Many claims are made about how certain tools, technologies, and practices improve software development. Software application development methodologies continue to jostle for recognition (and ultimately adoption) among the programmer cognoscenti around the globe. When waterfall is out, Agile is in. When "lean scrum" clustering for application development is out, Rational Unified Process and more “systems level” architecting is in.
But which claims are verifiable and which are merely wishful thinking — and what really works?
In truth, we now have so much “information about information,” so much “data management” to help deal with our data that we sometimes appear to be at a tipping point when even meta-tagging and data optimization tools seem to lead us into brick walls.
In Making Software: What Really Works, and Why We Believe It (O'Reilly Media), contributors including Steve McConnell, Barry Boehm, Jorge Aranda, Andreas Zeller, and Barbara Kitchenham offer essays that uncover what they call the “truth" and "unmask myths” commonly held within the software development community.
The book is edited by Andy Oram and longtime Dr. Dobb's contributor Gregory V. Wilson.
According to the publishers, the insights collected in this book may surprise you:
- Are some programmers really ten times more productive than others?
- Does writing tests first help you develop better code faster?
- Can code metrics predict the number of bugs in a piece of software?
- Do design patterns actually make better software?
- What effect does personality have on pair programming?
- What matters more: How far apart people are geographically, or how far apart they are in the org chart?
"We call ourselves 'engineers', but programming processes are mostly dictated by comfort and momentum instead of being driven by data. With this wealth of empirical data about writing code, finally our processes can be as scientific as our personalities," said Jason Cohen, founder of Smart Bear & WPEngine and guest author in this book.