Making Software - What Really Works, and Why We Believe It

Making Software - What Really Works, and Why We Believe It. Does the MMR vaccine cause autism? Does watching violence on TV make children more violent? Are some programming languages better than others? People argue about these questions every day. Every serious attempt to answer the first two questions relies on the scientific met hod: careful collection of evidence, and impartial evaluation of its implications. Until recently, though, only a few people have tried to apply these techniques to the third. When it comes to computing, it often seems that a couple glasses of beer and an anecdote about a startup in Warsaw are all the “evidence” most programmers expect. That is changing, thanks in part to the work of the contributors to this book. Drawing on fields as diverse as data mining, cognitive psychology, and sociology, they and their colleagues are creating an evidence-based approach to software engineering. By gathering evidence drawn from a myriad of primary sources and analyzing the results, they are shedding new light onto some vexing questions of software development. What do most programmers get wrong in their first job? Does test-driven development lead to better code? What about pair programming, or code reviews? Is it possible to predict the likely number of bugs in a piece of code before it’s released? If so, how? hod: careful collection of evidence, and impartial evaluation of its implications. Until recently, though, only a few people have tried to apply these techniques to the third. When it comes to computing, it often seems that a couple glasses of beer and an anecdote about a startup in Warsaw are all the “evidence” most programmers expect. That is changing, thanks in part to the work of the contributors to this book. Drawing on fields as diverse as data mining, cognitive psychology, and sociology, they and their colleagues are creating an evidence-based approach to software engineering. By gathering evidence drawn from a myriad of primary sources and analyzing the results, they are shedding new light onto some vexing questions of software development. What do most programmers get wrong in their first job? Does test-driven development lead to better code? What about pair programming, or code reviews? Is it possible to predict the likely number of bugs in a piece of code before it’s released? If so, how?