While debating which platform to use for what applications (specifically we debated c++, java, c# and f#) we tried finding scientific quality research on productivity (cost of ownership really) of similar applications build on various platforms/using the above mentioned languages. Any one know of such research?
EDIT: I see several have commented that the requested kind of research does not exist/cannot be executed. So I thought I'd clarified, since the kind of research I'm asking for is executable (and I know I've read one survey already but forgotten the source)
I'm not asking for a study that gives conclusion on what platform/language that would be the most productive "hammer" for any "nail". I'm asking for reasearch that given a set of precodition (as all research have) e.g. kind of HW platform, kind of application with comparable competencies in the staff, investigates on the tools (specifically language) and their impact on productivity. I'm not trying to start a religious war, that's why I'm not asking for peoples opinions but scientific quality research :)
Material productivity is expressed as the amount of economic output generated (in terms of GDP) per unit of materials consumed (in terms of DMC). This indicator is measured in USD constant prices using 2010 base year and Purchasing Power Parities (PPPs).
Total Factor Productivity There are many factors that impact a country's productivity. Such things include investment in plant and equipment, innovation, improvements in supply chain logistics, education, enterprise, and competition.
Several studies over the past few months show productivity while working remotely from home is better than working in an office setting. On average, those who work from home spend 10 minutes less a day being unproductive, work one more day a week, and are 47% more productive.
Here's a C++ vs Java study.
Here's a semi-scientific study of Python/Django vs. C#.
And here's one on Java vs. C# vs. Ada.
Whatever languages you're interested in comparing, do a Google search for
study of [LanguageX] vs [LanguageY]
and see what you can glean.
But I agree with most everyone else that as long as you're in the right ballpark with your language selection, the rest of your productivity rests with the quality of your tools and people, not with whether you choose Perl or Python.
This isn't science, but it's based on 28 years in the business, observing and participating in teams which used a huge array of technologies, from assembly up through a long list of higher-level languages, plus of course a litany of methodological silver-bullet-du-jours:
What really affects productivity is your people - specifically, how good they are, and how well led they are.
So if you're trying to pick a language or other technology, go for the one with which more of your team is competent. If that's a tossup, or if it's truly green-field, hire the best people you can find, and then pick the tech best supported by the vendors whose tech you'll be dependent on... or toss a coin.
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