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Socio-PLT: Quantitative and Social Theories for Programming Language Adoption

Google Tech Talk November 14, 2012 Presented by Leo A. Meyerovich ABSTRACT Why do some programming languages succeed and others fail? We have been tackling this basic question in two ways: First, I will discuss theories from the social sciences about the adoption process and what that means for designing new languages. For example, the Haskell and type systems communities may be suffering some of the same challenges that the public health community did for safe sex advocacy in the early nineties. Second, informed by these studies, we gathered and quantitatively analyzed several large datasets, including over 200000 SourceForge projects and multiple surveys of 1000-13000 programmers. We find that social factors usually outweigh intrinsic technical ones. In fact, the larger the organization, the more important social factors become. I'll report on additional surprises about the popularity, perception, and learning of programming languages. Taken together, our results help explain the process by which languages become adopted or not. Speaker Info: Leo A. Meyerovich is a Ph.D. candidate at UC Berkeley researching browser parallelization, the Superconductor language for visualizing big data, and language adoption. Earlier, he worked on security extensions for JavaScript and the Flapjax language for functional reactive web programming (

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Hi, I'm working on the National Vulnerability Database (NVD). I want to categorise the vulnerable software by category. I already have the categories and a good training set to feed into a machine learning algorithm.

The original idea was to use the description of the vulnerability in NVD to categorise the software, but this won't obviously work (because it doesn't describe the software).

Then we thought to download the first paragraph of the Wikipedia entry for that software. This works only 10% of the time, as many entries do not match any page. This is an example of a page that cannot load Further manual google queries seem to identify that software as a VOIP server. In some other cases, e.g. for the software Swift, the returned page is definitely not related to the software, and in the disambiguation page#Software_and_information_technology) it is not even clear which entry should be the one of interest.

Do you have suggestions to mitigate this problem? More reliable software-related databases other than wikipedia? Better ways to query the dataset instead of feeding the bare software name provided by NVD (e.g. up-ux_v, vendor:Nec)? Ways to include the vendor in the query, so to make the results more reliable?

Ever faced a problem like that?


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Stack Exchange

This Q&A is part of a biweekly series of posts highlighting common questions encountered by technophiles and answered by users at Stack Exchange, a free, community-powered network of 80+ Q&A sites.

SomeKittens asks:

In my few years of programming, I've toyed with everything from Ruby to C++. I've done everything from just learning basic syntax (Ruby) to completing several major (for me) projects that stretched my abilities with the language.

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