  Cryptic type error messages are a major obstacle to learning OCaml or other
ML-based languages. In many cases, error messages cannot be interpreted without
a sufficiently-precise model of the type inference algorithm. The problem of
improving type error messages in ML has received quite a bit of attention over
the past two decades, and many different strategies have been considered. The
challenge is not only to produce error messages that are both sufficiently
concise and systematically useful to the programmer, but also to handle a
full-blown programming language and to cope with large-sized programs
efficiently.
  In this work, we present a modification to the traditional ML type inference
algorithm implemented in OCaml that, by significantly reducing the
left-to-right bias, allows us to report error messages that are more helpful to
the programmer. Our algorithm remains fully predictable and continues to
produce fairly concise error messages that always help making some progress
towards fixing the code. We implemented our approach as a patch to the OCaml
compiler in just a few hundred lines of code. We believe that this patch should
benefit not just to beginners, but also to experienced programs developing
large-scale OCaml programs.
