Introduction to parallel programming: deterministic and non-deterministic programs, models for parallel computation, synchronization, communication, and fairness.

Security issues in modern systems (blockchains, datacenters, deep learning, etc.) result in billions of losses due to hacks and system downtime. This course introduces fundamental techniques (ranging over automated analysis, machine learning, synthesis, zero-knowledge, differential privacy, and their combinations) that can be applied in practice so to build more secure and reliable modern systems.

Reliability, security, privacy, and robustness are core challenges in achieving trustworthy AI and are of fundamental importance. The goal of this course is to teach both the mathematical foundations of this emerging field and to introduce students to the latest and most exciting advances.

This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research.

The course provides an overview of techniques to build correct software, with a strong focus on testing and program analysis.

The course is an introduction to research in software engineering, based on reading and presenting high quality research papers in the field. The instructor may choose a variety of topics or one topic that is explored through several papers.