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Stochastic Programming
This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book’s closing section, several case studies are presented, helping students apply the theory covered to practical problems.The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide.
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Integer Programming
A PRACTICAL GUIDE TO OPTIMIZATION PROBLEMS WITH DISCRETE OR INTEGER VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming explains in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems. The second edition also includes information on the remarkable progress in the development of mixed integer programming solvers in the 22 years since the first edition of the book appeared. The updated text includes information on the most recent developments in the field such as the much improved preprocessing/presolving and the many new ideas for primal heuristics included in the solvers. The result has been a speed-up of several orders of magnitude. The other major change reflected in the text is the widespread use of decomposition algorithms, in particular column generation (branch-(cut)-and-price) and Benders’ decomposition. The revised second edition: Contains new developments on column generationOffers a new chapter on Benders’ algorithmIncludes expanded information on preprocessing, heuristics, and branch-and-cutPresents several basic and extended formulations, for example for fixed costnetwork flowsAlso touches on and briefly introduces topics such as non-bipartite matching, the complexity of extended formulations or a good linear program for the implementation of lift-and-project Written for students of integer/mathematical programming in operations research, mathematics, engineering, or computer science, Integer Programming offers an updated edition of the basic text that reflects the most recent developments in the field.
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Inductive Synthesis of Functional Programs
Because of its promise to support human programmers in developing correct and efficient program code and in reasoning about programs, automatic program synthesis has attracted the attention of researchers and professionals since the 1970s.This book focusses on inductive program synthesis, and especially on the induction of recursive functions; it is organized into three parts on planning, inductive program synthesis, and analogical problem solving and learning. Besides methodological issues in inductive program synthesis, emphasis is placed on its applications to control rule learning for planning. Furthermore, relations to problem solving and learning in cognitive psychology are discussed.
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Linear Programming
The book provides a broad introduction to both the theory and the application of optimization with a special emphasis on the elegance, importance, and usefulness of the parametric self-dual simplex method. The book assumes that a problem in “standard form,” is a problem with inequality constraints and nonnegative variables. The main new innovation to the book is the use of clickable links to the (newly updated) online app to help students do the trivial but tedious arithmetic when solving optimization problems.The latest edition now includes: a discussion of modern Machine Learning applications, as motivational material; a section explaining Gomory Cuts and an application of integer programming to solve Sudoku problems. Readers will discover a host of practical business applications as well as non-business applications. Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, the primal-dual simplex method, the path-following interior-point method, and and the homogeneous self-dual method. In addition, the author provides online tools that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and online pivot tools can be found on the book's website. The website also includes new online instructional tools and exercises.
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Beyond Programming
Beyond Programming provides a unique examination of the software development process. It asserts that software development, a discipline that is less than 50 years old, is still guided by methods conceived in the framework of an older technology. To make significant progress in software development, we must re-examine our fundamental principles and construct a computer science for the technology of the twenty-first century. Blum goes on to explore thehistory of software development through looking at the scientific foundations of computer technology, the perspectives of the designers themselves and the methods used. The concepts reviewed in Beyond Programming are key to understanding the research and development challenges that will confront computertechnology in the next century.
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Stochastic Programming
From the Preface… The preparation of this book started in 2004, when George B. Dantzig and I, following a long-standing invitation by Fred Hillier to contribute a volume to his International Series in Operations Research and Management Science, decided finally to go ahead with editing a volume on stochastic programming. The field of stochastic programming (also referred to as optimization under uncertainty or planning under uncertainty) had advanced significantly in the last two decades, both theoretically and in practice. George Dantzig and I felt that it would be valuable to showcase some of these advances and to present what one might call the state-of- the-art of the field to a broader audience. We invited researchers whom we considered to be leading experts in various specialties of the field, including a few representatives of promising developments in the making, to write a chapter for the volume. Unfortunately, to the great loss of all of us, George Dantzig passed away on May 13, 2005. Encouraged by many colleagues, I decided to continue with the book and edit it as a volume dedicated to George Dantzig. Management Science published in 2005 a special volume featuring the “Ten most Influential Papers of the first 50 Years of Management Science.” George Dantzig’s original 1955 stochastic programming paper, “Linear Programming under Uncertainty,” was featured among these ten. Hearing about this, George Dantzig suggested that his 1955 paper be the first chapter of this book. The vision expressed in that paper gives an important scientific and historical perspective to the book.Gerd Infanger
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Systematic Program Design
A systematic program design method can help developers ensure the correctness and performance of programs while minimizing the development cost. This book describes a method that starts with a clear specification of a computation and derives an efficient implementation by step-wise program analysis and transformations. The method applies to problems specified in imperative, database, functional, logic and object-oriented programming languages with different data, control and module abstractions. Designed for courses or self-study, this book includes numerous exercises and examples that require minimal computer science background, making it accessible to novices. Experienced practitioners and researchers will appreciate the detailed examples in a wide range of application areas including hardware design, image processing, access control, query optimization and program analysis. The last section of the book points out directions for future studies.
