Skip to main content

Books in Software

This collection encompasses software engineering, programming languages, and development frameworks. Showcasing best practices, innovative methodologies, and case studies, it supports developers, researchers, and educators in building reliable, efficient, and maintainable software systems. Addressing agile development, software testing, and DevOps, these resources foster technological excellence and industry readiness.

    • Theory of Structured Parallel Programming

      • 1st Edition
      • Yong Wang
      • English
      Theory of Structured Parallel Programming is a comprehensive guide to structured parallel programming corresponding to traditional structured sequential programming. The book provides readers with comprehensive coverage of theoretical foundations of structured parallel programming, including analyses of parallelism and concurrency, truly concurrent process algebras, building block-based structured parallel programming, modelling and verification of parallel programming language, modelling and verification of parallel programming patterns, as well as modeling and verification of distributed systems.There have been always two ways to approach parallel computing: one is the structured way, and the other is the graph-based (true concurrent) way. The structured way is often based on the interleaving semantics, such as process algebra CCS. Since the parallelism in interleaving semantics is not a fundamental computational pattern (the parallel operator can be replaced by alternative composition and sequential composition), the parallel operator often does not occur as an explicit operator, such as in the mainstream programming languages C, C++, Java, et al.
    • Artificial Intelligence and Machine Learning for Open-world Novelty

      • 1st Edition
      • Volume 134
      • English
      Artificial Intelligence and Machine Learning for Open-world Novelty, Volume 134 in the Advances in Computers series presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on AI and Machine Learning for Real-world problems, Graph Neural Network for learning complex problems, Adaptive Software platform architecture for Aerial Vehicle Safety Levels in real-world applications, OODA Loop for Learning Open-world Novelty Problems, Privacy-Aware Crowd Counting Methods for Real-World Environment, AI and Machine Learning for 3D Computer Vision Applications in Open-world, and PIM Hardware accelerators for real-world problems.Other sections cover Irregular Situations in Real-World Intelligent Systems, Offline Reinforcement Learning Methods for Real-world Problems, Addressing Uncertainty Challenges for Autonomous Driving in Real-World Environments, and more.
    • Internet of Things: Architectures for Enhanced Living Environments

      • 1st Edition
      • Volume 133
      • Goncalo Marques
      • English
      Internet of Things: Architectures for Enhanced Living Environments, Volume 133 presents interesting chapters on a variety of timely topics, including Explainable Artificial Intelligence for Enhanced Living Environments: A Study on User Perspective, Human behavioral anomaly pattern mining within an IoT environment: an exploratory study, Indoor Activity Localization Technologies for Assisted Living: Opportunities, Challenges, and Future Directions, Smart Indoor Air Quality Monitoring for Enhanced Living Environments and Ambient Assisted Living, Usability evaluation for the IoT use in Enhanced Living Environments, Roadmap to the elderly enhanced living and care environments: applications and challenges on the Internet of Things domain, and much more.
    • Handbook of Truly Concurrent Process Algebra

      • 1st Edition
      • Yong Wang
      • English
      Handbook of Truly Concurrent Process Algebra provides readers with a detailed and in-depth explanation of the algebra used for concurrent computing. This complete handbook is divided into five Parts: Algebraic Theory for Reversible Computing, Probabilistic Process Algebra for True Concurrency, Actors – A Process Algebra-Based Approach, Secure Process Algebra, and Verification of Patterns. The author demonstrates actor models which are captured using the following characteristics: Concurrency, Asynchrony, Uniqueness, Concentration, Communication Dependency, Abstraction, and Persistence. Every pattern is detailed according to a regular format to be understood and utilized easily, which includes introduction to a pattern and its verifications.Patter... of the vertical domains are also provided, including the domains of networked objects and resource management. To help readers develop and implement the software patterns scientifically, the pattern languages are also presented.
    • Embedded Systems

      ARM Programming and Optimization
      • 2nd Edition
      • Jason D. Bakos
      • English
      Embedded Systems: ARM Programming and Optimization, Second Edition combines an exploration of the ARM architecture with an examination of the facilities offered by the Linux operating system to explain how various features of program design can influence processor performance. The book demonstrates methods by which a programmer can optimize program code in a way that does not impact its behavior but instead improves its performance. Several applications, including image transformations, fractal generation, image convolution, computer vision tasks, and now machine learning are used to describe and demonstrate these methods. From this, the reader will gain insight into computer architecture and application design, as well as practical knowledge in embedded software design for modern embedded systems. The second edition has been expanded to include more topics of interest to upper level undergraduate courses in embedded systems.
    • Perspective of DNA Computing in Computer Science

