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In space missions, boot software is in charge of the initialisation sequence of flight computers. The processor module in which it runs has a high tolerance to radiation, although not all devices have the same tolerance level. A boot software design capable of recovering from errors in the most vulnerable devices shall provide greater system reliability. This work has been carried out in the context of the boot software development for the control unit of the Energetic Particle Detector instrument on-board the Solar Orbiter mission. This mission operates close to the Sun where high-energy particles can cause single event effects on electronic devices, especially SDRAM and EEPROM, which show lower radiation tolerance than the other devices. This fact motivates this work, where a sensitivity analysis of the incidence of single event effects on the behaviour of the boot software is carried out. Specifically, a fault injection environment has been used to analyse the effect of “stuck-at” bits on the boot software ability to deploy and pass control to the application software. The results show the boot software vulnerability to this kind of permanent effects and have led to the implementation of a reliability-oriented design, presented in this paper.

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

Reliability-oriented design of on-board satellite boot software against single event effects

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

The AAMAS conference series was initiated in 2002 in Bologna, Italy as a joint event comprising the 6th International Conference on Autonomous Agents (AA), the 5th International Conference on Multiagent Systems (ICMAS), and the 9th International Workshop on Agent Theories, Architectures, and Languages (ATAL).

Subsequent AAMAS conferences have been held in Melbourne, Australia (July 2003), New York City, NY, USA (July 2004), Utrecht, The Netherlands (July 2005), Hakodate, Japan (May 2006), Honolulu, Hawaii, USA (May 2007), Estoril, Portugal (May 2008), Budapest, Hungary (May 2009), Toronto, Canada (May 2010), Taipei, Taiwan (May 2011), Valencia, Spain (June 2012), Minnesota, USA (May 2013), Paris, France (May 2014), Istanbul, Turkey (May 2015), Singapore (May 2016), São Paulo (2017) and Stockholm, Sweden (2018), Montreal (May 2019), Auckland (May 2020, Virtual), London (May 2021, Virtual).
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AAMAS 2022

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

technical paper

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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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This paper compares the origins, features, and status of two different tools intended to facilitate static analysis of Ada programs: ASIS and LibAdalang. It stresses the differences in principles, features,and intended usages, and shows use cases where each is more appropriate.

ASIS vs. Libadalang: a comparative assessment

Ghost entities and optimization

Vendor presentation: Vector

Augmented Reality (AR) technologies are used as human-machine interface within various types of safety-critical systems. In order to avoid unreasonable risk, it is required to detect new types of dependability threats (faults, errors, failures). These dependability threats could be introduced within the systems by new technologies. Based on the context of ImmerSAFE project and due to spread of AR technologies we target AR. In our previous work, we have designed extensions for SafeConcert metamodel to capture AR-related dependability threats (focusing on faults and failures). The extensions provide modeling and analysis capabilities that can be used for modeling and analyzing \hl{different entities and their behaviors} in AR-equipped socio-technical systems. \hl{Despite provision of various modeling and analyzing techniques, there has been no detailed investigation of providing an integrated framework for risk assessment in AR-equipped socio-technical systems.} In this paper, we provide an integrated framework based on our proposed extensions. In addition, we design and execute a case study, with our industrial partners, active in the automotive domain. We aim at validating modeling and analysis capabilities of the framework and finding out if the proposed extensions would be helpful in capturing system risks caused by new AR-related dependability threats. We conduct qualitative analysis based on Concerto-FLA analysis technique, which is an analysis technique for socio-technical systems included in CHESS toolset.

A case study for risk assessment in AR-equipped socio-technical systems

The current dependency of Artificial Intelligence (AI) systems on Cloud computing implies higher transmission latency and bandwidth consumption. Moreover, it challenges the real-time monitoring of physical objects, e.g., the Internet of Things (IoT). Edge systems bring computing closer to end devices and support time-sensitive applications. However, Edge systems struggle with state-of-the-art Deep Neural Networks (DNN) due to computational resource limitations. In this proposal, an introduced framework combines the Edge-Cloud architecture concept with BranchyNet advantages to support fault-tolerant and low-latency AI predictions. The implementation and evaluation of this framework allow assessing the benefits of running Distributed DNN (DDNN) in the Cloud-to-Things continuum. Compared to a Cloud-only deployment, the results obtained show an improvement of 45.34% in the response time. Furthermore, this proposal presents an extension for Kafka-ML that reduces rigidness over the Cloud-to-Things continuum managing and deploying DDNN.

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Reliability-oriented design of on-board satellite boot software against single event effects

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