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Java for Programmers
The professional programmer's Deitel® guide to Java with integrated generative AI Written for programmers with a background in another high-level language, in Java for Programmers: with Generative AI, Fifth Edition, you'll learn modern Java development hands on using the latest Java idioms and features and genAIs. In the context of 200+ real-world code examples, you'll quickly master Java fundamentals then move on to arrays, strings, regular expressions, JSON/CSV processing with the Jackson library, private- and public-key cryptography, classes, inheritance, polymorphism, interfaces, dependency injection, exceptions, generic collections, custom generics, functional programming with lambdas and streams, JavaFX GUI, graphics and multimedia, platform threads, virtual threads, structured concurrency, scoped values, building API-based Java genAI apps, database with JDBC and SQLite, the Java Platform Module System and JShell for Python-like interactivity. Features: GenAI Prompt Engineering, API Calls, 600 GenAI ExercisesChatGPT, Gemini, Claude, PerplexityMultimodal: Text, Code, Images, Audio, Speech-to-Text, Text-to-Speech, VideoGenerics: Collections, Classes, MethodsFunctional Programming: Lambdas & StreamsJavaFX: GUI, Graphics, MultimediaConcurrency: Parallel Streams, Virtual Threads, Structured Concurrency, Scoped Values, Concurrent Collections, Multi-CoreDatabase: JDBC, SQL, SQLiteJava Platform Module System (JPMS)Objects Natural: Java API, String, BigInteger, BigDecimal, Date/Time, Cryptography, ArrayList, Regex, JSON, CSV, Web ServicesJShell for Python-Like Interactivity Want to stay in touch with the Deitels? Contact the authors at deitel@deitel.comJoin the Deitel social media communitiesdeitel.com/linkedinfacebook.com/DeitelFaninstagram.com/DeitelFanx.com/deitelyoutube.com/DeitelTVmastodon.social/@deitelFor source code and updates, visit: deitel.com/javafp5 Reviewer Comments"The future of Java programming is here, and this new edition of Deitel is leading the charge! By embracing genAI head-on, the authors are potentially revolutionizing programming education. Through its integrative approach to the use and study of genAI, this book is positioned to be the leading book in modern Java and its applications. Indeed, I expect that it should be widely adopted by instructors who want to ingrain in their students an appreciation for the critical role that Java will play in data science, machine learning, artificial intelligence, and cybersecurity. "The book's innovative and forward-thinking use of genAI facilitates reader engagement and inspires readers to think critically about the benefits and limitations of AI as a programming aid. Chapter 19 could become everyone's favorite new Java book chapter--the generative AI API-based code examples are interesting and fun. "All audiences of this book should read the Preface--there's so much to get excited about! It demonstrates, with refreshing transparency and honesty, how much love and care went into the r
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Minimalist Program
The development of the Minimalist Program (MP), Noam Chomsky's most recent generative model of linguistics, has been highly influential over the last twenty years. It has had significant implications not only for the conduct of linguistic analysis itself, but also for our understanding of the status of linguistics as a science. The reflections and analyses in this book contain insights into the strengths and the weaknesses of the MP. These include: a clarification of the content of the Strong Minimalist Thesis (SMT); a synthesis of Chomsky's linguistic and interdisciplinary discourses; and an analysis of the notion of optimal computation from conceptual, empirical and philosophical perspectives. This book will encourage graduate students and researchers in linguistics to reflect on the foundations of their discipline, and the interdisciplinary nature of the topics explored will appeal to those studying biolinguistics, neurolinguistics, the philosophy of language and other related disciplines.
