https://bugzilla.redhat.com/show_bug.cgi?id=2391039

            Bug ID: 2391039
           Summary: Review Request: ocaml-monolith - Framework for strong
                    random testing of OCaml libraries
           Product: Fedora
           Version: rawhide
          Hardware: All
                OS: Linux
            Status: NEW
         Component: Package Review
          Severity: medium
          Priority: medium
          Assignee: [email protected]
          Reporter: [email protected]
        QA Contact: [email protected]
                CC: [email protected]
  Target Milestone: ---
    Classification: Fedora



Spec URL: https://jjames.fedorapeople.org/ocaml-monolith/ocaml-monolith.spec
SRPM URL:
https://jjames.fedorapeople.org/ocaml-monolith/ocaml-monolith-20250314-1.fc44.src.rpm
Fedora Account System Username: jjames
Description: Monolith offers facilities for testing an OCaml library (for
instance, a data structure implementation) by comparing it against a reference
implementation.  It can be used to perform either random testing or fuzz
testing.  Fuzz testing relies on the external tool afl-fuzz.

The user must describe what types and operations the library provides.  Under
the best circumstances, this requires 2-3 lines of code per type or operation. 
The user must also provide a reference implementation and a candidate
implementation of the library.

Then, like a monkey typing on a keyboard, Monolith attempts to exercise the
library in every possible way, in the hope of discovering a sequence of
operations that leads to an unexpected behavior (that is, a situation where the
library either raises an unexpected exception or returns an incorrect result). 
If such a scenario is discovered, it is printed in the form of an OCaml
program, so as to help the user reproduce the problem.

Monolith assumes that the candidate implementation behaves in a deterministic
way.  (Without this assumption, one cannot hope to reliably produce a
problematic scenario.)  It does however allow nondeterministic specifications,
that is, situations where the candidate implementation is allowed to behave in
several possible ways.


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