Spain

A thread-safe data store has been developed to enforce 
interface consistency and shared data coherency in a 
concurrent modular embedded real-time system. 
Typical messaging techniques may not provide optimal 
data transfer between software components in all 
embedded systems, especially if there is a high degree 
of data interdependency as the number of components 
increases. The data store paradigm reduces the 
overall communication load by providing finer data 
item granularity, and eliminating the copy and transfer 
of unused message content. The data store described 
in this paper is implemented with code auto-generation 
and provides compile-time error checking, ensuring 
effortless data integrity by automatically rebuilding 
when software component interfaces are changed. The 
data store has been successfully employed to rehost a 
highly-coupled legacy software application into a 
more modularized component architecture. 
Keywords: modular embedded systems, code autogeneration, concurrency, multicore, pipelined data 
transfer

AEiC 2021 - 25th Ada-Europe International Conference on Reliable Software Technologies

Auto-generated coherent data store for concurrent modular embedded systems

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### Welcome Message from our Co-Chairs

Through this message, we want to give you our warmest welcome to the 25th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2021). The special circumstances we all go through have made the conference a virtual event. Nonetheless, this will allow us to take advantage of the benefits of this format by using the Underline.io platform that allows remote participation of speakers and attendees and a virtual exhibition.
The platform will also provide a virtual space through Gather.Town to facilitate social interaction among participants, which, in addition to presenting state of the art research results, is one of the most important goals of a conference. This platform will hold various social events together with breaks and a poster session. 

The conference schedule includes a four-day program and exhibition from Monday to Thursday, with parallel tutorials on Monday, and keynotes, technical sessions and a Work-in-Progress session on the remaining three days. The technical sessions include the presentations of 13 journal-track papers, 5 industrial presentations and 6 invited talks on leading topics on reliable software technologies. The program will be completed with three outstanding keynotes that will delight the participants.

The main conference activities will be from 13:00 to 18:00 Central European Summer Time (CEST) to allow participants from America to Central Asia to attend to the conference sessions. Virtual social events are scheduled at the beginning and the end of each day. We encourage you to participate in these activities as well as visiting the exhibition. We look forward to meeting you virtually in June 2021!

**J. Javier Gutiérrez and Mario Aldea Rivas**
 // AEiC 2021 Program Co-Chairs

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The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities. This includes talks to attend in person, talks to attend remotely, breaks with colleagues and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).

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The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

technical paper

Partitioning techniques are implemented in the development of safety-critical applications to ensure isolation among components. An adequate scheduling of the execution of such partitions is a key challenge so that applications meet the hard deadlines imposed. In this work, we study the effect of different partition window configuration parameters, with the aim of analyzing their impact in the worst-case response times of system tasks. This is the first step in the development of an algorithm for optimizing partition windows in hierarchically-scheduled time-partitioned distributed systems.

How windows size and number can influence the schedulability of hierarchically-scheduled time-partitioned distributed real-time systems

Safety Critical Multicore for Avionics Creating a multicore platform for safety critical avionics is the next major step for most avionics manufactures. While multicore processors are commonly used in most all other markets, the avionics industry has taken years to trust multicore technologies. This delayed acceptance is understandable due to an avionics system’s stringent safety and deterministic requirements which are not commonplace in many other industries. As a result, years of study have been invested to determine the challenges multicore processors pose for safety critical systems and then followed by the development of technologies and strategies that mitigate those challenges. Certification authorities and industry suppliers have invested in numerous studies and discussions over recent years to identify the issues multicore processors pose for safety critical systems. Formalized positions of these efforts are the FAA CAST-32A Positioning Paper, and EASA’s multicore certification review item (CRI). The crux of these papers (regarding software) focuses on bounding and controlling the interference patterns that exists when processor cores share resources. Unless interference patterns are addressed, real-time operations can be erratic and worse case execution (WCE) times can be longer than in a single core system. This paper will highlight the challenges of implementing multicore processors for any avionics developer. It will present Deos SafeMC and show how it helps address CAST-32A concerns. Specifically, the paper will introduce the means of which Deos SafeMC minimizes and bounds contention issues within multicore environments. For example, Deos cache partitioning and memory pooling features enable the user to configure the memory architecture to minimize cache thrashing. In addition, Deos provides the system architect the tools required to schedule applications across all cores in such a way that developers can coordinate applications such that they minimize conflicts over shared resources. While the paper uses Deos SafeMC an example of how one can address items brought up in CAST-32A, non-Deos users should also gain an insight into the concern multicore processors pose and to consider way in which they can be resolved.