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Programmieren für Ingenieure und Naturwissenschaftler
Ziel des Buches ist es, Studierenden der Ingenieur- oder Naturwissenschaften die Programmierung als Schlüsselqualifikation mit zahlreichen Anwendungsmöglichkeiten vorzustellen. Die Umsetzung von Programmierkonzepten und algorithmischen Verfahren erfolgt in diesem Buch in Java. Im ersten Teil gibt der Autor eine Einführung in die Grundkonzepte von Java, im zweiten Teil werden algorithmische Verfahren aus dem Bereich der Numerik, sowie allgemeine Methoden zum Entwurf von Algorithmen vorgestellt. Im dritten Teil werden Grundlagen der objektorientierten Programmierung dargestellt sowie ein Überblick über die Erstellung von graphischen Benutzeroberflächen gegeben. Ein Kapitel zu diversen Anwendungen aus dem Bereich der Ingenieur- und Naturwissenschaften sowie Aufgaben und Lösungen in jedem Kapitel runden das Buch ab.
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Algebraic Approaches to Program Semantics
In the 1930s, mathematical logicians studied the notion of "effective comput ability" using such notions as recursive functions, A-calculus, and Turing machines. The 1940s saw the construction of the first electronic computers, and the next 20 years saw the evolution of higher-level programming languages in which programs could be written in a convenient fashion independent (thanks to compilers and interpreters) of the architecture of any specific machine. The development of such languages led in turn to the general analysis of questions of syntax, structuring strings of symbols which could count as legal programs, and semantics, determining the "meaning" of a program, for example, as the function it computes in transforming input data to output results. An important approach to semantics, pioneered by Floyd, Hoare, and Wirth, is called assertion semantics: given a specification of which assertions (preconditions) on input data should guarantee that the results satisfy desired assertions (postconditions) on output data, one seeks a logical proof that the program satisfies its specification. An alternative approach, pioneered by Scott and Strachey, is called denotational semantics: it offers algebraic techniques for characterizing the denotation of (i. e. , the function computed by) a program-the properties of the program can then be checked by direct comparison of the denotation with the specification. This book is an introduction to denotational semantics. More specifically, we introduce the reader to two approaches to denotational semantics: the order semantics of Scott and Strachey and our own partially additive semantics.
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Programs, Recursion and Unbounded Choice
This book is a complete account of the predicate transformation calculus semantics of sequential programs, including repetitions, recursive procedures, computational induction and unbounded nondeterminacy. Predicate transformation semantics are the best specification method for the development of correct and well-structured computer programs. The author develops this theory to a greater depth than has been achieved before, and describes it in a way that makes it readily compatible with programming rules for partial and total correctness of repetitions and recursive procedures, supplies new rules for proving incorrectness, and a stronger rule for proving that two programs satisfy the same specifications. Finally, the semantics are extended so that non-terminating programs can be specified as well. This will be essential reading for all computer scientists working in specification and verification of programs.
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Programming in Two Semesters
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features:Assumes no prior knowledge, and makes the transition from Python to Java a smooth processFeatures numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFXExplains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
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Programmiersprache Dist
Keine ausf�hrliche Beschreibung f�r "Programmiersprache DIST" verf�gbar.
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Optimal Control from Theory to Computer Programs
The aim of this book is to present the mathematical theory and the know-how to make computer programs for the numerical approximation of Optimal Control of PDE's. The computer programs are presented in a straightforward generic language. As a consequence they are well structured, clearly explained and can be translated easily into any high level programming language. Applications and corresponding numerical tests are also given and discussed. To our knowledge, this is the first book to put together mathematics and computer programs for Optimal Control in order to bridge the gap between mathematical abstract algorithms and concrete numerical ones. The text is addressed to students and graduates in Mathematics, Mechanics, Applied Mathematics, Numerical Software, Information Technology and Engineering. It can also be used for Master and Ph.D. programs.
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Behavioral Program Synthesis with Genetic Programming
Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subscribing to that perspective to varying extent are presented and discussed, including implicit fitness sharing, semantic GP, co-solvability, trace convergence analysis, pattern-guided program synthesis, and behavioral archives of subprograms. The framework involves several concepts that are new to GP, including execution record, combined trace, and search driver, a generalization of objective function. Empirical evidence gathered in several presented experiments clearly demonstrates the usefulness of behavioral approach. The book contains also an extensive discussion of implications of the behavioral perspective for program synthesis and beyond.
