
A Large Scale Study of Programming Languages and Code Quality in GitHub [pdf] - nine_k
http://rayb.info/uploads/cacm2017-lang.pdf
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nine_k
_From abstract:_

In this study, we gather a very large data set from GitHub (728 projects, 63
Million SLOC, 29,000 authors, 1.5 million commits, in 17 languages) in an
attempt to shed some empirical light on this question. This reasonably large
sample size allows us to use a mixed-methods approach, combining multiple
regression modeling with visualization and text analytics, to study the effect
of language features such as static v.s. dynamic typing, strong v.s. weak
typing on software quality.

 _From conclusion:_

The data indicates functional languages are better than procedural languages;
it suggests that strong typing is better than weak typing; that static typing
is better than dynamic; and that managed memory usage is better than
unmanaged. Further, that the defect proneness of languages in general is not
associated with software domains. Also, languages are more related to
individual bug categories than bugs overall.

