Das Buch wendet sich an alle, die Word nicht als Büroanwendung, also zum Erstellen von Briefen, Präsentationen, Notizen oder kurzen Mitteilungen einsetzen, sondern die immer wieder längere Dokumente schreiben oder bearbeiten. Hauptzielgruppe sind Autoren, Lektoren und Redakteure. Aber auch Setzer, Layouter, Dozenten, Studenten, Lehrer, Schüler und überhaupt alle, die mehr aus dem Programm herausholen möchten, als es die Word-Hilfe oder die üblichen Handbücher erlauben, werden von dem Werk profitieren können. Selbst dem VBA-Programmierprofi werden an vielen Stellen Anregungen geboten. Vorausgesetzt werden Grundkenntnisse in Word und eine offene Einstellung, sich auf neue Blickwinkel und Verfahren einzulassen. Es ist hilfreich, wenn die Leser sich mit der Oberfläche von Word (Menüband) auskennen.
These proceedings consist of 19 papers, which have been peer-reviewed by international program committee and selected for the 5th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2017), which was held on June 30-July 1, 2017 in Berlin, Germany. The respective chapters discuss both theoretical and practical issues in connection with computational methods and optimization methods for knowledge engineering. The broad range of application areas discussed includes network computing, simulation, intelligent and adaptive e-learning, information retrieval, sentiment analysis, autonomous underwater vehicles, social media analysis, natural language processing, biomimetics in organizations, and cash management. In addition to pure content, the book offers many inspiring ideas and suggests new research directions, making it a valuable resource for graduate students, Ph.D. students, and researchers in Computer Science and Applied Mathematics alike.
The Unified Modeling Language (UML) provides an environment for modeling complex systems. It supports a variety of diagrams for analyzing, designing, and implementing software systems. During the requirements phase, developers abstract concepts from the application domain and describe what the system is intended to do, not how it will do it. UML was adopted as a standard for OO modeling by the Object Management Group in 1997 and has found use in various software development projects. However, the continued success of any new technology depends a great deal on its usability. To predict the future success of a language like UML it is important to address the issue of usability from the perspective of the users of the language, the software developers. This publication reports on the results of an empirical study aimed at assessing the usability of UML for developing software requirements. It addresses the dimensions of ease of use, usefulness, and usefulness for communicating requirements to various project stakeholders.
The primary objective of software reliability is the probability that the program works without failure for a period of time, and it is usually expressed as the mean time to failure. Software is either correct or incorrect when it is designed and developed, and it does not physically deteriorate with time. Models are simplifications of the reality, and a good model allows accurate predictions of future behavior to be made. A model is judged effective if there is good empirical evidence to support it, and a good software reliability model will have good theoretical foundations and realistic assumptions. This book covers the important topics in software engineering such as software reliability, software reliability models, software defects and critical systems.
An indispensable collection of practical tips and real-world advice for tackling common Python problems and taking your code to the next level. Features interviews with high-profile Python developers who share their tips, tricks, best practices, and real-world advice gleaned from years of experience. Sharpen your Python skills as you dive deep into the Python programming language with Serious Python. You´ll cover a range of advanced topics like multithreading and memorization, get advice from experts on things like designing APIs and dealing with databases, and learn Python internals to help you gain a deeper understanding of the language itself. Written for developers and experienced programmers, Serious Python brings together over 15 years of Python experience to teach you how to avoid common mistakes, write code more efficiently, and build better programs in less time. As you make your way through the book´s extensive tutorials, you´ll learn how to start a project and tackle topics like versioning, layouts, coding style, and automated checks. You´ll learn how to package your software for distribution, optimize performance, use the right data structures, define functions efficiently, pick the right libraries, build future-proof programs, and optimize your programs down to the bytecode. You´ll also learn how to: - Make and use effective decorators and methods, including abstract, static, and class methods - Employ Python for functional programming using generators, pure functions, and functional functions - Extend flake8 to work with the abstract syntax tree (AST) to introduce more sophisticated automatic checks into your programs - Apply dynamic performance analysis to identify bottlenecks in your code - Work with relational databases and effectively manage and stream data with PostgreSQL If you´ve been looking for a way to take your Python skills from good to great, Serious Python will help you get there. Learn from the experts and get seriously good at Python with Serious Python!
Today, reliable software systems are the basis of any business or company. The continuous further development of those systems is the central component in software evolution. It requires a huge amount of time- man power- as well as financial resources. The challenges are size, seniority and heterogeneity of those software systems. Christian Wagner addresses software evolution: the inherent problems and uncertainties in the process. He presents a model-driven method which leads to a synchronization between source code and design. As a result the model layer will be the central part in further evolution and source code becomes a by-product. For the first time a model-driven procedure for maintenance and migration of software systems is described. The procedure is composed of a model-driven reengineering and a model-driven migration phase. The application and effectiveness of the procedure are confirmed with a reference implementation applied to four exemplary systems.