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Genetic Programming Theory and Practice XIX
This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year´s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research.
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Programmed Capitalism
Focuses on how the computer has transformed the economy into an information processing and intelligence system. Annotation copyright Book News, Inc. Portland, Or.
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Extensions of Logic Programming
This book contains papers which investigate how to extendlogic programming toward the artificial intelligence andsoftware engineering areas, covering both theoretical andpractical aspects. Some papers investigate topics such asabductive reasoning and negation. Some works discuss how toenhance the expressive power of logic programming byintroducing constraints, sets, and integration withfunctional programming. Other papers deal with thestructuring of knowledge into modules, taxonomies, andobjects, withthe aim of extending logic programming towardsoftware engineering applications. A section is devoted topapers concentrating on proof theory and inspired byGentzen-style sequent or natural deduction systems. Topicssuch as concurrency are considered to enhance the expressivepower of logic languages. Finally, some papers mainlyconcernimplementation techniques for some of these logicprogramming extensions.
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Reasoning About Program Transformations
The text contains a detailed and current presentation of the program analyses and transformations that extract the flow of data in computer memory systems. The emphasis is on a framework for the optimization of code for imperative programs and greater computer systems efficiency. In addition, the author shows that correctness of program transformations is guaranteed by the conservation of data flow. Professionals and researchers in software engineering, computer engineering, program design analysis, and compiler design will benefit from its presentation of data-flow methods and memory optimization of compilers.
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Preprogrammed
A free ebook version of this title is available through Luminos, University of California Press’s Open Access publishing program. Visit www.luminosoa.org to learn more.How much of your life is preprogrammed? Presets, or default settings on technology, can be found everywhere, from predictive text and Instagram filters to microwave popcorn buttons and morning alarms. But while presets facilitate the completion of tasks and the production of art, they also reinforce—or sometimes challenge—economic, political, and social norms. In Preprogrammed, interdisciplinary scholar Amy Skjerseth turns to modern music and media to explore what presets allow and deny. Using capitalist, queer, and feminist critique, she shows how, from the popularization of the push-button car radio in the 1930s to the Auto-Tune era and the advent of AI, artists have co-opted preset technologies to reconfigure ways of seeing and hearing and develop new forms of artistic and cultural expression. An urgent reconsideration of the cultural and political systems we often take for granted, this elegantly theorized and paradigm-shifting book invites us to rethink the profundity of the everyday.
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Introduction to Python Programming for Scientists and Engineers
Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
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Logic Programming with Prolog
Logic Programming is the name given to a distinctive style of programming, very different from that of conventional programming languages such as C++ and Java. By far the most widely used Logic Programming language is Prolog. Prolog is a good choice for developing complex applications, especially in the field of Artificial Intelligence.Logic Programming with Prolog does not assume that the reader is an experienced programmer or has a background in Mathematics, Logic or Artificial Intelligence. It starts from scratch and aims to arrive at the point where quite powerful programs can be written in the language. It is intended both as a textbook for an introductory course and as a self-study book. On completion readers will know enough to use Prolog in their own research or practical projects.Each chapter has self-assessment exercises so that readers may check their own progress. A glossary of the technical terms used completes the book.This second edition has been revised to be fully compatible with SWI-Prolog, a popular multi-platform public domain implementation of the language. Additional chapters have been added covering the use of Prolog to analyse English sentences and to illustrate how Prolog can be used to implement applications of an 'Artificial Intelligence' kind.Max Bramer is Emeritus Professor of Information Technology at the University of Portsmouth, England. He has taught Prolog to undergraduate computer science students and used Prolog in his own work for many years.
