Given the lack of evidence to support the claim I find the argument specious. There are large code bases written in dynamic languages that are well maintained by thousands of contributors that could weaken such a claim without strong data backing it up (OpenStack comes to mind). The author fails to provide a link to a single study and relies purely on intuition for eir argument.
I only see one link to that answer on SO that points to a single study. It was provided by another commentator asking for the OP to provide evidence for the "strong correlation," claim. Not very good.
Though I'd hate to work with a team that used a statically typed language and tools that didn't write tests for their software. It's not magic soya-sauce that frees you from ever introducing bugs into your software. Most static analyzers I've seen for C-like languages involve computing the fixed-point from a graph (ie: looking for convergence). Generics makes things a little trickier. Tests are as much about specification as they are about correctness.
In my experience there are some things you will only ever know at run-time and the trade-off in flexibility for static analysis is not very beneficial in most cases.
Some interesting areas in program analysis are, imho, the intersection of logic programming, decomposition methods and constraint programming as applied to whole-program analysis. Projects like kibit in Clojure-land are neat and it would be cool to see them applied more generally to other problems such as, "correctness," and the like.
My experience with Python had been that scaling to large code bases is possible, but the burden of the late runtime errors and lack of type documentation accumulates.
The beginning of the project is wonderfully productive. By the time you regret having chosen a dynamic language for the project, it's too late to switch.
I only see one link to that answer on SO that points to a single study. It was provided by another commentator asking for the OP to provide evidence for the "strong correlation," claim. Not very good.
Though I'd hate to work with a team that used a statically typed language and tools that didn't write tests for their software. It's not magic soya-sauce that frees you from ever introducing bugs into your software. Most static analyzers I've seen for C-like languages involve computing the fixed-point from a graph (ie: looking for convergence). Generics makes things a little trickier. Tests are as much about specification as they are about correctness.
In my experience there are some things you will only ever know at run-time and the trade-off in flexibility for static analysis is not very beneficial in most cases.
Some interesting areas in program analysis are, imho, the intersection of logic programming, decomposition methods and constraint programming as applied to whole-program analysis. Projects like kibit in Clojure-land are neat and it would be cool to see them applied more generally to other problems such as, "correctness," and the like.