Fast and sound random generation for automated testing and benchmarking in objective Caml
Benjamin Canou, Alexis Darrasse · 2009
Numerous software testing methods involve random generation of data structures. However, random sampling methods currently in use by testing frameworks are not satisfactory: often manually written by the programmer or at best extracted in an ad-hoc way relying on no theoretical background. On the other end, random sampling methods with good theoretical properties exist but have a too high cost to be used in testing, in particular when large inputs are needed.