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Introduction to Programming with Fortran
This fourth Edition presents new examples on submodules, derived type i/o, object oriented programming, abstract interfaces and procedure pointers, C interop, sorting and searching, statistics and converting to more modern versions of Fortran.Key FeaturesHighlights the core language features of modern Fortran including data typing, array processing, control structures, functions, subroutines, modules and submodules, user defined types, pointers, operator overloading, generic programming, parallel programming, abstract interfaces, procedure pointersPinpoints common problems that occur when programmingIllustrates the use of several compilersIntroduction to Programming with Fortran has been written for the complete beginner with little or no programming background as well as existing Fortran programmers and those with programming experience in other languages
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Unconventional Programming Paradigms
Nowadays, developers have to face the proliferation of hardware and software environments, the increasing demands of the users, the growing number of p- grams and the sharing of information, competences and services thanks to the generalization ofdatabasesandcommunication networks. Aprogramisnomore a monolithic entity conceived, produced and ?nalized before being used. A p- gram is now seen as an open and adaptive frame, which, for example, can - namically incorporate services not foreseen by the initial designer. These new needs call for new control structures and program interactions. Unconventionalapproachestoprogramminghavelongbeendevelopedinv- iousnichesandconstituteareservoirofalternativewaystofacetheprogramming languages crisis. New models of programming (e. g. , bio-inspired computing, - ti?cialchemistry,amorphouscomputing,. . . )arealsocurrentlyexperiencinga renewed period of growth as they face speci?c needs and new application - mains. These approaches provide new abstractions and notations or develop new ways of interacting with programs. They are implemented by embedding new sophisticated data structures in a classical programming model (API), by extending an existing language with new constructs (to handle concurrency, - ceptions, open environments, . . . ), by conceiving new software life cycles and program executions (aspect weaving, run-time compilation) or by relying on an entire new paradigm to specify a computation. They are inspired by theoretical considerations (e. g. , topological, algebraic or logical foundations), driven by the domain at hand (domain-speci?c languages like PostScript, musical notation, animation, signal processing, etc. ) or by metaphors taken from various areas (quantum computing, computing with molecules, information processing in - ological tissues, problem solving from nature, ethological and social modeling).
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Algorithms and Programs
Algorithms power modern systems--from flight control and robotics to recommendation engines and AI applications. Algorithms and Programs: An AI-Assisted Approach shows how to clearly define an algorithm's purpose, design a structured outline, translate it into reliable code, and reason about its efficiency and complexity. Rather than relying on traditional pseudocode, this book uses precise algorithm outlines that are easier to understand and directly support correct implementation. This approach bridges the gap between design and code, reducing ambiguity and minimizing errors. Each algorithm is expressed as a sequence of clear, intended outcomes, which naturally define its correctness conditions and support reasoning about invariants and program behavior. This structured method encourages better programming practice, improves reliability, and aligns well with modern AI-assisted development tools. Practical approach to algorithms: Moves beyond traditional pseudocode to clear, structured algorithm outlines that directly translate into reliable code.Bridges theory and real-world programming: Helps learners and engineers connect algorithm design with implementation, correctness, and performance in everyday software development.Makes invariants intuitive and usable: Developed from decades of teaching experience, the book rethinks invariants in a practical, common-sense way that students and practitioners can actually apply.Designed for modern AI-assisted development: Aligns with how programming is done today, enabling AI-checkable algorithm structures that support correctness and reduce errors.Rooted in teaching and real industry experience: Inspired by long-term discussions with students and professional practice, addressing real gaps between academic concepts and industry needs.Strategic AI Thinking: Explore leverage from AI platforms that specify function requirements, outline appropriate algorithms, implement outlines, and inspect them reliably.
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Program Verification
Among the most important problems confronting computer science is that of developing a paradigm appropriate to the discipline. Proponents of formal methods - such as John McCarthy, C.A.R. Hoare, and Edgar Dijkstra - have advanced the position that computing is a mathematical activity and that computer science should model itself after mathematics. Opponents of formal methods - by contrast, suggest that programming is the activity which is fundamental to computer science and that there are important differences that distinguish it from mathematics, which therefore cannot provide a suitable paradigm. Disagreement over the place of formal methods in computer science has recently arisen in the form of renewed interest in the nature and capacity of program verification as a method for establishing the reliability of software systems. A paper that appeared in Communications of the ACM entitled, `Program Verification: The Very Idea', by James H. Fetzer triggered an extended debate that has been discussed in several journals and that has endured for several years, engaging the interest of computer scientists (both theoretical and applied) and of other thinkers from a wide range of backgrounds who want to understand computer science as a domain of inquiry. The editors of this collection have brought together many of the most interesting and important studies that contribute to answering questions about the nature and the limits of computer science. These include early papers advocating the mathematical paradigm by McCarthy, Naur, R. Floyd, and Hoare (in Part I), others that elaborate the paradigm by Hoare, Meyer, Naur, and Scherlis and Scott (in Part II), challenges, limits and alternatives explored by C. Floyd, Smith, Blum, and Naur (in Part III), and recent work focusing on formal verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and Colburn (in Part IV). It provides essential resources for further study. This volume will appeal to scientists, philosophers, and laypersons who want to understand the theoretical foundations of computer science and be appropriately positioned to evaluate the scope and limits of the discipline.
