319
• Data Structures & Problem Solving Using Java, Mark Allen Weiss, Addison Wesley, 4. Auflage, 2010, ISBN: 0-321-54140-5
• Cormen, Leiserson, Rivest: Introduction to Algorithms, 3. Auflage 2009,
• Bundle of algorithms in java, third edition, parts 1-5. Sedgewick Robert und Michael Schidlowsky. Addison-Wesley Longman, Amsterdam. 2003.

Prerequisites

background as taught in the class "Functional Programming".

Please also sign up for the class in our KVV.

Website: https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/summer_term_2019/alp4.html

The first lecture will take place Monday, 08th of April 2018 at 2pm ct.

Contents:

Programming and synchronization of concurrent processes that share resources or interact through message passing.

• Non-Sequential programs and processes in their various forms, non-determinism, determinism
• Synchronization mechanisms: locks, monitors, guards, events, semaphores
• Non-Sequential program execution and object oriented systems
• Control flow, strategies selection, priorities, handling and avoiding deadlock
• Coroutines implementation, 
• - Multiprocessor systems
• Programming and Synchronisation of concurrent processes that interact through message passing
• Remote Calling Techniques
• Client-server, Peer-to-peer Networks
• Parallel computing over networks
• Concurrent and coordination languages
• Processing on the server and on the client.
• Middleware, structured communication, static and dynamic interfaces
• Event-based and stream-based processing
• Security of network applications
• Non-functional Aspects (time, memory, quality of service)

Literatur:

• Principles of Concurrent and Distributed Programming. M. Ben-Ari. Addison-Wesley. 
• Distributed Systems. Concepts and Design. Fifth Edition. George Coulouris, Jean Dollimore, Tim Kindberg, Gordon Blair. Pearson.

Website: https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/summer_term_2019/alp4.html

The first lecture will take place Monday, 08th of April 2018 at 2pm ct.

Contents:

Programming and synchronization of concurrent processes that share resources or interact through message passing.

• Non-Sequential programs and processes in their various forms, non-determinism, determinism
• Synchronization mechanisms: locks, monitors, guards, events, semaphores
• Non-Sequential program execution and object oriented systems
• Control flow, strategies selection, priorities, handling and avoiding deadlock
• Coroutines implementation, 
• - Multiprocessor systems
• Programming and Synchronisation of concurrent processes that interact through message passing
• Remote Calling Techniques
• Client-server, Peer-to-peer Networks
• Parallel computing over networks
• Concurrent and coordination languages
• Processing on the server and on the client.
• Middleware, structured communication, static and dynamic interfaces
• Event-based and stream-based processing
• Security of network applications
• Non-functional Aspects (time, memory, quality of service)

Literatur:

• Principles of Concurrent and Distributed Programming. M. Ben-Ari. Addison-Wesley. 
• Distributed Systems. Concepts and Design. Fifth Edition. George Coulouris, Jean Dollimore, Tim Kindberg, Gordon Blair. Pearson.

The module operating and communication systems closes the gap between the hardware of a computer and the applications.

We will cover the following topics::

• I/O systems
• DMA/PIO
• Interrupt handling
• Buffers
• Processes/threads
• Virtual memory
• UNIX and Windows
• Shells
• Utilities
• Peripherals and networking
• Networks
• Media
• Media access
• Protocols
• Reference models
• TCP/IP
• The Internet

• Andrew S. Tanenbaum: Computerarchitektur, 5.Auflage, Pearson Studium, 2006
• English: Andrew S. Tanenbaum (with contributions from James R. Goodman):
• Structured Computer Organization, 4th Ed., Prentice Hall International, 2005.

Begleitveranstaltung zur Vorlesung 19300701

The module “Grundlagen der Technischen Informatik” build the basis of understanding the operation mode of real computer systems. Starting with the logic, this module will focus on combinatorial circuits and sequential circuits, logic minimization, gates, flip-flops, memory, automatic and simple hardware design. Furthermore, basic knowledge in the areas of direct and alternating current networks, semiconductors, transistors, CMOS, operational amplifiers, A/D and D/A converters are taught, as far as they are necessary for the computer science.  The corresponding “Praktikum”amplifys with numerous practical tests the content learned in the lecture and the module "Rechnerarchitektur, Betriebs- und Kommunikationssysteme". Based on a simple hardware platform with a processor and several interfaces to, the participants learn to program basic driver to enhance operating system routines and to drive the interfaces. Subsequently, the systems should be networked and be able to interact with their environment.

Siehe Unterlagen auf der Webseite - nur aus dem FB-Netz oder über VPN Webseite
Seminar am PC Dienstag, 12-16 Uhr Takustraße 9, Raum K63
 

Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented. It runs in parallel to the integrated course Parallel Programming. Both complement each other and form the module Parallel Systems.

• Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
• Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
• Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
• Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
• Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

Target group

• Computer Science Master students

Requirements

• Experience with computers and software as well as programing skills.

