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Code Generation, Analysis Tools, and Testing for Quality
Despite the advances that have been made in programming, there is still a lack of sufficient methods for quality control. While code standards try to force programmers to follow a specific set of rules, few tools exist that really deal with automatic refactoring of this code, and evaluation of the coverage of these tests is still a challenge. Code Generation, Analysis Tools, and Testing for Quality is an essential reference source that discusses the generation and writing of computer programming and methods of quality control such as analysis and testing. Featuring research on topics such as programming languages, quality assessment, and automated development, this book is ideally designed for academicians, practitioners, computer science teachers, enterprise developers, and researchers seeking coverage on code auditing strategies and methods.
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Channel Codes
Channel coding lies at the heart of digital communication and data storage. Fully updated, including a new chapter on polar codes, this detailed introduction describes the core theory of channel coding, decoding algorithms, implementation details, and performance analyses. This new edition includes over 50 new end-of-chapter problems and new figures and worked examples throughout. The authors emphasize the practical approach and present clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes, detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, product codes as well as polar codes for error correction and detection, providing a one-stop resource for classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design.
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Quantum Codes for Topological Quantum Computation
This book offers a structured algebraic and geometric approach to the classification and construction of quantum codes for topological quantum computation. It combines key concepts in linear algebra, algebraic topology, hyperbolic geometry, group theory, quantum mechanics, and classical and quantum coding theory to help readers understand and develop quantum codes for topological quantum computation.One possible approach to building a quantum computer is based on surface codes, operated as stabilizer codes. The surface codes evolved from Kitaev's toric codes, as a means to developing models for topological order by using qubits distributed on the surface of a toroid. A significant advantage of surface codes is their relative tolerance to local errors. A second approach is based on color codes, which are topological stabilizer codes defined on a tessellation with geometrically local stabilizer generators. This book provides basic geometric concepts, like surface geometry, hyperbolic geometry and tessellation, as well as basic algebraic concepts, like stabilizer formalism, for the construction of the most promising classes of quantum error-correcting codes such as surfaces codes and color codes.The book is intended for senior undergraduate and graduate students in Electrical Engineering and Mathematics with an understanding of the basic concepts of linear algebra and quantum mechanics.
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Unifying Business, Data, and Code
How can we harness the powerful principles of intelligence to foster innovation and collaboration, especially among non-data scientists? This book outlines a practical methodology to help you learn fundamental concepts underlying the study of intelligence, including AI and human intelligence, so you can achieve goals faster. After conducting extensive research with data scientists, business analysts, and data engineers, authors Ron Itelman and Juan Cruz Viotti learned three specific key activities: assess, analyze, and align, to augment innovation where Agile isn't meeting the specific needs of business, data, and code teams. This guide shows how to collaborate more effectively and design intelligent systems without having to become a data scientist. Map your team, objectives, data, actions, and outcomes as a holistic network and discover connections that may not always be obvious. You'll learn how to reveal hidden root problems and explain how information flows across your organizational networks in order to innovate better, faster. Use an innovation and collaborative methodology grounded in principles of intelligence Create data schemas, data products, and data contracts, and design better data experiences Build a wisdom graph, which combines high-level knowledge, people, processes, objectives, and outcomes, for a focused data science approach to innovation Integrate your wisdom graph with ChatGPT and learn about large language model innovation opportunities
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Codes, Curves, and Signals
Codes, Curves, and Signals: Common Threads in Communications is a collection of seventeen contributions from leading researchers in communications. The book provides a representative cross-section of cutting edge contemporary research in the fields of algebraic curves and the associated decoding algorithms, the use of signal processing techniques in coding theory, and the application of information-theoretic methods in communications and signal processing. The book is organized into three parts: Curves and Codes, Codes and Signals, and Signals and Information. Codes, Curves, and Signals: Common Threads in Communications is a tribute to the broad and profound influence of Richard E. Blahut on the fields of algebraic coding, information theory, and digital signal processing. All the contributors have individually and collectively dedicated their work to R. E. Blahut. Codes, Curves, and Signals: Common Threads in Communications is an excellent reference for researchers and professionals.