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Hands-On Object-Oriented Programming
Learn how to easily design and implement a software system using object-oriented programming. Through hands-on activities, this book equips you with the real-world practice needed to master OOP skills that can be applied universally across any programming language. This book is dedicated to bridging the gap between theoretical concepts and practical implementation in software development using OOP. Readers will first understand the importance of OOP in handling software complexities before learning how to model real-world problems through access control, extendible object design, and object relationships. Specifically, the author discusses how to use inheritance, association, and polymorphism concepts for implementing reusable and easy-to-use complex software. More importantly, this book covers design patterns and event-driven programming for learning how to model complex interactions among various objects of the software system to implement various use cases. Unlike existing books on OOP which teach syntax and semantics through standard examples, this book leverages an immersive learning experience through a variety of real-world use cases, applications, games, and system software. While written in C++, the skills can be applied to any OOP language of the reader's preference. The book's last chapters will quickly introduce Python and Solidity languages for learning advanced technologies. By the end, novice and seasoned developers will know how to implement practical and reusable software systems with confidence. What You Will Learn Apply OOP concepts through real-time use cases: games, applications software (online shopping, reservations, etc.), system software (protocols, simulators, etc.), and modeling and implementation using C+Design and implement reusable and extendible software with OOPUnderstand the importance of design patterns and learn how to use them for solving real-time issuesUse event-driven programming for implementing complete interactions of complex application software, system software, and simulatorsImplement OOP using C++ features and discover Python and Solidity constructs for OOP Who This Book Is For Beginners and intermediate software developers with basic programming knowledge to quickly learn OOP concepts with C++. Advanced users will find it useful for quickly exploring best-design principles, patterns, and event-driven programming for implementing complex software systems.
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Foundations of Logic Programming
In the two and a half years since the frrst edition of this book was published, the field of logic programming has grown rapidly. Consequently, it seemed advisable to try to expand the subject matter covered in the first edition. The new material in the second edition has a strong database flavour, which reflects my own research interests over the last three years. However, despite the fact that the second edition has about 70% more material than the first edition, many worthwhile topic!! are still missing. I can only plead that the field is now too big to expect one author to cover everything. In the second edition, I discuss a larger class of programs than that discussed in the first edition. Related to this, I have also taken the opportunity to try to improve some of the earlier terminology. Firstly, I introduce "program statements", which are formulas of the form A+-W, where the head A is an atom and the body W is an arbitrary formula. A "program" is a finite set of program statements. There are various restrictions of this class. "Normal" programs are ones where the body of each program statement is a conjunction of literals. (The terminology "general", used in the first edition, is obviously now inappropriate).
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Grundlagen Der Logischen Programmierung
Keine ausführliche Beschreibung für "Grundlagen der logischen Programmierung" verfügbar.
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Programmieren mit Python
Diese einmalige und in sich geschlossene Einführung in die Programmierung verwendet Python um in die wichtigsten Paradigmen der Programmierung einzuführen: die Prozedurale Programmierung, dieObjektorientierte Programmierung und die Funktionale Programmierung und schließlich die Programmierung mit Numpy. Das Buch eignet sich für eine 5 – 7 ECTS Einführungsvorlesung und enthält eine Vielzahl von Aufgaben, die auch von Studierenden im Selbststudium gut zum Üben verwendet werden können.
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R 426.00
Logic-Based Program Synthesis and Transformation
This book constitutes the thoroughly refereed post-conference proceedings of the 22nd International Symposium on Logic-Based Program Synthesis and Transformation, LOPSTR 2012, held in Leuven, Belgium in September 2012. The 13 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 27 submissions. Among the topics covered are specification, synthesis, verification, analysis, optimization, specialization, security, certification, applications and tools, program/model manipulation, and transformation techniques for any programming language paradigm.
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