Language

• The course language is German (or English if requested).
• The exam will be formulated in German, but answers may be given in English, too.

Credits & Exams

The criteria for gaining credits are

• active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
• passing of the exam

Website

https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

In this lecture, we will focus on the Internet core and the deployment of its applications. We will introduce methods to measure and assess network protocols and network architectures. The topics of this lectures are embedded in a practical context. For exmaple, we will discuss how the current peering ecosystem works and why it is challenging to measure it. You will better understand how to quantify the deployment of common and upcoming protocols (e.g., IPv6, DNSSEc, HTTP/2). We will also discuss how to process large-scale Intenret data sets efficiently.

In addition to the lecture, we will offer lab exercises. In these exercises, you will conduct your own measurements and analyze existing data sets.

We plan to visit a data centre.

,

Audience: All students who want to gain a better understanding of the Internet and its applications.

Requirements: Good understanding of computer networks and communication systems.

Topics: measurements, network protocols, network architectures, network security

Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented. It runs in parallel to the integrated course Parallel Programming. Both complement each other and form the module Parallel Systems.

• Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
• Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
• Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
• Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
• Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

Target group

• Computer Science Master students

Requirements

• Experience with computers and software as well as programing skills.

Language

• The course language is German (or English if requested).
• The exam will be formulated in German, but answers may be given in English, too.

Credits & Exams

The criteria for gaining credits are

• active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
• passing of the exam

Website

https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

In this lecture, we will focus on the Internet core and the deployment of its applications. We will introduce methods to measure and assess network protocols and network architectures. The topics of this lectures are embedded in a practical context. For exmaple, we will discuss how the current peering ecosystem works and why it is challenging to measure it. You will better understand how to quantify the deployment of common and upcoming protocols (e.g., IPv6, DNSSEc, HTTP/2). We will also discuss how to process large-scale Intenret data sets efficiently.

In addition to the lecture, we will offer lab exercises. In these exercises, you will conduct your own measurements and analyze existing data sets.

We plan to visit a data centre.

,

Audience: All students who want to gain a better understanding of the Internet and its applications.

Requirements: Good understanding of computer networks and communication systems.

Topics: measurements, network protocols, network architectures, network security

Contents:

• models of computation
  • automata
  • formal languates
  • grammars and the Chomsky-hierarchy
  • Turing-machines
  • computabilty
• introduction to the complexity of computational problems

• Uwe Schöning, Theoretische Informatik kurzgefasst, 5. Auflage, Spektrum Akademischer Verlag, 2008
• John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman, Einführung in die Automatentheorie, Formale Sprachen und Komplexität, Pearson Studium, 3. Auflage, 2011
• Ingo Wegener: Theoretische Informatik - Eine algorithmenorientierte Einführung, 2. Auflage, Teubner, 1999
• Michael Sipser, Introduction to the Theory of Computation, 2nd ed., Thomson Course Technology, 2006
• Wegener, Kompendium theoretische Informatik - Eine Ideensammlung, Teubner 1996

Contents

The proseminar delves more deeply into topics covered in the basic classes taught by the theory group. During the winter semester, we consider advanced topics from the theory of computability and of formal languates (in continuation of "Theory of Computation"); during the summer semester, we talk about algorithms (in continuation of "Algorithms, Data Structures, and Data Abstraction").

Prerequisites

two semesters of computer science, successful completion of "Theory of Computation"

wird mit der Ankündigung bekannt gegeben

During this pro-seminar we will discuss current and relevant topics from the field of practical IT security. The seminar is for undergraduate students, who want to gain initial experience with IT security. Topics will cover among other things hardware security, mobile security, and classical cryptography.

The goal of the seminar is to familiarize oneself with one topic of practical IT security, process this topic scientifically, and finally give a talk about the chosen topic.

After that, an approximately five page long paper must be written, due at the end of the semester.

Topic assignment will be completed at the pre-meeting during the first lecture week.

Literaturhinweise erfolgen während des Vorbesprechungstermins.

The proseminar is aimed at all students who are interested in computer science in education. The aim of the seminar is an introduction to various topics of informatics education and to gaining insight into the related research. Therefore, the participants will scientifically prepare and present various topics of informatics education and related research.

Organizational information:

• Each student will deal specifically with a selected topic and present it as a talk followed by a discussion in the seminar.
• In addition, a written elaboration on the topic is required.
• Knowledge in the basic subjects of computer science is required. However, there is no need for any specific prior knowledge, especially in the field of education.
• The seminar topics and references will be announced and distributed in the first meeting.

Content

Database design with ERM/ERDD. Theoretical foundations of relational database systems: relational algebra, functional dependencies, normal forms. Relational database development: SQL data definitions, foreign keys and other integrity constraints, SQL as applicable language: essential language elements, embedding in programming language. Application programming; object-relational mapping. Security and protection concepts. Transaction subject, transactional guaranties, synchronization of multi user operations, fault tolerance features. Application and new developments: data warehousing, data mining, OLAP.

