Since the original article was written, there have been many changes and improvements to the J language. While the mathematically oriented users no doubt drove these, many of the changes have not only simplified the code, but also provided considerable speed up to the operations typical of commercial processing. As a result I have updated the original article with discussion of these changes. J, like its precursor APL, is used in business for financial and mathematical modeling, analysis of large databases, engineering, actuarial work, forecasting, operational research studies, and other applications where a knowledgeable person is mostly employing it in their own work or as a teaching and communications tool. Quite often those employing it are very reticent about how they use it, or just exactly what the application consists of. They view it as conferring a definite edge, a competitive advantage in their business that they would prefers others not be aware of. When competing for fixed price applications development contracts, others are equally disinclined to broadcast the fact that they employ such languages to gain a speed and cost advantage. All this makes it rather difficult for an IT or business manager to evaluate whether J is applicable to their own business. The J language is a powerful interpretive language with a concise syntax. Its very power and conciseness makes it difficult for a novice to master, but also makes it of interest to a manager because little code and effort is required to achieve results. This article discuses the features of J, which make it applicable to typical commercial processing, tasks. It provides simple code examples to illustrate for a manager how little code may be required to implement powerful data manipulation capabilities. Hopefully the article will be of value to those evaluating high-level languages suitable for commercial processing in a distributed, client/server or mainframe environment.

Uncover the necessary steps to building successful software applications.

A breakthrough approach to managing agile software development. Agile methods might just be the alternative to outsourcing. However, agile development must scale in scope and discipline to be acceptable in the boardrooms of the Fortune 1000. In Agile Management for Software Engineering, David J. Anderson shows managers how to apply management science to gain the full business benefits of agility through application of the focused approach taught by Eli Goldratt in his Theory of Constraints. Whether you're using XP, Scrum, FDD, or another agile approach, you'll learn how to develop management discipline for all phases of the engineering process, implement realistic financial and production metrics, and focus on building software that delivers maximum customer value and outstanding business results

Written for software maintenance engineers, this book suggests strategies for debugging code, examines how debuggers function internally, and describes techniques for fine-tuning programs to improve their performance.

A sophisticated yet easy-to-use software program, Microsoft CRM handles the full range of Sales and Customer Service functions, and allows the user to access key customer and sales information from Microsoft Outlook and the Web. It is designed for rapid deployment, ease of use, and integration with Microsoft Office and Microsoft Great Plains' back-office solutions, increasing information reliability, employee usage and productivity.

By using IBM Rational ClearCase, development teams can dramatically improve their productivity and responsiveness throughout the entire software lifecycle. Now, there's an easy-to-use ClearCase deployment guide for every team member: project managers, analysts, developers, and software customers.

Maple is a Symbolic Computation System or Computer Algebra System. Maple manipulates information in a symbolic or algebraic manner. Other conventional mathematical programs require numerical values for all variables. In contrast, Maple maintains and manipulates the underlying symbols and expressions, and evaluates numerical expressions.

This plain English guide on building complex architectures with UML 2 shows how to adjust to the UML 2 standard, extract key information from UML models, object modeling, case modeling and more.

This book arose from a series of courses on computer algebra which were given at Eindhoven Technical University. Its chapters present a variety of topics in computer algebra at an accessible (upper undergraduate/graduate) level with a view towards recentdevelopments. For those wanting to acquaint themselves somewhat further with the material, the book also contains seven 'projects', which could serve as practical sessions related to one or more chapters. The contributions focus on topics like Gröbner bases, real algebraic geometry, Lie algebras, factorisation of polynomials, integer programming, permutation groups, differential equations, coding theory, automatic theorem proving, and polyhedral geometry. This book is a must-read for everybody interested in computer algebra.

Ultimately, software development is about creating value-yet, all too often, applications fail to deliver the business value customers need. This book will help you change that, by linking software development directly to value creation. You'll learn how to identify which features add value and which don't-and refocus on delivering more value, more rapidly.

The software development community widely acknowledges that domain modeling is central to software design. Through domain modeling, software developers are able to express rich functionality and translate that functionality into software implementation that truly serves the needs of its users. Despite its obvious importance, however, there are few practical resources that show how to incorporate effective domain modeling into the software development process.

Computer algebra systems are gaining more and more importance in all areas of sciece and engineering. This textbook gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems.

Computer algebra systems are gaining more and more importance in all areas of science and engineering. This textbook gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems. It is designed to accompany one- or two-semester courses for advanced undergraduate or graduate students in computer science or mathematics. Its comprehensiveness and authority make it also an essential reference for professionals in the area.

The GNU Scientific Library (GSL) is a free numerical library for C and C++ programmers. This reference manual is the definitive guide to the library.

Can open source software - software that is usually available without charge and that individuals are free to modify - survive against the fierce competition of proprietary software, such as Microsoft Windows? Should the government intervene on its behalf? This work addresses a host of issues raised by the rapid growth of open source software, including government procurement policy, and patent and copyright policy. Contributors offer diverse perspectives on a phenomenon that has become a lightning rod for controversy in the field of information technology.

Written by a seasoned pro who has been using Knoppix for years, this lighthearted yet informative book shows hack-hungry fans how to customize Knoppix distributions, create Knoppix-based live CDs, rescue a Windows computer that won't boot, and more.

After introducing Software Factories, the book describes key enabling technologies in depth, and shows how they can be integrated and applied to support a form of Rapid Application Development (RAD).

With the help of this comprehensive guide, you'll discover how your honeypot will capture waves of automated exploits, and how to defend the computer assets under your control.