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Books in Software engineering

  • Digital Twins

    Core Principles and AI Integration
    • 1st Edition
    • Bedir Tekinerdogan + 1 more
    • English
    Digital Twins: Core Principles, System Engineering, and AI Integration provides a comprehensive overview of digital twin technology, a cutting-edge innovation that bridges the physical and digital worlds. 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 discusses 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. 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.

  • Pioneering Autonomous Technology: A Deep Dive into Hyper Automation

    • 1st Edition
    • Volume 143
    • English
    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 important topics such as a Survey on Deep Learning Based Autonomous Medical Diagnosis Models for Chronic Disease Identification, Human-Robot Interaction: Ensuring Safe and Effective Coordination, Blazing Trails: Cutting-Edge Technologies Revolutionizing Forest Fire Screening, Connected Communities: Fostering Social Inclusion and Equity in Smart Cities through IoT Integration, and much more.Additional chapters cover a Preliminary Study of Retinal Biomarkers Detection on Fundus Images for the Diagnosis of Alzheimer’s and Parkinson’s Diseases, Deep Learning Driven Classification of Sweet Lime Leaves: A Superior CNN Approach for Agricultural Automation, Machine Learning in Healthcare: Advancements, Applications, and Challenges, Feature Extraction and Object Recognition in Autonomous Systems, The Future of Autonomous Vehicles: Industry Trends, Technologies, and Challenges, Autonomous Systems: Shaping the Future of Industries and Transportation, and many other topics that will be of interest to readers.

  • Mastering DevOps

    A Cloud Engineering and Data Science Perspective
    • 1st Edition
    • Chinmaya Kumar Dehury + 1 more
    • English
    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. Content 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. Specific topics cover fundamental principles, including history, planning, and essential tools like Git, introduce the core technologies and architectures that power modern DevOps, such as microservices, cloud computing, and containerization, and focus on the practical implementation of DevOps, exploring key practices like continuous integration, automation, and monitoring. Finally, the book 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.

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

    • 1st Edition
    • Volume 142
    • English
    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.

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

    • 1st Edition
    • Volume 141
    • English
    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.

  • Engineering Generative AI-Based Software

    • 1st Edition
    • Miroslaw Staroń
    • English
    Engineering Generative-AI Based Software discusses both the process of developing this kind of AI-based software and its architectures, combining theory with practice. Sections review the most relevant models and technologies, detail software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, explore various architectural styles and tactics for such systems, including different programming platforms, and show how to create robust licensing models. Finally, readers learn how to manage data, both during training and when generating new data, and how to use generated data and user feedback to constantly evolve generative AI-based software.As generative AI software is gaining popularity thanks to such models as GPT-4 or Llama, this is a welcomed resource on the topics explored. With these systems becoming increasingly important, Software Engineering Professionals will need to know how to overcome challenges in incorporating GAI into the products and programs they develop.

  • Consensus

    Fueling Blockchain Innovation and DApp Expansion
    • 1st Edition
    • Ali Ahmadian + 3 more
    • English
    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

    Principles and Paradigms
    • 1st Edition
    • Rajkumar Buyya + 1 more
    • English
    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.

  • Python Fast Track

    A Complete Guide to Rapidly Mastering and Applying Python Programming
    • 1st Edition
    • Sanjiban Sekhar Roy + 2 more
    • English
    Python Fast Track: A Complete Guide to Rapidly Mastering and Applying Python Programming adopts a simplified writing style and provides clear explanations to ensure ease of understanding, making it an ideal resource for those new to Python. Starting with the basics, the book covers fundamental concepts such as variables, data types, printing and prompting, lists, dictionaries, tuples, control structure, functions, and object-oriented concepts. The book includes everything you need to understand and apply more advanced programming techniques such as file handling, exception handling, and regex.This great resource is created especially for those who want to apply Python for their research and professional work in scientific computing, data analysis and machine learning, including chapters on NumPy and Pandas, two of the most popular Python application libraries. It demonstrates how to effectively master key applications of Python such as web development, software creation, task automation, and data analysis. The book covers data analysis and machine learning tasks that greatly benefit from Python, thanks to libraries such as TensorFlow and Keras that enable efficient coding.

  • The Convergence of Artificial Intelligence (AI) and 6G Communication Networks: The Needs and Implications

    • 1st Edition
    • Volume 139
    • English
    Advances in Computers, Volume 139 focuses on the convergence of Artificial Intelligence (AI) and 6G communication networks, addressing key advancements and implications across various fields. It explores cybersecurity challenges in 5G networks, solutions for 5G performance evaluation, and the transition to 5G-Advanced. The role of AI in enhancing 6G network performance, resource allocation, and management is discussed alongside the technical foundations of 6G and its ability to power edge AI applications. The volume highlights how 6G will transform industries like logistics through automation and AI-driven decision-making, while also covering strategic management perspectives on AI-driven innovations. Sustainability is a key theme, with discussions on energy-efficient cloud and quantum data centers, as well as the integration of green innovations into AI-6G synergy. The metaverse and its reliance on 5G and 6G for immersive experiences are reviewed, alongside the revolutionary potential of quantum computing in 6G networks. The practical applications of AI, such as a CNN-based model for brain tumor detection using 5G edge cloud, and federated learning for 6G, demonstrate the technology's impact on healthcare and data privacy. Additionally, the volume delves into 6G’s role in enabling next-generation metaverse systems and AI-powered telemedicine, while providing insights into the architecture, communication systems, and industrial use cases of 6G. It concludes by summarizing the advancements, advantages, and challenges of 6G, offering a comprehensive view of its future impact on global connectivity.