Certifiable safety critical multi-core for avionics

Brook SC: High-level certification-friendly programming for GPU-powered safety critical systems

Machine learning and high criticality applications

Several industrial domains are currently developing innovative safety-related autonomous systems characterized by increasing software complexity and high-performance requirements. Due to these features, different research initiatives aim to pave the way towards the usage of Linux for the development of such complex safety-related systems. However, the high execution path variability of the Linux kernel challenges test coverage-based verification, Highly Recommended (HR) technique by safety standards. This research describes a novel statistical analysis method for Linux kernel execution path coverage quantification, which includes the uncertainty estimation of the software execution. The method is applied to a simple, but reproducible case study, and the results of which are analyzed and explained.

Towards Linux based safety systems - A statistical approach for software execution path coverage

In order to build reliable Big Data software, we should prepare ourselves to the distributed fallacy, “A distributed 
system will always fail”. In this way, Big Data systems have been architected for survival of multiple system failures 
from the ground up. We will make a little introduction about different Big Data frameworks and their architectural 
decisions in order to be able to survive to multiple system failures in order to be reliable. 
Next, we will focus on the Industrial Internet of Things (IIoT). IIoT nowadays is an exploding trend with significant 
implications for the global economy. It spans industries including manufacturing, mining, agriculture, oil and gas, and 
utilities. It also encompasses companies that depend on durable physical goods to conduct business, such as 
organizations that operate hospitals, warehouses and ports or that offer transportation, logistics and healthcare 
services. Not surprisingly, the IIoT’s potential payoff is enormous. A specific example of this potential use is the 
Predictive maintenance of assets, saving over scheduled repairs, reducing overall maintenance costs and eliminating 
breakdowns up. For example, Thames Water, one of the largest providers of water in the UK, is using sensors and 
real‐time data to help the utility company anticipate equipment failures and respond more quickly to critical 
situations, such as leaks or adverse weather events. However, analyzing such large quantities of usually out‐of‐order 
real‐time data from different sensors and system is a real challenge with Big Data analytics frameworks. 
The final part of the talk will be composed of a hands‐on workshop where we will use Apache Zeppelin, Apache Kafka, 
Apache Avro, Apache Cassandra and Spark´s Structured Streaming API to see how we can solve challenges of related 
to IIoT projects such as handling late unordered data. 
All the code used along with the developer environment be available at GitHub right after the keynote.

Software reliability in the Big Data era with an industry‐minded focus

The forthcoming Ada 2022 revision of the Ada standard includes a number of significant new features, which together 
make the language more expressive and productive in a multicore context, while enhancing its safety and support for 
more complete abstractions with formal contracts. This talk will introduce these key new features with a series of 
examples: 
• parallel loops and blocks, coupled with static detection of data races and potential blocking 
• iterator syntax for incorporating filters and user‐defined iterator procedures 
• libraries for atomic operations, including fetch‐and‐add and compare‐and‐swap 
• aggregates, literals, images, and map‐reduce for user‐defined types 
• libraries for arbitrary precision integer and rational arithmetic 
• more expressive contracts using delta aggregates and declare expressions 
• the Jorvik profile as the next step up from the Ravenscar profile

Auto-generated coherent data store for concurrent modular embedded systems

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Next from AEiC 2021 - 25th Ada-Europe International Conference on Reliable Software Technologies

How windows size and number can influence the schedulability of hierarchically-scheduled time-partitioned distributed real-time systems

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