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In diesem Talk blicken Prof. Dr. Wolfgang Mauerer und Ralf Ramsauer unter die Haube des verteilten Versionskontrollsystems Git. Neben einer genauen Beschreibung der Strukturen und Plumbing APIs, mit denen Git intern Commits erzeugt und verknüpft, gehen die Vortragenden auch auf nützliche Features und Standards ein, welche die Kollaborition in großen Open-Source Projekten erleichtern.
Debian, as a collection of software packages and components, is known to be one of the largest software projects in the history of mankind. Combined with a traceable history over many years, the artefacts created by Debian developers and users make it one of science’s favourite targets to quantitatively or qualitatively understand how real-world software development works (or does not), how people collaborate, and many other other related questions. Unfortunately, while scientists make ample use of the resources and artefacts created by FLOSS and friends, the exchange of insights and ideas does not seem to extend in both directions: Developers, users and integrators are often unaware of results obtained in science. This talk will introduce the Debian community to a selection the most important results obtained by scientific (software engineering) research, with a special focus on large-scale socio-technical analysis of projects like Debian, and the possible implications and improvements these may bring to Debian development itself.
Embedded Linux drives an every-increasing number of appliances in many domains and applications, some even real-time and/or safety critical. Traditional quality assurance of such systems is based on testing and formal verification, but the huge amount of code and the rapid dynamics of the Linux ecosystem, as well as fundamental limitations of formal methods make these approaches unsatisfactory.
Statistical quality assurance for reliability, error rates, maximal latencies etc. is needed. We will discuss current best practises, how to design and run automated statistical tests that capture relevant information, and how to properly evaluate the resulting data. Practical real-world examples and recipes are played through using the open source R language. Most importantly, we identify common mistakes in (over-)interpreting statistical results and predictions that may eventually harm people.
The partitioning hypervisor Jaihouse allows us to run safety critical and uncritical applications in parallel on a single SoC. We present our experiences when porting a safety and real-time critical existing application as a Jailhouse guest. It shows a novel and promising approach for implementing mixed-criticality applications with real-time requirement while not loosing the benefits of Linux. This is done by static partitioning of hardware resources; guests do not interfere. We will present a multicopter platform running the real-time critical flight stack in an isolated Jailhouse guest. This proves the practicability of Jailhouse as well as the suitability for real-time safety critical systems by porting an existing application to a Jailhouse cell. We stress its concept and show up current hardware limitations, like undesired behaviour and present possible workarounds and solutions.
Industrial computing devices, in particular cyber-physical, real-time and safety-critical systems, focus on reacting to external events and the need to cooperate with other devices to create a functional system. They are often implemented with languages that focus on a simple, local description of how a component reacts to external input data and stimuli. Despite the trend in modern software architectures to structure systems into largely independent components, the remaining interdependencies still create rich behavioural dynamics even for small systems. Standard and industrial programming approaches do usually not model or extensively describe the global properties of an entire system. Although a large number of approaches to solve this dilemma have been suggested, it remains a hard and error-prone task to implement systems with complex interdependencies correctly. We introduce multiple coupled finite state machines (McFSMs), a novel mechanism that allows us to model and manage such interdependencies. It is based on a consistent, well-structured and simple global description. A sound theoretical foundation is provided, and associated tools allow us to generate efficient low-level code in various programming languages using model-driven techniques. We also present a domain specific language to express McFSMs and their connections to other systems, to model their dynamic behaviour, and to investigate their efficiency and correctness at compile-time.