The goal of this seminar is to introduce students to important research results in the area of software reliability, and in particular, program analysis, software engineering, and software security. To achieve this, students will study and present research papers in the area; they will also be expected to participate in paper discussions.
During this seminar, the students will...
- become familiar with a broad range of research results in the area of software reliability,
- learn how to read and understand papers in the area,
- learn how to evaluate papers in the area by highlighting limitations and suggesting possible improvements,
- learn how to present a technical topic in the area to an audience of peers.
Students become familiar with the area through a study of key papers, reviewing papers, presenting papers to colleagues, and working individually or in groups to solve a research problem.
This course introduces students to the principles, design, and implementation of operating systems. The lectures focus primarily on the principles and design of operating systems; a course project exposes students to the implementation aspects of operating systems and serves to solidify students' understanding of the course material. Please refer to https://courses.mpi-sws.org/os-ws19 for further details.
Program analysis can be used to find or to show the absence of certain kinds of bad program behaviors, e.g. division by zero, null-pointer access, etc., in general fully automatically. In this course, we will
- introduce the theoretical foundation of many static analysis techniques (data flow analysis, abstract interpretation)
- present the main types of dynamic techniques (fuzz testing, symbolic execution)
- discuss the tradeoffs in efficiency, accuracy, and soundness between the different techniques
- show applications of program analysis techniques in various application areas
We would like to start a series of 'townhall talks' at the institute, which will feature a mix of technical overview, as well as communication, presentation, and other research skills talks. The technical overview talks will be high-level presentations about a group's current research. The research skills talks are meant to complement Rose's communication classes and support, and will be usually followed by a (panel) discussion, i.e. they are meant to be interactive. Everyone is encouraged to participate!
The talks are scheduled roughly every 6 weeks.
This course will cover both the writing process and the writing product. You will learn writing principles that will you help you to create text that is coherent, cohesive, and clear. A primary goal of this course is to teach you how to "escape" your own expertise in order to identify the parts of your text that will cause a reader difficulties.
The course format will vary from week-to-week, and will include a mix of mini-lectures, exercises, one-on-one feedback, and group discussions of part of a paper (usually written by a course participant but sometimes selected from the literature). In order to get the most out of the class, participants will be expected to do substantial out-of-class writing (about one to two hours per week). The precise content of the course will be tailored to the course participants.
This course is intended for PhD students and postdocs in Computer Science. For PhD students, I typically prefer that students have already taken my course on how to give scientific presentations. I do make exceptions, but students need to demonstrate that they already have basic competence at communicating scientific ideas verbally.
- Teacher: Rose Hoberman
This course covers advanced topics of automata theory and its applications (e.g., computer-aided verification), including:
- learning of automata
- the connection of automata to second-order logic and Linear Temporal Logic
- automata on infinite words
- automata on trees
- synthesis of reactive systems
Intended Audience: The course is intended for computer science or math students with background in logic and theory of computation (familiarity with basic algorithms, logic, and the theory of computation will be assumed). Talk to the instructor if you are not sure if you have the background. Please attend the initial lecture for background material.
Further, students should (1) have "mathematical maturity" (e.g., you should be comfortable with proofs and abstract reasoning), (2) be interested in the material; and (3) are willing to spend time outside of class in order to better understand the material presented in lectures.
Advanced course at Universität des Saarlandes
6 credit points
Summer semester 2019
This course introduces two topics together
- The first part is a self-contained introduction to the proof assistant Isabelle/HOL.
- The second part is an introduction to the semantics of imperative programming languages. This part is formalized in Isabelle.
This advanced course is based on a book by Prof. Tobias Nipkow and Prof. Gerwin Klein, which is available both as a free PDF online and as a hardcover from Springer. The material is complementary to the core Semantics course by Prof. Gert Smolka, which uses Coq and focuses on the λ-calculus and functional programming.
Proof assistants are tools that allow its users to carry out mathematical proofs rigorously, based on a logical foundation. Developing a proof in a proof asssistant as opposed to using pen and paper is roughly the equivalent of programming on a computer as opposed to sketching pseudocode on paper. Expertise with proof assistants is becoming an increasingly important skill, especially for software verification, which aims at proving the absence of bugs in programs. In the experience of many instructors, the use of a proof assistant helps students get a good grip on computer science topics.
Coq and Isabelle are the main two proof assistants in use. Isabelle's strength is that it is simple as 1-2-3: It offers (1) a simple yet powerful logic, (2) a convenient user interface, and (3) a lot of proof automation.
There are no formal prerequisites for taking the course. Familiarity with a typed functional programming language (such as Standard ML, OCaml, Haskell, or F#), as taught in Programmierung 1, is highly recommended.