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I am very pleased to write these few brief paragraphs introducing this book, and would like to take this opportunity to attempt to set the Toolpack project in an appropriate historical context. The Toolpack project must be considered to have actually began in the Fall of 1978, when Prof. Webb C. Miller, at a meeting at Jet Propulsion Laboratories in Pasadena, California, suggested that there be a large-scale project, called Toolpack, aimed at pulling together a comprehensive collection of mathematical software development tools. It was suggested that the project follow the pattern of other "Pack" projects, such as Eispack, Linpack, and Funpack which had assembled and systematized comprehensive collections of mathematical software in such areas as eigenvalue computation, linear equation solution and special function approximation. From the that the Toolpack project would differ significantly from beginning it was recognized these earlier "Pack" projects in that it was attempting to assemble and systematize software in an area which was not well established and understood. Thus it was not clear how to organize and integrate the tools we were to collect into Toolpack. As a consequence Toolpack became simultaneously a research project and a development project. The research was aimed at determining effective strategies for large-scale integration of large-scale software tools, and the development project was aimed at implementing these strategies and using them to put high quality tools at the disposal of working mathematical software writers.
Includes articles in topic areas such as autonomic computing, operating system architectures, and open source software technologies and applications.
Hardbound. The aim of this conference was to investigate the motivation for and development of Problem Solving Environments (PSEs) for Scientific Computing. The meeting was interdisciplinary, including experts in Physics, Chemistry, Oceanography, Biology and fields of Engineering, as well as authorities in Software Engineering, Numerical Software Construction, Computing Science, Computational Mathematics and Statistics.Whilst some Working Conferences are essentially review meetings in the course of the development of a particular field, it is evident that focussed consideration of problem solving environments for many people started with this meeting.
The 2nd edition of this integrated guide explains and lists readily available graphics software tools and their applications, while also serving as a shortcut to graphics theory and programming. It grounds readers in fundamental concepts and helps them use visualization, modeling, simulation, and virtual reality to complement and improve their work.
Rapid Application Generation of Business and Finance Software describes a method for developing wide ranging computing applications with emerging software technologies. The pressure of the market place calls for reducing the time to market of new software applications. This book shows how to build such software faster and more reliably. Using an elegant concept of extended tools, the book presents a method for the constructive building of `hybrid' applications. The book includes such application areas as direct marketing, banking insurance and executive information systems. The methods used adopt the latest object-oriented and client-server techniques. Rapid Application Generation of Business and Finance Software is an important book for computer scientists working on rapid application development. It is also of interest to information systems specialists.
Product verifiable, defensible, and achievable software estimates Based on data collected by the International Software Benchmarking Standards Group (ISBSG), Practical Software Project Estimation explains how to accurately forecast the size, cost, and schedule of software projects. Get expert advice on generating accurate estimates, minimizing risks, and planning and managing projects. Valuable appendixes provide estimation equations, delivery rate tables, and the ISBSG Repository demographics. Verify project objectives and requirements Determine, validate, and refine software functional size Produce indicative estimates using regression equations Predict effect and duration through comparison and analogy Build estimation frameworks Perform benchmarks using the ISBSG Repository Compare IFPUG, COSMIC, and FiSMA sizing methods Peter Hill is the chief executive officer and a director of the ISBSG. He has been in the information services industry for more than 40 years and has compiled and edited five books for the ISBSG.