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Making Software by Greg Wilson, Andy Oram

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Surveying Software

The first step in this study was to select a representative sample of software, just like surveys in the social sciences. From a known population, statistical methods allow us to obtain the minimum sample size that lets us extract conclusions with a given uncertainty. For instance, the U.S. population is about 300 million people at the moment of writing this text; exit polls can accurately predict the results of elections if the size of the polled sample is large enough, say, 30,000 people.

The problem with this approach when carried over to software engineering is that we do not know the size of the world’s software. So we cannot determine a minimum sample that can answer our questions with a given uncertainty, and the classic “survey approach” to the whole population of software becomes unfeasible.

However, even though the whole population of software is indeterminable, a portion of that population is open, accessible for research, and willing to share its source code with the world: open source software. Of course, restricting our population to this kind of software should theoretically bind the answer to our initial question to this kind of software. But when all is said and done, the only difference between open source and closed source software is the license. Although open source software is usually developed using particular practices (projects that are community-driven, source code available, etc.), the open source software population is very heterogeneous, ...

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