Empirical Software Engineering
As researchers investigate how software gets made, a new empire for empirical research opens up
Software engineering has long considered itself one of the hard sciences. After all, what could be “harder” than ones and zeroes? In reality, though, the rigorous examination of cause and effect that characterizes science has been much less common in this field than in supposedly soft disciplines like marketing, which long ago traded in the gut-based gambles of “Mad Men” for quantitative, analytic approaches.
A growing number of researchers believe software engineering is now at a turning point comparable to the dawn of evidence-based medicine, when the health-care community began examining its practices and sorting out which interventions actually worked and which were just-so stories. This burgeoning field is known as empirical software engineering and as interest in it has exploded over the past decade, it has begun to borrow and adapt research techniques from fields as diverse as anthropology, psychology, industrial engineering and data mining.
The stakes couldn’t be higher. The software industry employs tens of millions of people worldwide; even small increases in their productivity could be worth billions of dollars a year. And with software landing our planes, diagnosing our illnesses and keeping track of the wealth of nations, discovering how to make programs more reliable is hardly an academic question.
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