The Art Of Debugging With Gdb Ddd And Eclipse

Provides information on using three debugging tools on the Linux/Unix platforms, covering such topics as inspecting variables and data structures, understanding segmentation faults and core dumps, using catchpoints and artificial arrays, and avoiding debu

This book is an authoritative guide to the art of debugging, covering two of the most popular debuggers--GDB and DDD--and discussing other tools that help prevent, catch, and fix bugs in programs.

Many Linux and Unix developers are familiar with the GNU debugger (GBD), the invaluable open source tool for testing, fixing, and retesting software. And since GDB can be ported to Windows, Microsoft developers and others who use this platform can also take advantage of this amazing free software that allows you to see exactly what's going on inside of a program as it's executing. This new pocket guide gives you a convenient quick reference for using the debugger with several different programming languages, including C, C++, Java, Fortran and Assembly. The GNU debugger is the most useful tool during the testing phase of the software development cycle because it helps you catch bugs in the act. You can see what a program was doing at the moment it crashed, and then readily pinpoint and correct problem code. With the GDB Pocket Reference on hand, the process is quick and painless. The book covers the essentials of using GBD is a testing environment, including how to specify a target for debugging and how to make a program stop on specified conditions. This handy guide also provides details on using the debugger to examine the stack, source files and data to find the cause of program failure-and then explains ways to use GBD to make quick changes to the program for further testing and debugging. The ability to spot a bug in real time with GDB can save you hours of frustration, and having a quick way to refer to GBD's essential functions is key to making the process work. Once you get your hands on the GDB Pocket Reference, you'll never let go!

Learn to expertly apply a range of machine learning methods to real data with this practical guide. Packed with real datasets and practical examples, The Art of Machine Learning will help you develop an intuitive understanding of how and why ML methods work, without the need for advanced math. As you work through the book, you’ll learn how to implement a range of powerful ML techniques, starting with the k-Nearest Neighbors (k-NN) method and random forests, and moving on to gradient boosting, support vector machines (SVMs), neural networks, and more. With the aid of real datasets, you’ll delve into regression models through the use of a bike-sharing dataset, explore decision trees by leveraging New York City taxi data, and dissect parametric methods with baseball player stats. You’ll also find expert tips for avoiding common problems, like handling “dirty” or unbalanced data, and how to troubleshoot pitfalls. You’ll also explore: How to deal with large datasets and techniques for dimension reduction Details on how the Bias-Variance Trade-off plays out in specific ML methods Models based on linear relationships, including ridge and LASSO regression Real-world image and text classification and how to handle time series data Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you’ll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use. Requirements: A basic understanding of graphs and charts and familiarity with the R programming language

Every software developer and IT professional understands the crucial importance of effective debugging. Often, debugging consumes most of a developer’s workday, and mastering the required techniques and skills can take a lifetime. In Effective Debugging, Diomidis Spinellis helps experienced programmers accelerate their journey to mastery, by systematically categorizing, explaining, and illustrating the most useful debugging methods, strategies, techniques, and tools. Drawing on more than thirty-five years of experience, Spinellis expands your arsenal of debugging techniques, helping you choose the best approaches for each challenge. He presents vendor-neutral, example-rich advice on general principles, high-level strategies, concrete techniques, high-efficiency tools, creative tricks, and the behavioral traits associated with effective debugging. Spinellis’s 66 expert techniques address every facet of debugging and are illustrated with step-by-step instructions and actual code. He addresses the full spectrum of problems that can arise in modern software systems, especially problems caused by complex interactions among components and services running on hosts scattered around the planet. Whether you’re debugging isolated runtime errors or catastrophic enterprise system failures, this guide will help you get the job done—more quickly, and with less pain. Key features include High-level strategies and methods for addressing diverse software failures Specific techniques to apply when programming, compiling, and running code Better ways to make the most of your debugger General-purpose skills and tools worth investing in Advanced ideas and techniques for escaping dead-ends and the maze of complexity Advice for making programs easier to debug Specialized approaches for debugging multithreaded, asynchronous, and embedded code Bug avoidance through improved software design, construction, and management

R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: –Create artful graphs to visualize complex data sets and functions –Write more efficient code using parallel R and vectorization –Interface R with C/C++ and Python for increased speed or functionality –Find new R packages for text analysis, image manipulation, and more –Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

This book provides the reader with a comprehensive overview of the new open source programming language Go (in its first stable and maintained release Go 1) from Google. The language is devised with Java / C#-like syntax so as to feel familiar to the bulk of programmers today, but Go code is much cleaner and simpler to read, thus increasing the productivity of developers. You will see how Go: simplifies programming with slices, maps, structs and interfaces incorporates functional programming makes error-handling easy and secure simplifies concurrent and parallel programming with goroutines and channels And you will learn how to: make use of Go's excellent standard library program Go the idiomatic way using patterns and best practices in over 225 working examples and 135 exercises This book focuses on the aspects that the reader needs to take part in the coming software revolution using Go.