On this site, there is only displayed the English speaking sessions of the OOP 2022 Digital. You can find all conference sessions, including the German speaking ones, here.
The times given in the conference program of OOP 2022 Digital correspond to Central European Time (CET).
By clicking on "EVENT MERKEN" within the lecture descriptions you can arrange your own schedule. You can view your schedule at any time using the icon in the upper right corner.
Track: Signature Track: The Time is Now!
- Artificial Intelligence Now!
- C++ and Programming of Embedded Systems
- DevOps & Automation Now!
- Diversity & Inclusion
- From Projects to Products/Services: Aligning Architecture and Organization for Sustainable Speed
- Full Day Tutorial
- Fusion: IT-Future-Society
- Half Day Tutorial
- Modern Software Architecture
- Product Development in Times of Digitalization
- Signature Track: The Time is Now!
- Social Integration
- Software Architecture Communication & Assessment
- Testing & Quality
- Trends & Techniques
- Use Domain-Driven Design Now!
- Artificial Intelligence
- Domain-Driven Design
- Product Development
- Programming Languages
- Requirements Engineering
- Soft Skills/Social Skills
- Software Engineering
- Talks with Limited Attendance
- Testing & Quality
- Virtual Reality
Chaos engineering, popularised by Netflix, is an approach to building scalable, resilient systems through destructive experiments, but what other impacts does it have? How can adopting chaos engineering change organisational culture? This talk explores the parallels between modern distributed architectures and the unpredictable challenges of the modern world, and how approaches like chaos engineering help organisations deal with both.
We will deep dive into the practices needed to make chaos engineering a success in your organisation and uncover how they help beyond just chaos engineering experiments. We will also explore the nature of complex, socio-technical systems and why new approaches are needed to deal with them.
Target Audience: Anyone in a team or organisation considering adopting chaos engineering
Digitalization has been changing existing industry B2B businesses, digitalization business models arrived and the Digitalization solutions need to be developed to support this. The sudden enforcement of social distancing has given the digital transformation a significant push forward. How do we develop innovative Digitalization offerings in the future? We will show how to seize these opportunities and forge new paths toward the new normal for Software Engineering.
Target Audience: Software Engineers, System and Software Architects, Software Managers
Prerequisites: Knowledge in Software Engineering Practice
Besides IoT and Machine2Machine communication Digital Twins are a cornerstone of the fourth industrial revolution. In general, a Digital Twin is the virtual replica of a physical object or system. But what does this mean in detail – what are the ingredients of a Digital Twin? How can Digital Twins be built and utilized and what value do they bring? This talk gives an overview of different types of Digital Twins, different applications from public to industrial utilization and architectural approaches how to create and execute them.
Target Audience: System Architects, product owners, software engineers
Leaders of innovation, business and tech are experiencing an unprecedented demand to accelerate the pace of digital transformation. From board rooms to kindergarten classrooms, the unexpected upheaval triggered by the onset of the pandemic saw organizations make drastic changes. In this talk, Layla will share how we can learn from our transformations of past industrial revolutions, how shifts in human behavior help inform opportunities and how we can best consider interventions and take action.
Target Audience: Strategists, Product Owners, Designers, Technologists, Developers, Architects, Managers, - everyone
Leaders of innovation, business and tech are experiencing an unprecedented demand to accelerate the pace of digital transformation. From board rooms to kindergarten classrooms, the unexpected upheaval triggered by the onset of the pandemic saw organizations make drastic changes. What for some was previously believed to be a process anticipating to take years, or met with resistance or incremental change, happened in months, weeks or even days.
We now have the amazing opportunity to shape our future rather than to react to it. Pandemic affects and evolving needs are converging to drive development towards innovative solutions. We need to build new capabilities towards helping organizations adopt new skills and shape new products and solutions – and simultaneously, we need to make different choices about where to focus efforts and initiatives. While no one can predict future moments of opportunity, or how technology will impact our lives on the short and long term, with certainty, we know opportunities will continue to come.
In this talk, Layla will share how we can learn from our transformations of past industrial revolutions, how shifts in human behavior help inform opportunities and how we can best consider interventions and take action.
In this talk, we will give an overview about all the different aspects that affect climate change from the software engineering perspective and discuss a number of concrete actions that every software engineer can take (and should keep in mind day-in day-out) to help fight climate change. During the talk, we will not only provide an overview of the landscape, but also cover topics in more depth and discuss the challenges that come with them.
