Author: John Allen Robinson
Software Design for Engineers and Scientists integrates three core areas of computing: . Software engineering - including both traditional methods and the insights of 'extreme programming' . Program design - including the analysis of data structures and algorithms . Practical object-oriented programming Without assuming prior knowledge of any particular programming language, and avoiding the need for students to learn from separate, specialised Computer Science texts, John Robinson takes the reader from small-scale programing to competence in large software projects, all within one volume. Copious examples and case studies are provided in C++. The book is especially suitable for undergraduates in the natural sciences and all branches of engineering who have some knowledge of computing basics, and now need to understand and apply software design to tasks like data analysis, simulation, signal processing or visualisation. John Robinson introduces both software theory and its application to problem solving using a range of design principles, applied to the creation of medium-sized systems, providing key methods and tools for designing reliable, efficient, maintainable programs. The case studies are presented within scientific contexts to illustrate all aspects of the design process, allowing students to relate theory to real-world applications. Core computing topics - usually found in separate specialised texts - presented to meet the specific requirements of science and engineering students Demonstrates good practice through applications, case studies and worked examples based in real-world contexts
Author: Paul W. Ross
Publisher: CRC Press
The Handbook of Software for Engineers and Scientists is a single-volume, ready reference for the practicing engineer and scientist in industry, government, and academia as well as the novice computer user. It provides the most up-to-date information in a variety of areas such as common platforms and operating systems, applications programs, networking, and many other problem-solving tools necessary to effectively use computers on a daily basis. Specific platforms and environments thoroughly discussed include MS-DOS®, Microsoft® WindowsTM, the Macintosh® and its various systems, UNIXTM, DEC VAXTM, IBM® mainframes, OS/2®, WindowsTM NT, and NeXTSTEPTM. Word processing, desktop publishing, spreadsheets, databases, integrated packages, computer presentation systems, groupware, and a number of useful utilities are also covered. Several extensive sections in the book are devoted to mathematical and statistical software. Information is provided on circuits and control simulation programs, finite element tools, and solid modeling tools. Additional coverage is included on data communications and networking. Many appendices at the end of the book provide useful supplemental information, such as ASCII codes, RS-232 parallel port and pinout information, and ANSI escape sequences. This valuable resource handbook brings together a wide variety of topics and offers a wealth of information at the reader's fingertips.
Author: Gary J. Bronson
Publisher: Course Technology Ptr
Category: Technology & Engineering
Bronson's robust second edition makes C++ accessible to first level engineering students, as C++ continues to gain a stronghold in the engineering and scientific communities.
Author: Tim Menzies,Laurie Williams,Thomas Zimmermann
Publisher: Morgan Kaufmann
Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains
Author: Jiju Antony
Category: Technology & Engineering
The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma. Key features: * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods – reducing time taken to design and develop prototypes, reducing time to reach the market * Case studies place DOE techniques in the context of different industry sectors * An excellent resource for the Six Sigma training program This book will be useful to engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs. * Provides essential DOE techniques for process improvement initiatives * Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and conduct tests * Case studies place DOE techniques in the context of different industry sectors
Author: Jeffrey C. Carver,Neil P. Chue Hong,George K. Thiruvathukal
Publisher: CRC Press
Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.
For Engineers and Scientists
Author: William J. Diamond
Publisher: John Wiley & Sons
Category: Business & Economics
Most books cover the subject from a statistical or theoretical point of view. Ideal for working engineers, this book uses real-world examples and boils statistical theory and analysis down to its simplest form. * Features new and updated material, including cases and a larger focus on multivariate analysis. * Uses simple analysis tools for practical implementation on the job. * Targets experiment planning as the groundwork for quality experiments.
Author: Larry Nyhoff
Publisher: CRC Press
Developed from the author’s many years of teaching computing courses, Programming in C++ for Engineering and Science guides students in designing programs to solve real problems encountered in engineering and scientific applications. These problems include radioactive decay, pollution indexes, digital circuits, differential equations, Internet addresses, data analysis, simulation, quality control, electrical networks, data encryption, beam deflection, and many other areas. To make it easier for novices to develop programs, the author uses an object-centered design approach that helps students identify the objects in a problem and the operations needed; develop an algorithm for processing; implement the objects, operations, and algorithm in a program; and test, correct, and revise the program. He also revisits topics in greater detail as the text progresses. By the end of the book, students will have a solid understanding of how C++ can be used to process complex objects, including how classes can be built to model objects. Web Resource The book’s website at http://cs.calvin.edu/books/c++/engr-sci provides source code, expanded presentations, links to relevant sites, reference materials, lab exercises, and projects. For instructors, solutions to exercises and PowerPoint slides for classroom use are available upon qualifying course adoption.
Author: Harry Cheng
Publisher: McGraw-Hill Science/Engineering/Math
C for Engineers and Scientists is a complete and authoritative introduction to computer programming in C, with introductions to object-oriented programming in C++, and graphical plotting and numerical computing in C/C++ interpreter Ch® and MATLAB® for applications in engineering and science. This book is designed to teach students how to solve engineering and science problems using C. It teaches beginners with no previous programming experience the underlying working principles of scientific computing and a disciplined approach for software development. All the major features of C89 and C99 are presented with numerous engineering application examples derived from production code. The book reveals the coding techniques used by the best C programmers and shows how experts solve problems in C. It is also an invaluable resource and reference book for seasoned programmers. C for Engineers and Scientists focuses on systematic software design approach in C for applications in engineering and science following the C99, the latest standard developed by the ANSI and ISO C Standard Committees which resolved many deficiencies of C89 for applications in engineering and science. The book includes a companion CD which contains the C/C++ interpreter Ch for use as an instructional tool as well as Visual C++ and gcc/g++ compilers to help teaching and learning of C and C++. Ch presents a pedagogically effective user-friendly interactive computing environment for the simplest possible teaching/learning computer programming in C so that the students can focus on improving their program design and problem solving skills.