Project: the topics are deepened in an implementation project for student groups.

• Alfons Kemper, Andre Eickler: Datenbanksysteme - Eine Einführung, 5. Auflage, Oldenbourg 2004
• R. Elmasri, S. Navathe: Grundlagen von Datenbanksystemen, Pearson Studium, 2005

Requirements

• ALP 1 - Functional Programming
• ALP 2 - Object-oriented Programming
• ALP 3 - Data structures and data abstractions
• OR Informatik B

Contents

We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

Prerequsitions

Basic knowledge in design and anaylsis of algorithms.

je nach Anwendungsgebiet

Description:

Different software modules of the autonomous vehicle of the Freie Univeristät Berlin will be developed or improved in this software project. Therefore there will be a variety of subtopics from the robotics and autonomous driving field – with focus on computer vision, sensory data processing, world modeling, trajectory planing and control. While achieving those tasks the students will gather knowledge of different areas, learn to collaborate within a team of developers and how to develop good software. Further information about our autonomous car project can be found here: http://www.autonomos-labs.de/

Wird noch bekannt gegeben

Target group:

Masterstudents (Bachelorstudents from the fifth semester)

Prerequisites:

Knowledge in C/C++, git

Programming for Internet Communication Along the Stack

In this course, students will develop solutions that relate to Internet communication. We will consider all aspects of the Internet ecosystem, including lower layers up to the application layer for the current Internet as well as the Internet of Things. Participants will work in smaller groups (3-4 students), where each group will focus on a specific builing block. This will allow to adapt to interests and expertises (e.g., web vs. embedded system programming).

Note that we intend to use the results of this software project to revamp the old super computers in the entrance area of the CS building (i.e., the PDP 11 and the Russian clone). We will extend both computers by network-capabale devices, sensors, screens, and your software (a) to demonstrate the Internet of Things and (b) to give insights into the current state of the Internet backbone.

Below you find some initial topics, which we will clarify during the first meeting.

Embedded / IoT Programming

You will develop applications for embedded devices. The software base is the open source operating system RIOT.

Internet Backbone Measurements

You will develop applications that process live BGP data and check if an attack is happening. The software base is the RTRlib and BGPMON/BGPStream.

Web Interface

You will develop a web interfaces that shows the state of the super computers to remote participants. Your web frontend should be suitable for mobile devices.

If you have questions in advance, feel free to contact Matthias Wählisch.

• A. S. Tanenbaum, Modern Operating Systems, 3rd ed. Upper Saddle River, NJ, USA: Prentice Hall Press, 2007.
• Shelby, Zach, and Carsten Bormann. 6LoWPAN: The wireless embedded Internet. Vol. 43. Wiley. com, 2011.
• A. Dunkels, B. Gronvall, and T. Voigt, "Contiki - a lightweight and flexible operating system for tiny networked sensors." in LCN. IEEE Computer Society, 2004, pp. 455-462.
• P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, and D. Culler, "TinyOS: An Operating System for Sensor Networks," in Ambient Intelligence, W. Weber, J. M. Rabaey, and E. Aarts, Eds. Berlin/Heidelberg: Springer-Verlag, 2005, ch. 7, pp. 115-148.
• Oliver Hahm, Emmanuel Baccelli, Mesut Günes, Matthias Wählisch, Thomas C. Schmidt, "RIOT OS: Towards an OS for the Internet of Things," in Proceedings of the 32nd IEEE International Conference on Computer Communications (INFOCOM), Poster Session, April 2013.
• M.R. Palattella, N. Accettura, X. Vilajosana, T. Watteyne, L.A. Grieco, G. Boggia and M. Dohler, "Standardized Protocol Stack For The Internet Of (Important) Things", IEEE Communications Surveys and Tutorials, December 2012.
• J. Wiegelmann, Softwareentwicklung in C für Mikroprozessoren und Mikrocontroller, Hüthig, 2009

In this course you will be expected to write code. The outcome of your software project should be a concrete contribution to the RIOT code base, and take the shape of one or more pull request(s) to the RIOT github (https://github.com/RIOT-OS/RIOT). Before you start coding, refer to the starting guide

https://github.com/RIOT-OS/RIOT/wiki#wiki-start-the-riot

Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

Corporate Semantic Web

Further information can be found on the course website

Content

Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

Wird bekannt gegeben

Requirement

ALP I-V, Foundations of Datenbase Systems, good programming knowledge.

Students are introduced to the basics of Free/Libre Open Source Software (FLOSS) projects and can gain practical experience by participating in existing projects such as Wikidata. There will be an introductory event on Free/Libre Open Source Software. We will introduce the FLOSS communities of the cooperation partners and discuss their organizational practices. Students are introduced to existing FLOSS projects and gain insights into the requirements of distributed software development projects.