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Coded Modulation Systems
Coded Modulation Systems is an introduction to the subject of coded modulation in digital communication. It is designed for classroom use and for anyone wanting to learn the ideas behind this modern kind of coding. Coded modulation is signal encoding that takes into account the nature of the channel over which it is used. Traditional error correcting codes work with bits and add redundant bits in order to correct transmission errors. In coded modulation, continuous time signals and their phases and amplitudes play the major role. The coding can be seen as a patterning of these quantities. The object is still to correct errors, but more fundamentally, it is to conserve signal energy and bandwidth at a given error performance. The book divides coded modulation into three major parts. Trellis coded modulation (TCM) schemes encode the points of QAM constellations; lattice coding and set-partition techniques play major roles here. Continuous-phase modulation (CPM) codes encode the signal phase, and create constant envelope RF signals. The partial-response signaling (PRS) field includes intersymbol interference problems, signals generated by real convolution, and signals created by lowpass filtering. In addition to these topics, the book covers coding techniques of several kinds for fading channels, spread spectrum and repeat-request systems. The history of the subject is fully traced back to the formative work of Shannon in 1949. Full explanation of the basics and complete homework problems make the book ideal for self-study or classroom use.
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Beyond the Code
For over 80 years, the National Society of Professional Engineers (NSPE) has been a leader in the promotion of ethical practice within the field of engineering. One of the Society’s greatest contributions is the formation and adoption of the NSPE Code of Ethics. But the code, with its six "Fundamental Canons," is only truly instructive if engineers can bridge the gap between principles and action. Here there is no substitute for personal reflection on the ethical and philosophical issues that underlie the code. If done well, such reflection provides an indispensable basis for moral problem solving. Beyond the Code: A Philosophical Guide to Engineering Ethics is designed to complement the NSPE Code of Ethics by helping readers "go beyond" in their understanding of the philosophical issues bound up in the code. Each chapter addresses one of the Fundamental Canons of the NSPE code, and provides a philosophical analysis of the various parts of each canon by employing contemporary and classical texts. This unique approach to engineering ethics guides students and professionals in their readings of the appended selections to refine their understanding of the code in order to apply it to the practical challenges of today’s engineers. Key Features: Is the first introduction to engineering ethics that helps students understand and apply the NSPE Code of Ethics to engineering practiceIncludes a Preface from Arthur E. Schwartz, NSPE Deputy Executive Director and General Counsel, and NAFE Executive DirectorAs a hybrid text, includes primary philosophical texts with extensive introductions and guided reading questions from the book’s three authorsOffers case studies from the NSPE Board of Ethical Review, allowing students to see a direct connection between the issues discussed in the text and real-world engineering practiceIncludes the following pedagogical aids: "Key Terms and Concepts" for each chapter "Preparing to Read" sections before each primary source reading "Guided Reading Questions" after each primary source reading "Going Beyond—Our Questions for a Deep Dive" after each case study.
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Codes on Algebraic Curves
This is a self-contained introduction to algebraic curves over finite fields and geometric Goppa codes. There are four main divisions in the book. The first is a brief exposition of basic concepts and facts of the theory of error-correcting codes (Part I). The second is a complete presentation of the theory of algebraic curves, especially the curves defined over finite fields (Part II). The third is a detailed description of the theory of classical modular curves and their reduction modulo a prime number (Part III). The fourth (and basic) is the construction of geometric Goppa codes and the production of asymptotically good linear codes coming from algebraic curves over finite fields (Part IV). The theory of geometric Goppa codes is a fascinating topic where two extremes meet: the highly abstract and deep theory of algebraic (specifically modular) curves over finite fields and the very concrete problems in the engineering of information transmission. At the present time there are two essentially different ways to produce asymptotically good codes coming from algebraic curves over a finite field with an extremely large number of rational points. The first way, developed by M. A. Tsfasman, S. G. Vladut and Th. Zink [210], is rather difficult and assumes a serious acquaintance with the theory of modular curves and their reduction modulo a prime number. The second way, proposed recently by A.
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Clean Code in Python
Tackle inefficiencies and errors the Pythonic wayKey FeaturesEnhance your coding skills using the new features introduced in Python 3.9Implement the refactoring techniques and SOLID principles in PythonApply microservices to your legacy systems by implementing practical techniquesBook DescriptionExperienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles and manage your projects successfully. The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform. By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.What you will learnSet up a productive development environment by leveraging automatic toolsLeverage the magic methods in Python to write better code, abstracting complexity away and encapsulating detailsCreate advanced object-oriented designs using unique features of Python, such as descriptorsEliminate duplicated code by creating powerful abstractions using software engineering principles of object-oriented designCreate Python-specific solutions using decorators and descriptorsRefactor code effectively with the help of unit testsBuild the foundations for solid architecture with a clean code base as its cornerstoneWho this book is forThis book is designed to benefit new as well as experienced programmers. It will appeal to team leads, software architects and senior software engineers who would like to write Pythonic code to save on costs and improve efficiency. The book assumes that you have a strong understanding of programming
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