Throw out your old ideas about C and get to know a programming language that's substantially outgrown its origins. With this revised edition of 21st Century C, you'll discover up-to-date techniques missing from other C tutorials, whether you're new to the language or just getting reacquainted. C isn't just the foundation of modern programming languages; it is a modern language, ideal for writing efficient, state-of-the-art applications. Get past idioms that made sense on mainframes and learn the tools you need to work with this evolved and aggressively simple language. No matter what programming language you currently favor, you'll quickly see that 21st century C rocks. Set up a C programming environment with shell facilities, makefiles, text editors, debuggers, and memory checkers Use Autotools, C's de facto cross-platform package manager Learn about the problematic C concepts too useful to discard Solve C's string-building problems with C-standard functions Use modern syntactic features for functions that take structured inputs Build high-level, object-based libraries and programs Perform advanced math, talk to internet servers, and run databases with existing C libraries This edition also includes new material on concurrent threads, virtual tables, C99 numeric types, and other features.

"Modeling with Data" fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.

Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date.

"Modeling with Data" will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.

This lively and innovative book is about computer code and the legal controls and restrictions on those who write it. The widespread use of personal computers and the Internet have made it possible to release new data or tools instantaneously to virtually the entire world. However, while the digital revolution allows quick and extensive use of these intellectual properties, it also means that their developers face new challenges in retaining their rights as creators. Drawing on a host of examples, Ben Klemens describes and analyzes the intellectual property issues involved in the development of computer software. He focuses on software patents because of their powerful effect on the software market, but he also provides an extensive discussion of how traditional copyright laws can be applied to code. The book concludes with a discussion of recommendations to ease the constraints on software development. This is the first book to confront these problems with serious policy solutions. It is sure to become the standard reference for software developers, those concerned with intellectual property issues, and for policymakers seeking direction. It is critical that public policy on these issues facilitates progress rather than hindering it. There is too much at stake.