Since the 70s, the C preprocessor is still widely used in practice in a number of projects to tailor systems to different platforms and application scenarios. In academia, researchers have criticized its lack of separation of concerns, its proneness to introduce subtle errors, and its obfuscation of the source code. To better understand the problems of using the C preprocessor, we conducted 40 interviews and a survey among 202 developers. We found that developers deal with three common problems in practice: configuration-related bugs, combinatorial testing, and code comprehension. To better deal with these problems, this book presents strategies to detect bugs and bad smells in preprocessor-based systems based on variability-aware analysis and sampling. This work presents useful findings for C developers during their development tasks, contributing to minimize the chances of introducing configuration-related bugs and bad smells, improve code comprehension, and guide developers to perform combinatorial testing.
Master functions and discover how to write functional programs in R. In this concise book, you´ll make your functions pure by avoiding side-effects; you´ll write functions that manipulate other functions, and you´ll construct complex functions using simpler functions as building blocks. In Functional Programming in R , you´ll see how we can replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn´t use recursion when loops are more efficient and how you can get the best of both worlds. Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions. What You´ll Learn Write functions in R including infix operators and replacement functions Create higher order functions Pass functions to other functions and start using functions as data you can manipulate Use Filer, Map and Reduce functions to express the intent behind code clearly and safely Build new functions from existing functions without necessarily writing any new functions, using point-free programming Create functions that carry data along with them Who This Book Is For Those with at least some experience with programming in R.