Safety-Critical Systems: From Predictable Systems to Autonomous AI (Wintersemester 2018/2019)
Lecturer:
Prof. Dr. Holger Giese
(Systemanalyse und Modellierung)
,
Joachim Hänsel
(Systemanalyse und Modellierung)
General Information
- Weekly Hours: 4
- Credits: 6
- Graded:
yes
- Enrolment Deadline: 26.10.2018
- Teaching Form: Lecture / Exercise
- Enrolment Type: Compulsory Elective Module
- Course Language: German
Programs, Module Groups & Modules
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-K Konzepte und Methoden
- SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-S Spezialisierung
- SAMT: Software Architecture & Modeling Technology
- HPI-SAMT-T Techniken und Werkzeuge
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-C Concepts and Methods
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-T Technologies and Tools
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
Description
Today, we are surrounded by many systems in our daily life as well as an underlying infrastructure that contains complex behavior realized by software. Often these systems and infrastructures could also endanger human life or the environment and thus are safety-critical systems. Traditionally, the safety is assured by building it in during design time, rather than adding it on to a completed design. Design time incorporation of safety is achieved by building predictable systems for which the necessary safety aspects can be understood and mastered.
However, nowadays we can observe a clear trend from predictable systems to systems that can be characterized as autonomous artificial intelligence. Consequently, the existing body of work for handling safety-critical systems and their software does often not apply and novel approaches are required. The lecture will review the challenges for assuring safety for the considered systems ranging from classical predictable systems to autonomous AI and present the current state-of-the-art for developing and assure safety.
Learning
Each week two lectures will be given (90 minutes). Some of these lectures will include working on exercises.
Examination
- Oral exams by the end of the semester.
- Active and successful participation in the exercises.
- The final course grade is the oral exam grade.
Dates
ANNOUNCEMENT. The lecture on 21st of November is cancelled.
ANNOUNCMENT: The lecture on 28th of November will be in A-2.8!!!
ANNOUNCMENT: Download site for PRISM
ANNOUNCEMENT. Meeting on 8th for extended exercise discussion, lecture next year will start at 15th of January 2019
https://www.prismmodelchecker.org/download.php
Lecture: each week:
Tuesday, 13:30 – 15:00, Room A-2.2
Wednseday, 13:30 – 15:00, Room A-2.2
First lecture: 23.10.2018
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