I have done fair amount of numeric programming and I have not seen any significant benefits from type checking. For me, only these increase robustness: 1. Abil

I have done fair amount of numeric programming and I have not seen any significant benefits from type checking. For me, only these increase robustness: 1. Ability to minimize the amount of code you write. Code you don't write is code without bugs. this means either writing problem specific libraries or having them in the system (Matlab creates more robust code than writing it all by yourself) 2. ability to minimize boilerplate. This is where dynamic languages often win. 3. Ability to change code easily and test or run frequently (not necessarily unit testing). Rewriting usually makes code more robust. Time and money always runs out. Always. The only constant law for selecting programming language for numeric programming is: IF YOU DON'T HAVE TO SPEND SIGNIFICANT TIME OPTIMIZING YOUR CODE AFTERWARDS, YOU ARE USING TOO LOW LEVEL LANGUAGE. If you don't have to optimize for speed, it means that you have been micro-optimizing your code everywhere without even noticing it. This is why C, C++ or Fortran should never be the main programming language you use. Use Python, Common Lisp, Matlab, Haskell, whatever and when you hit performance bottleneck, you write minimal amount of C or C++ code to get over it.