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Books in Software engineering

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    • Synthetic Media, Deepfakes, and Cyber Deception

      • 1st Edition
      • May 1, 2026
      • Cameron H. Malin + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 3 8 8 7 1
      • eBook
        9 7 8 0 4 4 3 2 3 8 8 8 8
      Synthetic Media, Deepfakes, and Cyber Deception: Attacks, Analysis, and Defenses introduces the only analytical Synthetic Media Analysis Framework (SMAF) to help describe cyber threats and help security professionals anticipate and analyze attacks. This framework encompasses seven dimensions: Credibility, Control, Medium, Interactivity, Familiarity, Intended Target, and Evocation. Synthetic media is a broad term that encompasses the artificial manipulation, modification, and production of information, covering a spectrum from audio-video deepfakes to text-based chatbots. Synthetic media provides cyber attackers and scammers with a game-changing advantage over traditional ROSE attacks because they have the potential to convincingly impersonate close associates through text, imagery, voice, and video.This burgeoning threat has yet to be meaningfully addressed through any written treatment on the topic. The book is co-authored by three cyber influence and deception experts who have gained deep knowledge and experience on the topic through diverse, true operational pathways and backgrounds. The diversity and perspectives of the author team makes the content in the book the broadest and deepest treatment of synthetic media attacks available to readers.

    • Digital Twins

      • 1st Edition
      • May 1, 2026
      • Bedir Tekinerdogan + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 5 5 7 3 5
      • eBook
        9 7 8 0 4 4 3 4 5 5 7 2 8
      Digital Twins: Core Principles and AI Integration provides a comprehensive overview of digital twin technology, a cutting-edge innovation that bridges the physical and digital worlds. As digital twin technology evolves, its integration with various advanced digital solutions is becoming essential for achieving real-time insights and autonomous decision-making. Challenges include understanding the interoperability of these technologies, managing data complexity, ensuring security, and optimizing for low-latency environments. The authors demystify digital twin technology, providing a clear framework for understanding how to effectively implement and utilize digital twins. The book addresses common challenges such as data integration, security, scalability, and the alignment of digital twin models with actual physical processes. After presenting core concepts of digital twins for software engineering, the book progresses to a section on integration with advanced digital solutions such as AI, IoT, Cloud computing, Big Data Analytics, and Extended Reality (XR). Next, the authors provide readers with a thorough presentation of digital twins applications in a variety of settings and industry/research topics. Finally, the book concludes with a discussion of challenges and solutions, along with future trends in digital twins research and development.

    • Engineering Generative AI-Based Software

      • 1st Edition
      • May 1, 2026
      • Miroslaw Staroń
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 6 0 6 4
      • eBook
        9 7 8 0 4 4 3 2 7 6 0 7 1
      Software Engineering professionals now face challenges in incorporating GAI into the products and programs they are developing. At this point, the knowledge about developing AI-based software is mostly based on classical AI, i.e., non-generative ML systems. Developers know how to use machine learning and, to some extent, how to include it in production systems. Engineering Generative-AI Based Software takes software development to the next level by using generative AI instead. Readers learn how to use text, image and audio models as part of larger software systems. The book discusses both the process of developing such software and the architectures for this kind of software, combining theory with practice. Generative AI software is gaining popularity thanks to such models as GPT-4 or Llama. More and more products use them as part of their feature portfolio, but this software is often limited to web applications or recommendation systems. Author Miroslav Staron shows readers how to tackle the challenges of professionally engineering generative AI-based systems. The book starts by reviewing the most relevant models and technologies in this area, both theoretically and practically. Once readers know the technologies, the book goes into details of software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, various architectural styles and tactics for such systems, and different programming platforms. The book also shows how to create robust licensing models and the technology to support them. Finally, readers learn how to manage data, both during the training and also when generating new data, as well as how to use the generated data and user feedback to constantly evolve generative AI-based software.