In the software project, we go through all phases of a user-centered software development project, from the identification of requirements in interviews through the interaction design of the user interface to the development in two-week iterations and the execution of user tests with a focus on usability. The developed solutions will be based on open source technologies and published under a free license. Through project-related learning, the participants can expand their communication skills, solve problems/tasks in a complex environment and develop their technical skills.

The tasks of the students within the project include:

- Coordinate the project idea together with the cooperation partner and plan the further course of the project.

- Collect and prepare requirements together with potential users

- Design, implementation, and testing of the software

- Organization and execution of presentations

- Documentation of the project results

Of course, the participants do not remain alone during the implementation of the software project. In the weekly meetings, we are available as consultants, mentors and (mediators). Besides, we will impart all the necessary methods and competencies if necessary.

Selbständige Erschließung von Literatur (Artikel, Internet)

Empfehlungen:

•    Fogel, Karl: Producing open source software, Sebastapol: O'Reilly 2006. http://shop.oreilly.com/product/9780596007591.do

•    Gacek, Cristina & B. Arief (2004): The Many Meanings of Open Source, IEEE Software 21(1), 34-40. https://ieeexplore.ieee.org/abstract/document/1259206/

•    Raymond, E.S. (1998): The Cathedral and the Bazaar, First Monday 3(3). https://firstmonday.org/article/view/578/499

Content

In this software project we will develop new ideas and necessary features for the MVS and KVV systems in the form of new tools/components/modules. After a seminar-style introduction to the necessary technologies, we will specify the requirements and design solutions and then develop them. Good teamwork is required. The possibilities for improving both systems are varied and range from infrastucture to usability. There will be weekly meetings during the semester, at which teams will report on progress and discuss solutions.

Inhalt:

Digitale Technologien erleichtern Reporter*innen und Journalist*innen weltweit die Recherche, Berichterstattung und Veröffentlichung. Doch zunehmend wird die Presse- und Berichtserstattung eingeschränkt und die Überwachung im digitalen Raum nimmt zu. In Berlin bieten Reporter ohne Grenzen Schulungen in IT-Sicherheit für Journalist*innen und Reporter*innen aus Krisenregionen an [1]. Es werden dabei Gefahrenmodelle entwickelt, technische Hintergründe dargestellt und neue technische Möglichkeiten (z.B. Verschlüsselungsprogramme) vorgestellt.
Wir bieten dazu im Sommersemester ein Softwareprojekt für Studierende aus der Informatik an. In diesem Softwareprojekt sollen Programme für Journalisten verbessert oder entwickelt werden. Dies erfolgt in Kooperation mit den Stipendiat*innen der Schulung und Reportern ohne Grenzen.
Aufbauend auf den Gefahrenmodell der Stipendiat*innen und durch Interviews und Fokusgruppen sollen Verbesserungen von bestehenden Programmen oder Vorschläge für neue Programme konzipiert werden. Diese sollen dann auf die Umsetzbarkeit evaluiert werden und anschließend implementiert werden. Die Ergebnisse werden den Stipendiat*innen präsentiert.

Der Fokus liegt auf der (Weiter-)Entwicklung von Browser-PlugIns [2]. Alternativ kann auch der Mailclient Letterbox (für iOS und in der Programmiersprache SWIFT) für spezielle Bedürfnisse von Journalistinnen und Journalisten angepasst werden [3]. 

Die Veranstaltung umfasst einige Einführungstermine zu dem Thema (April/Mai). Das eigentliche Softwareprojekt findet in der vorlesungsfreien Zeit (August/September) statt. Eine Auflistung der Termine ist unten angeführt!
Es besteht die Möglichkeit im Anschluss an das Softwareprojekt eine Abschlussarbeit in dem Kontext anzufertigen.
 

[1] https://www.reporter-ohne-grenzen.de/hilfe-schutz/stipendien/berliner-stipendienprogramm/
[2] https://developer.mozilla.org/en-US/docs/Mozilla/Add-ons/WebExtensions

[3] https://userpage.fu-berlin.de/letterbox/

Voraussetzungen:

Kenntnisse in:

• JavaScript/Browser Extensions oder die Motivations zur selbstständigen Einarbeitung
• Oder Kenntnisse in Swift
• Softwaretechnik

Interesse an:

• Benutzerfreundlichkeit, IT-Sicherheit
• Git-Versionskontrolle
• Bereitschaft zur Open-Source-Entwicklung
• Bereitschaft zur Durchführung von Interviews oder Fokusgruppen

Termine:

• 12. April 14 Uhr: Vorstellung vom Softwareprojekt und Einführung
• 26. April 14 Uhr: Vorbereitung Fokusgruppen und Interviews
• 3. Mai 14 Uhr: Vorbereitung Fokusgruppen und Interviews
• 10. Mai 14 Uhr: Einführung in Browser-PlugIns
• 31. Mai: Treffen mit Stipendiat*innen bei Reportern ohne Grenzen
• Kalenderwoche 31 - 37: Entwicklung eines Browser-PlugIns
• Kalenderwoche 35: Abschlusspräsentation bei ROG
• Kalenderwoche 37: Veröffentlichung des PlugIns

Programming for Internet Communication Along the Stack

In this course, students will develop solutions that relate to Internet communication. We will consider all aspects of the Internet ecosystem, including lower layers up to the application layer for the current Internet as well as the Internet of Things. Participants will work in smaller groups (3-4 students), where each group will focus on a specific builing block. This will allow to adapt to interests and expertises (e.g., web vs. embedded system programming).

Note that we intend to use the results of this software project to revamp the old super computers in the entrance area of the CS building (i.e., the PDP 11 and the Russian clone). We will extend both computers by network-capabale devices, sensors, screens, and your software (a) to demonstrate the Internet of Things and (b) to give insights into the current state of the Internet backbone.

Below you find some initial topics, which we will clarify during the first meeting.

Embedded / IoT Programming

You will develop applications for embedded devices. The software base is the open source operating system RIOT.

Internet Backbone Measurements

You will develop applications that process live BGP data and check if an attack is happening. The software base is the RTRlib and BGPMON/BGPStream.

Web Interface

You will develop a web interfaces that shows the state of the super computers to remote participants. Your web frontend should be suitable for mobile devices.

If you have questions in advance, feel free to contact Matthias Wählisch.

Automated methods for the recognition and analysis of behavior have been increasingly used to investigate individual and collective animal behavior. This includes applications such as tracking individuals in large groups (humans in crowds, animals in herds/swarms/flocks, cars in traffic), mapping observations of an individual to a behavioral space ("what is person X doing"), and learning about the structure of social interactions ("who is doing what with whom"). Recent methods allow processing large amounts of data resulting in surprisingly accurate results. We will look at a variety of supervised and unsupervised approaches with examples from our own research.

,,

,,

The lecture held by Dr. Andreas Wolf (from the Bundesdruckerei) He will give a broad overview of biometric processes and applications. He will also address the current issues with ePassports and new electronic identity cards.

The course aims to include:

• General structure of biometric systems
• Features of biometric modalities
• IT security and risk assessment
• Errors in biometric processes
• Fingerprinting
• Facial and iris recognition
• Speaker recognition and other modalities
• Standards
• ePassport

Next to the theoretical foundations of biometric modalities, the students are to develop the ability to assess the applicability of biometrics in various scenarios.

Bote classes begin on Friday, 12.4.2019.

Class PDFs under: https://drive.google.com/open?id=0B7NhYbv9QewkRkk2WVRuM2Rqd00

Nowadays is in private as well as in corporate context not the question if software will be used, it is of more importance, for which to choose. In this process is the usability dimension not an explicit requirement even if it has a high impact on the decision. A good usability and a positive user experience can only be achieved if their request, hidden desires and cognitive abilities are acquired and understood. Therefore is not only the choice of the "right" technology and "right" approach important, the factor users and their needs are fundamentally for the products success. But usability is neither an inherent feature nor can be developed at a certain point of time like a software feature. It has to be always regarded in a specific user context and this context has to be clearly understood in order to improve the usability. Furthermore has into the whole development process be intervened and according to the phase the appropriate principle and method be chosen. The goal will be, even which its complex functionality and overwhelming information, to achieve a high usability for the target user group. Hereby will be a positive user experience achieved by regarding emotional as well as aesthetic factors.

Shneiderman, Ben et al.: Designing the user interface: strategies for effective human-computer interaction. Pearson 2018.

Dix, Alan, J. Finlay, G.D. Abowd, R. Beale: Human-Computer Interaction. Pearson Prentice Hall 2004.

Sharp, Helen, Y. Rogers and J. Preece: Interaction design: beyond human-computer interaction. Wiley 2007.

https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/summer_term_2019/user-centered-design.html

Übung User-Centred Design

Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented. It runs in parallel to the integrated course Parallel Programming. Both complement each other and form the module Parallel Systems.

• Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
• Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
• Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
• Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
• Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

Target group

• Computer Science Master students

Requirements

• Experience with computers and software as well as programing skills.

Language

• The course language is German (or English if requested).
• The exam will be formulated in German, but answers may be given in English, too.

Credits & Exams

The criteria for gaining credits are

• active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
• passing of the exam

Website

https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

In this lecture, we will focus on the Internet core and the deployment of its applications. We will introduce methods to measure and assess network protocols and network architectures. The topics of this lectures are embedded in a practical context. For exmaple, we will discuss how the current peering ecosystem works and why it is challenging to measure it. You will better understand how to quantify the deployment of common and upcoming protocols (e.g., IPv6, DNSSEc, HTTP/2). We will also discuss how to process large-scale Intenret data sets efficiently.

