{"title":"Towards Characterization of Edge-Cloud Continuum","authors":"Danylo Khalyeyev, T. Bures, P. Hnetynka","doi":"10.1007/978-3-031-36889-9_16","DOIUrl":"https://doi.org/10.1007/978-3-031-36889-9_16","url":null,"abstract":"","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"393 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126925738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analyzing the Evolution of Inter-package Dependencies in Operating Systems: A Case Study of Ubuntu","authors":"Victor Prokhorenko, Chadni Islam, M. A. Babar","doi":"10.48550/arXiv.2307.04458","DOIUrl":"https://doi.org/10.48550/arXiv.2307.04458","url":null,"abstract":"An Operating System (OS) combines multiple interdependent software packages, which usually have their own independently developed architectures. When a multitude of independent packages are placed together in an OS, an implicit inter-package architecture is formed. For an evolutionary effort, designers/developers of OS can greatly benefit from fully understanding the system-wide dependency focused on individual files, specifically executable files, and dynamically loadable libraries. We propose a framework, DepEx, aimed at discovering the detailed package relations at the level of individual binary files and their associated evolutionary changes. We demonstrate the utility of DepEx by systematically investigating the evolution of a large-scale Open Source OS, Ubuntu. DepEx enabled us to systematically acquire and analyze the dependencies in different versions of Ubuntu released between 2005 (5.04) to 2023 (23.04). Our analysis revealed various evolutionary trends in package management and their implications based on the analysis of the 84 consecutive versions available for download (these include beta versions). This study has enabled us to assert that DepEx can provide researchers and practitioners with a better understanding of the implicit software dependencies in order to improve the stability, performance, and functionality of their software as well as to reduce the risk of issues arising during maintenance, updating, or migration.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123014450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"DAT: Data Architecture Modeling Tool for Data-Driven Applications","authors":"Moamin Abughazala, H. Muccini, Mohammad Sharaf","doi":"10.13140/RG.2.2.23556.81286","DOIUrl":"https://doi.org/10.13140/RG.2.2.23556.81286","url":null,"abstract":"Data is the key to success for any Data-Driven Organization, and managing it is considered the most challenging task. Data Architecture (DA) focuses on describing, collecting, storing, processing, and analyzing the data to meet business needs. In this tool demo paper, we present the DAT, a model-driven engineering tool enabling data architects, data engineers, and other stakeholders to describe how data flows through the system and provides a blueprint for managing data that saves time and effort dedicated to Data Architectures for IoT applications. We evaluated this work by modeling five case studies, receiving expressiveness and ease of use feedback from two companies, more than six researchers, and eighteen undergraduate students from the software architecture course","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116904233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using I4.0 digital twins in agriculture","authors":"R. Falcão, Raghad Matar, Bernd Rauch","doi":"10.48550/arXiv.2301.09682","DOIUrl":"https://doi.org/10.48550/arXiv.2301.09682","url":null,"abstract":"Agriculture is a huge domain where an enormous landscape of systems interact to support agricultural processes, which are becoming increasingly digital. From the perspective of agricultural service providers, a prominent challenge is interoperability. In the Fraunhofer lighthouse project Cognitive Agriculture (COGNAC), we investigated how the usage of Industry 4.0 digital twins (I4.0 DTs) can help overcome this challenge. This paper contributes architecture drivers and a solution concept using I4.0 DTs in the agricultural domain. Furthermore, we discuss the opportunities and limitations offered by I4.0 DTs for the agricultural domain.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134005169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trust Management in the Internet of Everything","authors":"Barbora Buhnova","doi":"10.48550/arXiv.2212.14688","DOIUrl":"https://doi.org/10.48550/arXiv.2212.14688","url":null,"abstract":"Digitalization is leading us towards a future where people, processes, data and things are not only interacting with each other, but might start forming societies on their own. In these dynamic systems enhanced by artificial intelligence, trust management on the level of human-to-machine as well as machine-to-machine interaction becomes an essential ingredient in supervising safe and secure progress of our digitalized future. This tutorial paper discusses the essential elements of trust management in complex digital ecosystems, guiding the reader through the definitions and core concepts of trust management. Furthermore, it explains how trust-building can be leveraged to support people in safe interaction with other (possibly autonomous) digital agents, as trust governance may allow the ecosystem to trigger an auto-immune response towards untrusted digital agents, protecting human safety.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"70 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126981685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Methodical Approach for Centralization Evaluation of Modern Automotive E/E Architectures","authors":"Lucas Mauser, S. Wagner, P. Ziegler","doi":"10.48550/arXiv.2209.14118","DOIUrl":"https://doi.org/10.48550/arXiv.2209.14118","url":null,"abstract":"Centralization is considered as a key enabler to master the CPU-intensive features of the modern car. The development and architecture change towards the next generation car is influenced by ADAS, connectivity, infotainment and the consequential need for cyber-security. There is already a high number of papers describing future centralized E/E architectures and technical instruments for centralization. What is missing is a methodical approach to analyze an existing system and find its potential for centralization on the function level. This paper introduces an approach, which serves a system designer or engineer to abstract functions and thus enables to shape a more centralized system architecture. The commonly known E/E architecture designs and the named instruments of current research are the basis for this abstraction. Based on the approach, new system architecture proposals can be set up to discuss and outweigh advantages and disadvantages of those. The approach is validated by applying it step by step to the inlet's derating function of a modern electric vehicle. A following discussion points out that many different factors affect the potential for centralization and centralization may not be the future of every function and system in general.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132021748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick Flynn, T. Vanderbruggen, C. Liao, Pei-Hung Lin, M. Emani, Xipeng Shen
{"title":"Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines","authors":"Patrick Flynn, T. Vanderbruggen, C. Liao, Pei-Hung Lin, M. Emani, Xipeng Shen","doi":"10.48550/arXiv.2208.05596","DOIUrl":"https://doi.org/10.48550/arXiv.2208.05596","url":null,"abstract":"Programming Language Processing (PLP) using machine learning has made vast improvements in the past few years. Increasingly more people are interested in exploring this promising field. However, it is challenging for new researchers and developers to find the right components to construct their own machine learning pipelines, given the diverse PLP tasks to be solved, the large number of datasets and models being released, and the set of complex compilers or tools involved. To improve the findability, accessibility, interoperability and reusability (FAIRness) of machine learning components, we collect and analyze a set of representative papers in the domain of machine learning-based PLP. We then identify and characterize key concepts including PLP tasks, model architectures and supportive tools. Finally, we show some example use cases of leveraging the reusable components to construct machine learning pipelines to solve a set of PLP tasks.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121290022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu, H. Do, Sofiane Laridi, Alexander Weber, Claudia Nieder'ee, Thomas Hildebrandt
{"title":"Developing an AI-enabled IIoT platform - Lessons learned from early use case validation","authors":"Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu, H. Do, Sofiane Laridi, Alexander Weber, Claudia Nieder'ee, Thomas Hildebrandt","doi":"10.48550/arXiv.2207.04515","DOIUrl":"https://doi.org/10.48550/arXiv.2207.04515","url":null,"abstract":"For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.","PeriodicalId":386831,"journal":{"name":"European Conference on Software Architecture","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127970659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}