    • Pioneering Autonomous Technology: A Deep dive into Hyper Automation

      • 1st Edition
      • Volume 143
      • May 1, 2026
      • English
      • Hardback
        9 7 8 0 4 4 3 3 1 7 1 0 1
      • eBook
        9 7 8 0 4 4 3 3 1 7 1 1 8
      Pioneering Autonomous Technology: A Deep dive into Hyper Automation, Volume 143 in the Advances in Computers series, showcases the transformative role of artificial intelligence, deep learning, and machine learning in creating safer, more efficient, and socially inclusive environments. This volume explores how autonomous technologies are reshaping healthcare, transportation, agriculture, and urban living. Chapters cover cutting-edge applications such as deep learning–based medical diagnostics for chronic diseases, retinal biomarkers for early detection of Alzheimer’s and Parkinson’s, and superior CNN approaches for agricultural automation. The book highlights advances in autonomous vehicles, from industry trends and electric vehicle integration to safety and societal impacts, as well as essential topics like cybersecurity challenges and machine learning–driven life expectancy prediction. Broader societal applications include income inequality modeling, sentiment analysis in Indian languages, and IoT-based smart city initiatives, offering readers a comprehensive perspective on the future of intelligent and autonomous systems.

    • Development of Multi-Agent Systems Infrastructures

      • 1st Edition
      • April 15, 2026
      • Andrei Olaru
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 4 9 5 5
      • eBook
        9 7 8 0 4 4 3 4 0 4 9 6 2
      Development of Multi-Agent Systems Infrastructure: A Practical Approach discusses modular infrastructure to underpin the deployment of real-life software applications, while implementing well-defined theoretical models. The book addresses the challenges associated with deploying multi-agent systems (MAS) and offers a practical approach to how solutions can be developed. The book is based on the author’s experience with building the FLASH-MAS framework (A Fast Lightweight Agent Shell) and other related MAS projects. Many applications are built using the paradigm of autonomous agents in very different fields, including manufacturing, robotics, health care, supply chain management, and more. Agents may be deployed individually, may be distributed over the network, or may be used in great numbers to simulate complex interactions, but there are always some invariants in the functionality of a multi-agent system. A multi-agent system contains other entities beside the agents: the environment, support infrastructures, and units continuously processing data; these have their own lifecycle and needs for interaction. Deployment, maintenance, and monitoring of multi-agent systems brings about many practical challenges, such as dealing with the interaction between entities, the construction, deployment, and eventual destruction of individual entities, the management of an open system, and the robustness of the system as a whole. Some of these challenges are common to many or all applications, hence this book comes to the assistance of multi-agent system developers by offering tools and frameworks for the development and deployment of such systems. Development of Multi-Agent Systems Infrastructure is divided into three main parts, dealing with: models and languages for multi-agent systems; the deployment and interaction between entities; and practical aspects of implementing modern MAS frameworks. FLASH-MAS is a framework built on modularity, so the book presents the solutions the author has identified in a modular manner, meaning that they can be replicated and used independently from one another.

    • AI, Blockchain and Social Network on Urban Crisis Management: Leveraging Emerging Technologies for Disaster Response and Resilience in Smart Cities

      • 1st Edition
      • Volume 142
      • April 1, 2026
      • English
      • Hardback
        9 7 8 0 4 4 3 3 1 3 6 8 4
      • eBook
        9 7 8 0 4 4 3 3 1 3 6 9 1
      AI, Blockchain and Social Network on Urban Crisis Management, Volume 142 in the Advances in Computers series, examines how cutting-edge digital technologies are reshaping disaster preparedness and response. This volume highlights the convergence of artificial intelligence, blockchain, and social network analysis to predict, prevent, and manage urban crises. Chapters explore diverse applications, from AI-driven deforestation monitoring in the Colombian Amazon and diffusion modeling for enhanced oil recovery, to blockchain-based citizen voting systems, metaverse-enabled disaster management, and graph-theoretic approaches for resource mobilization. Ethical AI for law enforcement training, social media’s role in disaster resilience, and innovative methods such as YOLO-based pothole detection further showcase how these technologies support sustainable cities and green energy initiatives. Collectively, the volume provides a multidisciplinary perspective on building smarter, safer, and more resilient urban environments.