In addition to the lecture, we will offer lab exercises. In these exercises, you will conduct your own measurements and analyze existing data sets.

We plan to visit a data centre.

,

Audience: All students who want to gain a better understanding of the Internet and its applications.

Requirements: Good understanding of computer networks and communication systems.

Topics: measurements, network protocols, network architectures, network security

In recent years, deep neural networks have become the state-of-the-art solution for a multitude of tasks in computer vision, natural language processing and robotics. In the lecture we will introduce essential concepts such as convolutional neural networks, recurrent neural networks, generative models and deep reinforcement learning. The lectures will be accompanied by practical assignments using modern deep learning frameworks such as Tensorflow and PyTorch.

http://www.deeplearningbook.org/

Übungen siehe 19329402

The lecture held by Dr. Andreas Wolf (from the Bundesdruckerei) He will give a broad overview of biometric processes and applications. He will also address the current issues with ePassports and new electronic identity cards.

The course aims to include:

• General structure of biometric systems
• Features of biometric modalities
• IT security and risk assessment
• Errors in biometric processes
• Fingerprinting
• Facial and iris recognition
• Speaker recognition and other modalities
• Standards
• ePassport

Next to the theoretical foundations of biometric modalities, the students are to develop the ability to assess the applicability of biometrics in various scenarios.

Bote classes begin on Friday, 12.4.2019.

Class PDFs under: https://drive.google.com/open?id=0B7NhYbv9QewkRkk2WVRuM2Rqd00

Nowadays is in private as well as in corporate context not the question if software will be used, it is of more importance, for which to choose. In this process is the usability dimension not an explicit requirement even if it has a high impact on the decision. A good usability and a positive user experience can only be achieved if their request, hidden desires and cognitive abilities are acquired and understood. Therefore is not only the choice of the "right" technology and "right" approach important, the factor users and their needs are fundamentally for the products success. But usability is neither an inherent feature nor can be developed at a certain point of time like a software feature. It has to be always regarded in a specific user context and this context has to be clearly understood in order to improve the usability. Furthermore has into the whole development process be intervened and according to the phase the appropriate principle and method be chosen. The goal will be, even which its complex functionality and overwhelming information, to achieve a high usability for the target user group. Hereby will be a positive user experience achieved by regarding emotional as well as aesthetic factors.

Shneiderman, Ben et al.: Designing the user interface: strategies for effective human-computer interaction. Pearson 2018.

Dix, Alan, J. Finlay, G.D. Abowd, R. Beale: Human-Computer Interaction. Pearson Prentice Hall 2004.

Sharp, Helen, Y. Rogers and J. Preece: Interaction design: beyond human-computer interaction. Wiley 2007.

https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/summer_term_2019/user-centered-design.html

Übung User-Centred Design

Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented. It runs in parallel to the integrated course Parallel Programming. Both complement each other and form the module Parallel Systems.

• Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
• Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
• Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
• Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
• Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

Target group

• Computer Science Master students

Requirements

• Experience with computers and software as well as programing skills.

Language

• The course language is German (or English if requested).
• The exam will be formulated in German, but answers may be given in English, too.

Credits & Exams

The criteria for gaining credits are

• active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
• passing of the exam

Website

https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

In this lecture, we will focus on the Internet core and the deployment of its applications. We will introduce methods to measure and assess network protocols and network architectures. The topics of this lectures are embedded in a practical context. For exmaple, we will discuss how the current peering ecosystem works and why it is challenging to measure it. You will better understand how to quantify the deployment of common and upcoming protocols (e.g., IPv6, DNSSEc, HTTP/2). We will also discuss how to process large-scale Intenret data sets efficiently.

In addition to the lecture, we will offer lab exercises. In these exercises, you will conduct your own measurements and analyze existing data sets.

We plan to visit a data centre.

,

Audience: All students who want to gain a better understanding of the Internet and its applications.

Requirements: Good understanding of computer networks and communication systems.

Topics: measurements, network protocols, network architectures, network security

In recent years, deep neural networks have become the state-of-the-art solution for a multitude of tasks in computer vision, natural language processing and robotics. In the lecture we will introduce essential concepts such as convolutional neural networks, recurrent neural networks, generative models and deep reinforcement learning. The lectures will be accompanied by practical assignments using modern deep learning frameworks such as Tensorflow and PyTorch.

http://www.deeplearningbook.org/

Übungen siehe 19329402

In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

Qualification objectives: The students have a basic understanding of algebraic and computational methods for deep neural networks, their application scope and can practically build and train them with state-of-the-art software tools. They are familiar with typical deep learning structures and understand the relationship to their shallow counterparts.