How to Think Like a Computer Scientist
Author: Allen Downey
Publisher: Cambridge University Press
Python for Software Design is a concise introduction to software design using the Python programming language. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept.
Author: Christian Bird,Tim Menzies,Thomas Zimmermann
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry
Author: Adrian A. Hopgood
Publisher: CRC Press
The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/
Author: Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters
Publisher: Morgan Kaufmann
Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data
Author: James Smith
Publisher: Springer Science & Business Media
This concise guide covers the fundamental aspects of the numerical analysis, basing upon it the construction of its routines for solving nonlinear equations, linear and nonlinear systems of equations, and eigenvalue problems. Focusing on software development, this book emphasizes software tools, OOP techniques for handling vectors, polynomials, and matrices. Using actual examples to demonstrate reusable tools, the book enables readers to solve broad classes of software development and programming challenges. It adopts a balanced approach between OOP techniques and quick and dirty number crunching, and emphasizes the use of OOP features in implementing vector, polynomial and matrix algebra. As a practical reference, it will help developers and consultants setting up applications programs for electrical, electronic engineering and physical sciences who need to develop clean, efficient C++ programs in minimal time.
Open Source Solutions for Numerical Computation
Author: Sandeep Nagar
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation. In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. What You'll Learn Understand the fundamentals of the Python programming language Apply Python to numerical computational programming projects in engineering and science Discover the Pythonic way of life Apply data types, operators, and arrays Carry out plotting for visualization Work with functions and loops Who This Book Is For Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.
Author: Julio Sanchez,Maria P. Canton
Publisher: CRC Press
Software requirements for engineering and scientific applications are almost always computational and possess an advanced mathematical component. However, an application that calls for calculating a statistical function, or performs basic differentiation of integration, cannot be easily developed in C++ or most programming languages. In such a case, the engineer or scientist must assume the role of software developer. And even though scientists who take on the role as programmer can sometimes be the originators of major software products, they often waste valuable time developing algorithms that lead to untested and unreliable routines. Software Solutions for Engineers and Scientists addresses the ever present demand for professionals to develop their own software by supplying them with a toolkit and problem-solving resource for developing computational applications. The authors' provide shortcuts to avoid complications, bearing in mind the technical and mathematical ability of their audience. The first section introduces the basic concepts of number systems, storage of numerical data, and machine arithmetic. Chapters on the Intel math unit architecture, data conversions, and the details of math unit programming establish a framework for developing routines in engineering and scientific code. The second part, entitled Application Development, covers the implementation of a C++ program and flowcharting. A tutorial on Windows programming supplies skills that allow readers to create professional quality programs. The section on project engineering examines the software engineering field, describing its common qualities, principles, and paradigms. This is followed by a discussion on the description and specification of software projects, including object-oriented approaches to software development. With the introduction of this volume, professionals can now design effective applications that meet their own field-specific requirements using modern tools and technology.
Author: Brian D. Hahn
The introduction of the Fortran 90 standard is the first significant change in the Fortran language in over 20 years. this book is designed for anyone wanting to learn Fortran for the first time or or a programmer who needs to upgrade from Fortran 77 to Fortran 90. Employing a practical, problem-based approach this book provides a comprehensive introduction to the language. More experienced programmers will find it a useful update to the new standard and will benefit from the emphasis on science and engineering applications.
An Introduction with Advanced Techniques and Examples
Author: John J. Barton,Lee R. Nackman
Publisher: Addison-Wesley Professional
Highlights: builds on knowledge of both FORTRAN and C, the languages most familiar to scientists and engineers; systematically treats object-oriented programming, templates, and the C++ type system; relates the C++ programming process to expressing commonality in the design and implementation of programs; describes how to use existing FORTRAN and C subroutine libraries to implement C++ classes; introduces advanced techniques coordinating templates, inheritance, virtual function interfaces, and exceptions in substantive examples; provides examples, including an extensive family of array classes, smart pointers, class wrappers for LAPACK, classes for abstract algebra and dimensional analysis, function objects, exploiting existing C and FORTRAN libraries, automatic differentiation, and data analysis via nonlinear least squares using the singular value decomposition; and references key sources of new programming ideas and C++ programming techniques.
Author: Jose Luiz Fiadeiro
Publisher: Springer Science & Business Media
Demonstrates how category theory can be used for formal software development. The mathematical toolbox for the Software Engineering in the new age of complex interactive systems.
Author: Brian Hahn,Daniel T. Valentine
Publisher: Academic Press
Category: Technology & Engineering
Essential MATLAB for Engineers and Scientists, Sixth Edition, provides a concise, balanced overview of MATLAB's functionality that facilitates independent learning, with coverage of both the fundamentals and applications. The essentials of MATLAB are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented clearly and intuitively, along with many examples from a wide range of familiar scientific and engineering areas. This updated edition includes the latest MATLAB versions through 2016a, and is an ideal book for a first course on MATLAB, or for an engineering problem-solving course using MATLAB, as well as a self-learning tutorial for professionals and students expected to learn and apply MATLAB. Updated to include all the newer features through MATLAB R2016a Includes new chapter on complex variables analysis Presents a comparison of execution time between compiled and un-compiled code that includes examples Describes the new H2 graphics features