Sourcing Developers in Source Code

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Searching for Software Engineers seems to be on many Sourcers’ minds. Finding “someone” qualified can be easy. They may be on LinkedIn, or Github, or Stackoverflow, or Google-Plus, or with resumes online,  and often on all of these sites at the same time. But if that coding guru is easily found, you are competing with “everybody else” for her attention. You might be even competing with recruiters from your own company (yikes) (as a friend who recently joined a software giant with a big brand name tells me).

The task then becomes, find Software Engineers that are hard to find!

( once specifically created a list of highly qualified Developers found on Github who didn’t have LinkedIn profiles and reached out to them;  they were very responsive, even offering references if they were not open to opportunities.)

There are endless ways to be creative, looking for people that would not be found on LinkedIn and other “mainstream” channels. One way you may want to try is to source Software Engineers within the Source Code in the programming languages they use. Let’s explore how to use Google’s filetype: operator for that.

Google’s official file types list includes:

  • Basic source code (.bas)
  • C/C++ source code (.c, .cc, .cpp, .cxx, .h, .hpp)
  • C# source code (.cs)
  • Java source code (.java)
  • Perl source code (.pl)
  • Python source code (.py)

But in fact, Google will recognize many more file types for software source code files. As long as a file contains code in a programming language, that is text, that someone typed in, Google should be able to “understand” it. Here’s a list with more source code file extentions, and even more can be found here.

If the author decides to leave a contact email in the code, that contact can be found. Of course, these searches, targeting programming languages and email addresses, will have to be very wide. But we know how to cross-reference lists of emails (Rapportive, Google-Plus, Outlook Social Connector, LinkedIn Contacts are just some ways to do that) and quickly narrow the lists down to the right locations and to other target parameters.

In addition to using the fitelype: operator, we may want to specifically X-Ray some sites with open source software code, such as Bitbucket, Google code, and Sourceforge, to name a few.

Combining all of the above, here are some sample searches to play with (perhaps, add some specific keywords that you expect to find as well):

These searches may find top coders that may be hard to find on the most common channels. Sometimes, they will discover developers that can be found, say, on LinkedIn, but with a different email address that the developer is likelier to check, which can also open doors to initial communication. Maybe you can even tell them that you have looked at some source code; I suppose that would make you stand out from the crowd in the eyes of a developer. Of course, an additional (intrinsic) advantage is that you would have the contact email address, which is not the case with LinkedIn searches.

As a quick example, this search within JavaScript source code files instantly finds about 50 email addresses, including those pointing to this profile and this profile on LinkedIn, that others are unlikely to find due to the lack of keywords (at the time of this post).

My webinar on the topic of finding “techies” has been popular; check it out if you might be interested in a 90-minutes recording with many more tips and a month of support.