Content:

- Perceptron

- Multilayer neural network and universal represenation theorem

- Backpropagation

- Deep feedforward networks

- Convolutional Neural Networks

- Autoencoder versus principal component analysis

- Time-autoencoder versus time-lagged independent component analysis

- Generative networks: Variational Autoencoders and Adversarial Generative Networks

- Active learning

This lecture/lab course is suitable for Master students of Mathematics, Computer Science or Computational Sciences
Students of the Computational Sciences program can combine this lecture/lab course with 19234502 + 19234501 (Mathematical aspects in machine learning) to complete “complex algorithms A/B”

Cryptoanalysis of asymmetrical schemes

The lecture deals with different asymmetrical cryptanalytics, in particular with the supposed hard problems of these processes. Some of the contents are

• RSA and the problem of factorization
• DSA and the discrete logarithm problem
• Merkel-Hellman and the knapsack and grid problem
• McEliece and the problem of decoding
• Matsumoto-Imai and the multivariate Polynomial System

Knowledge in the areas of IT security and cryptography is obligatory.

Effiziente Algorithmen für geometrische Probleme, z.B. Finden der konvexen Hülle einer Punktmenge, Voronoi-Diagramme, Delaunay-Triangulierung, geometrische Datenstrukturen, etwa zum Finden eines Punktes in einer ebenen Unterteilung. Das Gebiet hat Anwendungen in Computer-Graphik, Muster- und Formerkennung, geographischen Informationssystemen, CAD usw.

• M. de Berg, O. Cheong, M. van Kreveld, M. Overmars. Computational Geometry: Algorithms and Applications. Springer-Verlag Berlin, 2008.
• R. Klein. Algorithmische Geometrie. Addison-Wesley, 1997.
• J.-D. Boissonnat, M. Yvinec. Algorithmic Geometry. Cambridge University Press, 1998.
• F.P. Preparata, M.I. Shamos. Computational Geometry: An Introduction. Springer-Verlag New York, 1985.
• K. Mehlhorn. Data Structures and Algorithms, Vol. 3: Multi-dimensional Searching and Computational Geometry. Springer-Verlag Berlin, 1984.

Empfohlene Vorkenntnisse: "Höhere Algorithmik" oder verwandte Veranstaltungen.

Da es sich um das Hauptarbeitsgebiet der AG Theoretische Informatik handelt, ist ein Besuch für alle ratsam, die bei einem Dozenten dieser Gruppe eine Bachelor- oder Masterarbeit anfertigen wollen. Solche Arbeiten können im Anschluss an die Vorlesung vergeben werden.

Randomized algorithms

The word "random" often has negative connotations: if something is random, then it may be unpredictable, unprecise, noisy, erratic, difficult to understand. It is therefore surprising that randomness is of great help in algorithmic problem-solving. Algorithms that use randomness are often more efficient, easier to implement and easier to understand than their deterministic counterparts, and in some cases, the only efficient method we know for solving a problem is a randomized one. Randomness can also be viewed as a useful (and often limited) computational resource, similarly to time and space usage. Understanding the exact role that randomness plays in computation is one of the great scientific questions of our time.

This course will survey various algorithmic techniques, covering different aspects of the use of randomness in computation. Topics include (but are not limited to): randomized binary search trees, hashing-based data structures, random sampling, random walks, linear-time minimum spanning trees, cuts in graphs, verifying matrix multiplication, predicting the future with the help of experts, geometric algorithms, randomized incremental construction, load balancing, pattern matching, the probabilistic method, Chernoff bounds, primality testing, isolation, online algorithms, ski-rental and paging, approximation and LP-rounding.

(The course will be given in English.)

[MR] R. Motwani, P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995

[MU] M. Mitzenmacher, E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, 2005

[CLRS] T. H. Cormen, C. Leiserson, R. Rivest, C. Stein. Introduction to Algorithms, MIT Press 2009

[KT] J. Kleinberg, E. Tardos. Algorithm Design, Addison-Wesley 2005.

[M] J. Matoušek. Lectures in Discrete Geometry. Springer Verlag, 2002

Target Audience

Masters students in Computer Science or Mathematics, advanced Bachelor students.

Prerequisites

"Advanced Algorithms" or a similar class

In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

Randomized algorithms

The word "random" often has negative connotations: if something is random, then it may be unpredictable, unprecise, noisy, erratic, difficult to understand. It is therefore surprising that randomness is of great help in algorithmic problem-solving. Algorithms that use randomness are often more efficient, easier to implement and easier to understand than their deterministic counterparts, and in some cases, the only efficient method we know for solving a problem is a randomized one. Randomness can also be viewed as a useful (and often limited) computational resource, similarly to time and space usage. Understanding the exact role that randomness plays in computation is one of the great scientific questions of our time.