A decision procedure is an algorithm that, given a decision problem, terminates with a correct yes/no answer. Here, the authors focus on theories that are expressive enough to model real problems, but are still decidable. Specifically, the book concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research. The techniques described in the book draw from fields such as graph theory and logic, and are routinely used in industry. The authors introduce the basic terminology of satisfiability modulo theories and then, in separate chapters, study decision procedures for each of the following theories: propositional logic; equalities and uninterpreted functions; linear arithmetic; bit vectors; arrays; pointer logic; and quantified formulas.
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms. This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included. Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. What You Will Learn Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe Gain the fundamentals of deep learning with mathematical prerequisites Discover the practical considerations of large scale experiments Take deep learning models to production Who This Book Is For Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.
A basic primer for all employees on using Lean Six Sigma to meet your company´s goals and your customers´ needs Lean Six Sigma combines the two most important and popular quality trends of our time: Six Sigma and Lean Production. In this plain-English guide, you´ll discover how this remarkable quality improvement method will help you identify and eliminate waste, cut costs and grow revenue, enhance your job skills, and even make work more meaningful.What is Lean Six Sigma? reveals why companies are implementing this strategy, and walks you through the foundations of Lean Six Sigma, explaining the ´´four keys´´ and how they apply to your own job:Delight your customers with speed and quality Improve your processes Work together for maximum gain Base decisions on data and facts Featuring charts, diagrams, and case studies of teams who have used these methods to improve their workplace, What is Lean Six Sigma? tells you what you need to know to make this strategy a success in your organization.
Many systems, devices and appliances used routinely in everyday life, ranging from cell phones to cars, contain significant amounts of software that is not directly visible to the user and is therefore called ´´embedded´´. For coordinating the various software components and allowing them to communicate with each other, support software is needed, called an operating system (OS). Because embedded software must function in real time (RT), a RTOS is needed. This book describes a formally developed, network-centric Real-Time Operating System, OpenComRTOS. One of the first in its kind, OpenComRTOS was originally developed to verify the usefulness of formal methods in the context of embedded software engineering. Using the formal methods described in this book produces results that are more reliable while delivering higher performance. The result is a unique real-time concurrent programming system that supports heterogeneous systems with just 5 Kbytes/node. It is compatible with safety related engineering standards, such as IEC61508.
Write maintainable, extensible, and durable software with modern C++. This book is a must for every developer, software architect, or team leader who is interested in good C++ code, and thus also wants to save development costs. If you want to teach yourself about writing clean C++, Clean C++ is exactly what you need. It is written to help C++ developers of all skill levels and shows by example how to write understandable, flexible, maintainable, and efficient C++ code. Even if you are a seasoned C++ developer, there are nuggets and data points in this book that you will find useful in your work. If you don´t take care with your code, you can produce a large, messy, and unmaintainable beast in any programming language. However, C++ projects in particular are prone to be messy and tend to slip into bad habits. Lots of C++ code that is written today looks as if it was written in the 1980s. It seems that C++ developers have been forg otten by those who preach Software Craftsmanship and Clean Code principles. The Web is full of bad, but apparently very fast and highly optimized C++ code examples, with cruel syntax that completely ignores elementary principles of good design and well-written code. This book will explain how to avoid this scenario and how to get the most out of your C++ code. You´ll find your coding becomes more efficient and, importantly, more fun. What You´ll Learn Gain sound principles and rules for clean coding in C++ Carry out test driven development (TDD) Discover C++ design patterns and idioms Apply these design patterns Who This Book Is For Any C++ developer and software engineer with an interest in producing better code.
Deliver bug-free software projects on schedule and within budget Get a clear, complete understanding of how to estimate software costs, schedules, and quality using the real-world information contained in this comprehensive volume. Find out how to choose the correct hardware and software tools, develop an appraisal strategy, deploy tests and prototypes, and produce accurate software cost estimates. Plus, you´ll get full coverage of cutting-edge estimating approaches using Java, object-oriented methods, and reusable components. * Plan for and execute project-, phase-, and activity-level cost estimations * Estimate regression, component, integration, and stress tests * Compensate for inaccuracies in data collection, calculation, and analysis * Assess software deliverables and data complexity * Test design principles and operational characteristics using software prototyping * Handle configuration change, research, quality control, and documentation costs ´´Capers Jones´ work offers a unique contribution to the understanding of the economics of software production. It provides deep insights into why our advances in computing are not matched with corresponding improvements in the software that drives it. This book is absolutely required reading for an understanding of the limitations of our technological advances.´´ --Paul A. Strassmann, former CIO of Xerox, the Department of Defense, and NASA