Software Architecture. ECSA 2023 Tracks, Workshops, and Doctoral Symposium
Software Architecture. ECSA 2023 Tracks, Workshops, and Doctoral Symposium

Author: Bedir Tekinerdoğan

Publisher: Springer

Published: 2024-08-25

Total Pages: 0

ISBN-13: 9783031663253

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This book constitutes the refereed proceedings of the tracks and workshops which complemented the 17th European Conference on Software Architecture, ECSA 2023, held in Istanbul, Turkey, in September 2023. The 29 full papers included in this book were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: AMP; CASA; DE & I Track; DeMeSSA; FAACS; QUALIFIER; TwinArch; Tools and Demos; Industry Track; and Doctoral Symposium.

Software Architecture
Software Architecture

Author: Bedir Tekinerdogan

Publisher: Springer Nature

Published: 2023-09-07

Total Pages: 374

ISBN-13: 3031425928

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This book constitutes the refereed proceedings of the 17th International Conference on Software Architecture, ECSA 2023, held in Istanbul, Turkey, in September 2023. The 16 full papers and the 9 short papers included in this volume were carefully reviewed and selected from 71 submissions. They address the most recent, innovative, and significant findings and experiences in the field of software architecture research and practice.

Software Architecture. ECSA 2022 Tracks and Workshops
Software Architecture. ECSA 2022 Tracks and Workshops

Author: Thais Batista

Publisher: Springer Nature

Published: 2023-07-15

Total Pages: 492

ISBN-13: 3031368894

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This book constitutes the refereed proceedings of the tracks and workshops which complemented the 16th European Conference on Software Architecture, ECSA 2022, held in Prague, Czech Republic, in September 2022. The 26 full papers presented together with 4 short papers and 2 tutorial papers in this volume were carefully reviewed and selected from 61 submissions. Papers presented were accepted into the following tracks and workshops: Industry track; Tools and Demonstrations Track; Doctoral Symposium; Tutorials; 8th International Workshop on Automotive System/Software Architectures (WASA); 5th Context-Aware, Autonomous and Smart Architectures International Workshop (CASA); 6th International Workshop on Formal Approaches for Advanced Computing Systems (FAACS); 3rd Workshop on Systems, Architectures, and Solutions for Industry 4.0 (SASI4); 2nd International Workshop on Designing and Measuring Security in Software Architectures (DeMeSSA); 2nd International Workshop on Software Architecture and Machine Learning (SAML); 9th Workshop on Software Architecture Erosion and Architectural Consistency (SAEroCon); 2nd International Workshop on Mining Software Repositories for Software Architecture (MSR4SA); and 1st International Workshop on Digital Twin Architecture (TwinArch).

Self-Aware Computing Systems
Self-Aware Computing Systems

Author: Samuel Kounev

Publisher: Springer

Published: 2017-01-30

Total Pages: 0

ISBN-13: 9783319474724

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This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing relates to many existing subfields of computer science, especially software engineering. It describes architectures and algorithms for self-aware systems as well as the benefits and pitfalls of self-awareness, and reviews much of the latest relevant research across a wide array of disciplines, including open research challenges. The chapters of this book are organized into five parts: Introduction, System Architectures, Methods and Algorithms, Applications and Case Studies, and Outlook. Part I offers an introduction that defines self-aware computing systems from multiple perspectives, and establishes a formal definition, a taxonomy and a set of reference scenarios that help to unify the remaining chapters. Next, Part II explores architectures for self-aware computing systems, such as generic concepts and notations that allow a wide range of self-aware system architectures to be described and compared with both isolated and interacting systems. It also reviews the current state of reference architectures, architectural frameworks, and languages for self-aware systems. Part III focuses on methods and algorithms for self-aware computing systems by addressing issues pertaining to system design, like modeling, synthesis and verification. It also examines topics such as adaptation, benchmarks and metrics. Part IV then presents applications and case studies in various domains including cloud computing, data centers, cyber-physical systems, and the degree to which self-aware computing approaches have been adopted within those domains. Lastly, Part V surveys open challenges and future research directions for self-aware computing systems. It can be used as a handbook for professionals and researchers working in areas related to self-aware computing, and can also serve as an advanced textbook for lecturers and postgraduate students studying subjects like advanced software engineering, autonomic computing, self-adaptive systems, and data-center resource management. Each chapter is largely self-contained, and offers plenty of references for anyone wishing to pursue the topic more deeply.

Continuous Architecture in Practice
Continuous Architecture in Practice

Author: Eoin Woods

Publisher: Addison-Wesley Professional

Published: 2021-05-26

Total Pages: 449

ISBN-13: 0136523684

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Update Your Architectural Practices for New Challenges, Environments, and Stakeholder Expectations "I am continuously delighted and inspired by the work of these authors. Their first book laid the groundwork for understanding how to evolve the architecture of a software-intensive system, and this latest one builds on it in some wonderfully actionable ways." --Grady Booch, Chief Scientist for Software Engineering, IBM Research Authors Murat Erder, Pierre Pureur, and Eoin Woods have taken their extensive software architecture experience and applied it to the practical aspects of software architecture in real-world environments. Continuous Architecture in Practice provides hands-on advice for leveraging the continuous architecture approach in real-world environments and illuminates architecture's changing role in the age of Agile, DevOps, and cloud platforms. This guide will help technologists update their architecture practice for new software challenges. As part of the Vaughn Vernon Signature Series, this title was hand-selected for the practical, delivery-oriented knowledge that architects and software engineers can quickly apply. It includes in-depth guidance for addressing today's key quality attributes and cross-cutting concerns such as security, performance, scalability, resilience, data, and emerging technologies. Each key technique is demonstrated through a start-to-finish case study reflecting the authors' deep experience with complex software environments. Key topics include: Creating sustainable, coherent systems that meet functional requirements and the quality attributes stakeholders care about Understanding team-based software architecture and architecture as a "flow of decisions" Understanding crucial issues of data management, integration, and change, and the impact of varied data technologies on architecture Architecting for security, including continuous threat modeling and mitigation Architecting for scalability and resilience, including scaling microservices and serverless environments Using architecture to improve performance in continuous delivery environments Using architecture to apply emerging technologies successfully Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Federated Learning Systems
Federated Learning Systems

Author: Muhammad Habib ur Rehman

Publisher: Springer Nature

Published: 2021-06-11

Total Pages: 207

ISBN-13: 3030706044

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This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.