This course will survey various algorithmic techniques, covering different aspects of the use of randomness in computation. Topics include (but are not limited to): randomized binary search trees, hashing-based data structures, random sampling, random walks, linear-time minimum spanning trees, cuts in graphs, verifying matrix multiplication, predicting the future with the help of experts, geometric algorithms, randomized incremental construction, load balancing, pattern matching, the probabilistic method, Chernoff bounds, primality testing, isolation, online algorithms, ski-rental and paging, approximation and LP-rounding.

(The course will be given in English.)

[MR] R. Motwani, P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995

[MU] M. Mitzenmacher, E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, 2005

[CLRS] T. H. Cormen, C. Leiserson, R. Rivest, C. Stein. Introduction to Algorithms, MIT Press 2009

[KT] J. Kleinberg, E. Tardos. Algorithm Design, Addison-Wesley 2005.

[M] J. Matoušek. Lectures in Discrete Geometry. Springer Verlag, 2002

Target Audience

Masters students in Computer Science or Mathematics, advanced Bachelor students.

Prerequisites

"Advanced Algorithms" or a similar class

In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

Qualification objectives: The students have a basic understanding of algebraic and computational methods for deep neural networks, their application scope and can practically build and train them with state-of-the-art software tools. They are familiar with typical deep learning structures and understand the relationship to their shallow counterparts.

Content:

- Perceptron

- Multilayer neural network and universal represenation theorem

- Backpropagation

- Deep feedforward networks

- Convolutional Neural Networks

- Autoencoder versus principal component analysis

- Time-autoencoder versus time-lagged independent component analysis

- Generative networks: Variational Autoencoders and Adversarial Generative Networks

- Active learning

This lecture/lab course is suitable for Master students of Mathematics, Computer Science or Computational Sciences
Students of the Computational Sciences program can combine this lecture/lab course with 19234502 + 19234501 (Mathematical aspects in machine learning) to complete “complex algorithms A/B”

Cryptoanalysis of asymmetrical schemes

The lecture deals with different asymmetrical cryptanalytics, in particular with the supposed hard problems of these processes. Some of the contents are

• RSA and the problem of factorization
• DSA and the discrete logarithm problem
• Merkel-Hellman and the knapsack and grid problem
• McEliece and the problem of decoding
• Matsumoto-Imai and the multivariate Polynomial System

Knowledge in the areas of IT security and cryptography is obligatory.

Inhalt:

1. fundamentals, elementary logic, ordered pairs, relations, functions, domain and range of a function, inverse functions (injectivity, surjectivity)
2. numbers, induction, calculations in R, C
3. arrangement of R, maximum and minimum, supremum and infimum of real sets, supremum / infimum completeness of R, absolute value of a real number, Q is dense in R
4. sequences and series, limits, cauchy sequences, convergence criteria, series and basic principles of convergence
5. topological aspects of R, open, closed, and compact real sets
6. sequences of functions, series of functions, power series
7. properties of functions, boundedness, monotony, convexity
8. continuity, limits and continuity of functions, uniform continuity, intermediate value theorems, continuity and compactness
9. differentiability, concept of the derivative, differentiation rules, mean value theorem, local and global extrema, curvature, monotony, convexity
10. elementary functions, rational functions, root functions, exponential functions, angular functions, hyperbolic functions, real logarithm, inverse trigonometric functions, curve sketching
11. beginnings of integral calculus

Actual information can be found on the webpage of the working group:

Analysis I

Basic terms/concepts: sets, maps

Linear equation systems: solvability criteria, Gauss algorithm

Vector spaces: linear independence, generating systems and bases, dimension,
subspaces

Linear maps: image and rank, relationship to matrices, behaviour under
change of basis

Dual vector spaces: multilinear forms, alternating and symmetric bilinear
forms, relationship to matices, change of basis

Determinants: Cramer's rule, Eigenvalues and Eigenvectors

Equivalence relations, groups, rings, fields

Prerequisites:

Participation in the preparatory course (Brückenkurs) is highly recommended.

Literatur:

Wird in der Vorlesung genannt!

• linear algebra:
  • vector space, basis and dimension;
  • linear map, matrix and rank;
  • Gauss-elimination and linear systems of equations;
  • determinants, eigenvalues and eigenvectors;
  • euclidean vector spaces and orthonormalization;
  • principal component transformation;
  • Applications of linear algebra in affine geometry, statistics, and coding theory  (linear codes)

• Klaus Jänich: Lineare Algebra, Springer-Lehrbuch, 10. Auflage 2004
• Dirk Hachenberger: Mathematik für Informatiker, Pearson 2005
• G. Grimmett, D. Welsh: Probability - An Introduction, Oxford Science Publications 1986
• Kurt Meyberg, Peter Vachenauer: Höhere Mathematik 1, Springer-Verlag, 6. Auflage 2001
• G. Berendt: Mathematik für Informatiker, Spektrum Akademischer Verlag 1994
• Oliver Pretzel: Error-Correcting Codes and Finite Fields, Oxford Univ. Press 1996

The sign-up for the tutorial sessions will be announced in due time.