Target Audience: Architects, Developers, Project Leads
In this talk, we will give an overview about all the different aspects that affect climate change from the software engineering perspective and discuss a number of concrete actions that every software engineer can take (and should keep in mind day-in day-out) to help fight climate change, including:
- Energy consumption of software and what that means for software engineering
- Research studies about software running in data centers and the problem of zombies
- Work towards operating software in a carbon-aware way
- When and how far do renewable energies help
- How does carbon offsetting works and how to select the right projects
- And more...
In 2020, the three big cloud providers signed us all up for a revolution in the way we write and operate software. The deadline is 2030. Are you ready?
Target Audience: General techie. This works for all
In 2020, Google Cloud, AWS, and Azure all committed to be carbon zero by 2030. It's the incredibly tough goal of zero emitted carbon as a result for operating our applications and services. They can't do it alone. AWS says "we optimize for sustainability of the cloud, while customers are responsible for sustainability in the cloud, meaning they must optimize their workloads and resource utilization." I don't think this is a request. They've signed up to be carbon zero by 2030. That means we have too. The clock is ticking.
With AI entering more and more aspects of our lives, scepticism and worries towards this technology are increasing too. Empathy towards basic human needs and a great User Experience can help AI being more widely accepted and used.
But how to get there?
After covering basic UX principles, the talk will deep dive into the fields of trust, transparency and explainable AI.
The goal is to outline a path to a fruitful collaboration and mutual understanding between humans and AI.
Target Audience: Software Engineers, Data Scientists, Product Owners, Researchers, Designers
Big Bang rebuilds of systems are so 20th century. With our users expecting new functionality to be shipped more frequently than ever before, we no longer have the luxury of a complete system rebuild. In fact, a big bang migration of a monolithic architecture into a microservice architecture can be especially problematic, as we’ll explore in this talk.
We want to ship features, but we also want to improve our architecture, and for many of us this means breaking down existing systems into microservices. But how do you do this while still regularly releasing new features?
In this talk, I’ll share with you some key principles and a number of patterns which you can use to incrementally decompose an existing system into microservices. I’ll also cover off patterns that can work to migrate functionality out of systems you can’t change, which are useful when working with very old systems or vendor products. We'll look at the use of strangler patterns, change data capture, database decomposition and more.
Coming out of this talk you’ll have a better understanding of the importance of evolving an architecture, along with some concrete patterns to help you do that on your own projects.
Target Audience: Developers, architects, operations, testers and anyone actively involved in software delivery
Prerequisites: Basic knowledge about microservices and software delivery
Machine Learning appears to have made impressive progress on many tasks from image classification to autonomous vehicle control and more. ML has become so popular that its application, though often poorly understood and partially motivated by hype, is exploding. This is not necessarily a good thing. Systematic risk is invoked by adopting ML in a haphazard fashion. Understanding and categorizing security engineering risks introduced by ML at design level is critical. This talk focuses on results of an architectural risk analysis of ML systems.
Target Audience: Architects, Technical Leads, and Developers and Security Engineers of ML Systems
Prerequisites: Risk Managers, Software Security Professionals, ML Practitioners, everyone who is confronted by ML
Machine Learning appears to have made impressive progress on many tasks including image classification, machine translation, autonomous vehicle control, playing complex games including chess, Go, and Atari video games, and more. This has led to much breathless popular press coverage of Artificial Intelligence, and has elevated deep learning to an almost magical status in the eyes of the public. ML, especially of the deep learning sort, is not magic, however. ML has become so popular that its application, though often poorly understood and partially motivated by hype, is exploding. In my view, this is not necessarily a good thing. I am concerned with the systematic risk invoked by adopting ML in a haphazard fashion. Our research at the Berryville Institute of Machine Learning (BIIML) is focused on understanding and categorizing security engineering risks introduced by ML at the design level. Though the idea of addressing security risk in ML is not a new one, most previous work has focused on either particular attacks against running ML systems (a kind of dynamic analysis) or on operational security issues surrounding ML. This talk focuses on the results of an architectural risk analysis (sometimes called a threat model) of ML systems in general. A list of the top five (of 78 known) ML security risks will be presented.