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Books in Software engineering

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    • 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. This volume provides a comprehensive overview of how AI technologies—ranging from traditional machine learning and deep learning to generative and explainable AI—are transforming every stage of software development and deployment. Chapters cover agentic AI, MLOps, DevSecOps, CI/CD, and Kubernetes-based scalable systems, emphasizing real-world applications such as cloud-native ERP systems, software testing automation, and secrets management. The volume also addresses pressing concerns around ethical AI, responsible automation, and data privacy, offering a well-rounded perspective on the future of intelligent, agile, and secure software engineering.

    • 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.

    • 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.

    • Programming Language Pragmatics

      • 5th Edition
      • January 9, 2025
      • Michael Scott + 1 more
      • English
      • Paperback
        9 7 8 0 3 2 3 9 9 9 6 6 3
      • eBook
        9 7 8 0 3 2 3 9 8 4 2 3 2
      Programming Language Pragmatics is the most comprehensive programming language textbook available today, with nearly 1000 pages of content in the book, plus hundreds more pages of reference materials and ancillaries online. Michael Scott takes theperspective that language design and language implementation are tightly interconnected, and that neither can be fully understood in isolation. In an approachable, readable style, he discusses more than 50 languages in the context of understanding how code isinterpreted or compiled, providing an organizational framework for learning new languages, regardless of platform. This edition has been thoroughly updated to cover the most recent developments in programming language design and provides both a solid understanding of the most important issues driving software development today

    • Soft Computing in Smart Manufacturing and Materials

      • 1st Edition
      • January 20, 2025
      • Sudan Jha + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 9 2 7 8
      • eBook
        9 7 8 0 4 4 3 2 9 9 2 8 5
      Soft Computing in Smart Manufacturing and Materials explains the role of soft computing in the manufacturing industries. It presents the techniques, concepts and design principles behind smart soft computing, and describes how they can be applied in the development and manufacture of smart materials. It provides perspectives for design and commissioning of intelligent applications, including in health care, agriculture, and production assembly, and reviews the latest intelligent technologies and algorithms related to the methodologies of monitoring and mitigation of sustainable engineering.

    • Quantum Process Algebra

      • 1st Edition
      • March 6, 2025
      • Yong Wang
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 5 1 3 5
      • eBook
        9 7 8 0 4 4 3 2 7 5 1 4 2
      Quantum Process Algebra introduces readers to the algebraic properties and laws for quantum computing. The book provides readers with all aspects of algebraic theory for quantum computing, including the basis of semantics and axiomatization for quantum computing. With the assumption of a quantum system, readers will learn to solve the modeling of the three main components in a quantum system: the unitary operator, quantum measurement, and quantum entanglement, with full support of quantum and classical computing in closed systems. Next, the book establishes the relationship between probabilistic quantum bisimilarity and classical probabilistic bisimilarity, including strong probabilistic bisimilarity and weak probabilistic bisimilarity, which makes an axiomatization of quantum processes possible. With this framework, quantum and classical computing mixed processes are unified with the same structured operational semantics. Finally, the book establishes a series of axiomatizations of quantum process algebras. These process algebras support nearly all the main computation properties. Quantum and classical computing in closed quantum systems are unified with the same equational logic and the same structured operational semantics under the framework of ACP-like probabilistic process algebra. This unification means that the mathematics in the book can be used widely for verification of quantum and classical computing mixed systems, for example, most quantum communication protocols. ACP-like axiomatization also inherits the advantages of ACP, for example, and modularity means that it can be extended in an elegant way.

    • Python Fast Track

      • 1st Edition
      • June 14, 2025
      • Sanjiban Sekhar Roy + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 8 2 3 6
      • eBook
        9 7 8 0 4 4 3 3 3 8 2 4 3
      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.

    • Probability for Deep Learning Quantum

      • 1st Edition
      • January 21, 2025
      • Charles R. Giardina
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 8 3 4 4
      • eBook
        9 7 8 0 4 4 3 2 4 8 3 5 1
      Probability for Deep Learning Quantum provides readers with the first book to address probabilistic methods in the deep learning environment and the quantum technological area simultaneously, by using a common platform: the Many-Sorted Algebra (MSA) view. While machine learning is created with a foundation of probability, probability is at the heart of quantum physics as well. It is the cornerstone in quantum applications. These applications include quantum measuring, quantum information theory, quantum communication theory, quantum sensing, quantum signal processing, quantum computing, quantum cryptography, and quantum machine learning. Although some of the probabilistic methods differ in machine learning disciplines from those in the quantum technologies, many techniques are very similar.Probability is introduced in the text rigorously, in Komogorov’s vision. It is however, slightly modified by developing the theory in a Many-Sorted Algebra setting. This algebraic construct is also used in showing the shared structures underlying much of both machine learning and quantum theory. Both deep learning and quantum technologies have several probabilistic and stochastic methods in common. These methods are described and illustrated using numerous examples within the text. Concepts in entropy are provided from a Shannon as well as a von-Neumann view. Singular value decomposition is applied in machine learning as a basic tool and presented in the Schmidt decomposition. Besides the in-common methods, Born’s rule as well as positive operator valued measures are described and illustrated, along with quasi-probabilities. Author Charles R. Giardina provides clear and concise explanations, accompanied by insightful and thought-provoking visualizations, to deepen your understanding and enable you to apply the concepts to real-world scenarios.

    • 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.