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Keynote Lectures

The Lost Art of Software Architecture Modelling
Simon Brown, Architectis Limited, Jersey

Model-based Development and Assurance of Learning-enabled Cyber-Physical Systems
Gabor Karsai, Vanderbilt University, United States

 

The Lost Art of Software Architecture Modelling

Simon Brown
Architectis Limited
Jersey
 

Brief Bio
Simon is an independent consultant specialising in software architecture, and the author of “Software Architecture for Developers” (a developer-friendly guide to software architecture, technical leadership and the balance with agility). He is also the creator of the C4 model for visualising software architecture, and the founder of Structurizr. Simon is a regular speaker at international software development conferences, and travels the world to help organisations visualise and document their software architecture.


Abstract
"Big design up front is dumb. Doing no design up front is even dumber." This quote epitomises what I've seen during our journey from "big design up front" in the 20th century, to "emergent design" and "evolutionary architecture" in the 21st. In their desire to become "agile", many teams seem to have abandoned architectural thinking, up front design, documentation, diagramming, and modelling. In many cases this is a knee-jerk reaction to the heavy bloated processes of times past, and in others it's a misinterpretation and misapplication of the agile manifesto.
As a result, many of the software design activities I witness these days are very high-level and superficial in nature. The resulting output, typically an ad hoc sketch on a whiteboard, is usually ambiguous and open to interpretation, leading to a situation where the underlying solution can't be communicated, assessed, or reviewed. The same is true of long-lived documentation, which is typically a collection of disconnected diagrams that are out of sync, and out of date. Modelling can help resolve many of these problems, but that's a tough thing to sell to mainstream developer audiences these days - teams are either not aware of modelling, or they associate it with bad experiences using complicated CASE tools from the past. Join me for a discussion about the lost art of software architecture modelling, and my experiences of how I've reintroduced it to the agile generation.



 

 

Model-based Development and Assurance of Learning-enabled Cyber-Physical Systems

Gabor Karsai
Vanderbilt University
United States
 

Brief Bio
Dr. Gabor Karsai is Professor of Electrical Engineering and Computer Science at Vanderbilt University and Senior Research Scientist and Associate Director at the Institute for Software-Integrated Systems. He has over thirty years of experience in research on systems and software engineering. He conducts research in the model-based design and implementation of cyber-physical systems, in programming tools for visual programming environments, and in the theory and practice of model-integrated computing. He received his BSc, MSc, and Dr Techn degrees from the Technical University of Budapest, in 1982, 1984 and 1988, respectively, and his PhD from Vanderbilt University in 1988.


Abstract
Cyber-Physical Systems (CPS) are increasingly incorporating Learning-Enabled Components (LEC) to implement complex functions. By LEC we mean a component (typically, but not exclusively, implemented in software) that is realized with the help of data-driven techniques, like machine learning. For example, an LEC in an autonomous car can implement a lane follower function such that the developer trains an appropriate convolutional neural network with a stream of images of the road as input and the observed actions of a human driver as output. For high-consequence systems the challenge is to prove that the resulting system is safe: it does no harm, and it is ‘live’: it is functional. Safety is perhaps the foremost problem in autonomous vehicles, especially for ones that operate in a less-regulated environment, like the road network. The traditional approach for proving the safety of systems is based on extensively documented but often informal arguments – that are very hard to apply to CPS with LEC. The talk will focus on a current project that aims at changing this paradigm by introducing (1) formal verification techniques whenever possible (including proving properties of the ‘learned’ component), (2) monitoring technology for assurance to indicate when the LEC is not performing well, and (3) formalizing the safety case argumentation process so that it can be dynamically evaluated. The application target is autonomous vehicles. The goal is to construct a model-based engineering process and a supporting model-based toolchain that can be used for the engineering and systematic assurance of CPS with LECs.



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