Campus E1 1
66123 Saarbrücken (Germany)
ERC Consolidator Grant
Prof. Bernd Finkbeiner, Ph.D. is a faculty member at the CISPA Helmholtz Center for Information Security and a professor for computer science at Saarland University. He obtained his Ph.D. in 2003 from Stanford University. Since 2003, he leads the Reactive Systems Group, which became part of CISPA in 2020. His research focus is the development of reliable guarantees for the safety and security of computer systems, including specification, program synthesis and repair, and static and dynamic verification.
37th Annual ACM/IEEE Symposium on Logic in Computer Science37th Annual ACM/IEEE Symposium on Logic in Computer Science
Innovations in Systems and Software Engineering
FoSSaCS 2022, LNCS 13242ETAPS 2022
30th EACSL Annual Conference on Computer Science Logic (CSL 2022)30th EACSL Annual Conference on Computer Science Logic (CSL 2022)
41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2021)41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science
Advances in Neural Information Processing Systems 34 (NeurIPS 2021)Thirty-fifth Conference on Neural Information Processing Systems
IEEE Transactions on Visualization and Computer GraphicsIEEE VIS 2021
LNCS19th International Symposium on Automated Technology for Verification and Analysis (ATVA 2021)
Lectures: Tuesday 2 to 4 pm and Thursday 10 am to 12 noon in HS001, E1 3.
Tutorials: Friday 10 am to 12 noon and Friday 12 noon to 2 pm in Room 206, E1 1.
Office Hour: Wednesday 10 am to 12 noon in Room 106, E1 1.
There will be an option to attend the lectures, tutorials and Office Hour remotely.
How can one ensure that computer programs actually do what they are intended to do? Simply running a program repeatedly with various inputs is inadequate, because one cannot tell which inputs might cause the program to fail. It is possible to tailor a tester to test a given program, but present-day programs are so complex that they cannot be adequately checked through conventional testing, which can leave significant bugs undetected. Program verification uses mathematical and logical methods to prove that a program is correct. This approach was pioneered by, among others, Dijkstra, Floyd, Gries, Hoare, Lamport, Manna, Owicki and Pnueli. Today, we have powerful decision procedures that can, completely automatically, answer basic questions about the data types typically used by programmers. Model Checking is a “push-button” technology that can analyze finite-state abstractions of programs with as many as 1020 states. This course takes an up-to-date look at the theory and practice of program verification.
In this seminar, we will explore new research that shows that deep neural networks are, in fact, able to reason on “symbolic systems”, i.e., systems that are built with symbols like programming languages or formal logics.
This course takes an up-to-date look at the theory and practice of program verification.