      • 1st Edition
      • Volume 129
      • English
      DNA or Deoxyribonucleic Acid computing is an emerging branch of computing that uses DNA sequence, biochemistry, and hardware for encoding genetic information in computers. Here, information is represented by using the four genetic alphabets or DNA bases, namely A (Adenine), G (Guanine), C (Cytosine), and T (Thymine), instead of the binary representation (1 and 0) used by traditional computers. This is achieved because short DNA molecules of any arbitrary sequence of A, G, C, and T can be synthesized to order. DNA computing is mainly popular for three reasons: (i) speed (ii) minimal storage requirements, and (iii) minimal power requirements. There are many applications of DNA computing in the field of computer science. Nowadays, DNA computing is widely used in cryptography for achieving a strong security technique, so that unauthorized users are unable to retrieve the original data content. In DNA-based encryption, data are encrypted by using DNA bases (A, T, G, and C) instead of 0 and 1. As four DNA bases are used in the encryption process, DNA computing supports more randomness and makes it more complex for attackers or malicious users to hack the data. DNA computing is also used for data storage because a large number of data items can be stored inside the condensed volume. One gram of DNA holds approx DNA bases or approx 700 TB. However, it takes approx 233 hard disks to store the same data on 3 TB hard disks, and the weight of all these hard disks can be approx 151 kilos. In a cloud environment, the Data Owner (DO) stores their confidential encrypted data outside of their own domain, which attracts many attackers and hackers. DNA computing can be one of the best solutions to protect the data of a cloud server. Here, the DO can use DNA bases to encrypt the data by generating a long DNA sequence. Another application of DNA computing is in Wireless Sensor Network (WSN). Many researchers are trying to improve the security of WSN by using DNA computing. Here, DNA cryptography is used along with Secure Socket Layer (SSL) that supports a secure medium to exchange information. However, recent research shows some limitations of DNA computing. One of the critical issues is that DNA cryptography does not have a strong mathematical background like other cryptographic systems. This edited book is being planned to bring forth all the information of DNA computing. Along with the research gaps in the currently available books/literature, this edited book presents many applications of DNA computing in the fields of computer science. Moreover, research challenges and future work directions in DNA computing are also provided in this edited book.
    • Principles of Big Graph: In-depth Insight

      • 1st Edition
      • Volume 128
      • English
      Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph.
    • Engineering a Compiler

      • 3rd Edition
      • Keith D. Cooper + 1 more
      • English
      *Textbook and Academic Authors Association (TAA) Textbook Excellence Award Winner, 2024*Engineering a Compiler, Third Edition covers the latest developments in compiler technology, with new chapters focusing on semantic elaboration (the problems that arise in generating code from the ad-hoc syntax-directed translation schemes in a generated parser), on runtime support for naming and addressability, and on code shape for expressions, assignments and control-structures. Leading educators and researchers, Keith Cooper and Linda Torczon, have revised this popular text with a fresh approach to learning important techniques for constructing a modern compiler, combining basic principles with pragmatic insights from their own experience building state-of-the-art compilers.
    • MATLAB Programming for Biomedical Engineers and Scientists

      • 2nd Edition
      • Andrew P. King + 1 more
      • English
      MATLAB Programming for Biomedical Engineers and Scientists, Second Edition provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. The book explains the principles of good programming practice, while also demonstrating how to write efficient and robust code that analyzes and visualizes biomedical data. Aimed at the biomedical engineering student, biomedical scientist and medical researcher with little or no computer programming experience, this is an excellent resource for learning the principles and practice of computer programming using MATLAB. The book enables the reader to analyze problems and apply structured design methods to produce elegant, efficient and well-structured program designs, implement a structured program design in MATLAB, write code that makes good use of MATLAB programming features, including control structures, functions and advanced data types, and much more.
    • MATLAB

      A Practical Introduction to Programming and Problem Solving
      • 6th Edition
      • Dorothy C. Attaway
      • English
      MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and built-in functions to easily exploit MATLAB’s extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. The sixth edition has been updated to reflect the functionality of the current version of MATLAB (R2021a), including the introduction of machine learning concepts and the Machine Learning Toolbox, and new sections on data formats and data scrubbing.