    • Mastering DevOps

      • 1st Edition
      • April 1, 2026
      • Chinmaya Kumar Dehury + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 5 0 3 2 7
      • eBook
        9 7 8 0 4 4 3 4 5 0 3 3 4
      Mastering DevOps: A Cloud Engineering and Data Science Perspective addresses the challenge of understanding and implementing DevOps in an era of rapid technological advancement, where cloud-based infrastructure and data science applications have become integral to many organizations. The book covers the specific requirements of these fields, such as scalability, automation, and managing large-scale data and containerized applications. Mastering DevOps offers readers the knowledge and skills necessary to build, deploy, and manage DevOps practices effectively within the context of cloud engineering and data science. The book focuses on DevOps principles while integrating core technologies such as cloud computing, microservices, and continuous integration/continuo... delivery (CI/CD). Additionally, the book provides coverage of a DevOps approach tailored to data science by covering recent advancements and explaining their relevance in a DevOps environment. The structure of the book is divided into four units, each progressively building on the concepts of the previous one. The first unit (Unit 1: Foundations of DevOps) provides the fundamental principles of DevOps, including its history, planning, and essential tools like Git. The second unit (Unit 2: Core Technologies and Architectures) introduces the core technologies and architectures that power modern DevOps, such as microservices, cloud computing, and containerization. The third unit (Unit 3: CI/CD Practices and Automation) focuses on the practical implementation of DevOps, exploring key practices like continuous integration, automation, and monitoring. Finally, the fourth unit (Unit 4: Advanced Topics and Data Science Perspective) delves into advanced topics and future trends, such as deployment strategies and the extension of DevOps principles to data science and other narrowed-down domains.

    • Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices

      • 1st Edition
      • Volume 141
      • March 1, 2026
      • English
      • Hardback
        9 7 8 0 4 4 3 2 2 4 0 1 0
      • eBook
        9 7 8 0 4 4 3 2 2 4 0 2 7
      Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices, Volume 141 in the Advances in Computers series, explores the convergence of artificial intelligence, machine learning, and modern software engineering practices. Chapters in this new release include Demystifying the Cloud-native Artificial Intelligence (CNAI) Paradigm, Articulating Machine and Deep Learning Models for Next-Generation Software Development, Delineating Artificial Intelligence (AI) and Its Potentials for Automated Software Engineering, Leveraging Machine and Deep Learning (ML/DL) Algorithms towards AI Models for Automating Software Development, and more.Other sections cover Artificial Intelligence (AI) Technologies and Tools for Accelerated Software Development, Demystifying the Agentic AI Paradigm for Accelerated Software Engineering, Detailing AI Techniques and Tools for Software Engineering Acceleration and Automation, Generative AI Tools for Accelerated Software Engineering, Empowering Software Engineering Automation through Explainable AI, and much more.

    • Consensus

      • 1st Edition
      • December 1, 2025
      • Ali Ahmadian + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 4 3 9 9
      • eBook
        9 7 8 0 4 4 3 4 0 4 4 0 5
      Consensus: Fueling Blockchain Innovation and DApp Expansion explores the complexities of consensus mechanisms in order to shed light on emerging trends, best practices, and real-world applications that can fuel blockchain innovation while encouraging the dissemination of DApps across various industries. Additionally, the book bridges a crucial gap in the literature by providing in-depth insights into the role of consensus mechanisms in shaping the future of blockchain technology and decentralized applications. This book delves into the fundamentals of blockchain technology along with the roles and significance of vital consensus mechanisms, their underlying principles, formal specifications, functional characteristics, architecture, frameworks, and potential across diverse blockchain applications. Moreover, the book meticulously explores classification, performance metrics, and design parameters. It offers a comprehensive comparative analysis of these mechanisms, shedding light on their computational and communication complexity, strengths, weaknesses, and suitability. Additionally, the book delves into future research directions, highlighting emerging trends and areas requiring further investigation. It also addresses the efforts underway to address existing challenges and open issues within the realm of consensus mechanisms, ensuring a comprehensive understanding of the state-of-the-art in this pivotal aspect of blockchain technology. Due to the wide range of availability and evolving new consensus mechanisms, selecting an optimal and suitable consensus for a specific blockchain application is one of the crucial challenges in the development and innovation of blockchain systems. This book has also a discussion on appropriate selection algorithms based on multi-attribute decision-making for specific blockchain systems and DApps development.

    • Quantum Computing

      • 1st Edition
      • June 30, 2025
      • Rajkumar Buyya + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 0 9 6 1
      • eBook
        9 7 8 0 4 4 3 2 9 0 9 7 8
      Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers.This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.