package monolith

Monolith

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.

Installation

To install the latest released version, type:

  opam update
  opam install monolith

To install the latest development version, type:

  git clone git@gitlab.inria.fr:fpottier/monolith
  cd monolith
  opam pin add monolith .

Documentation

The documentation of the latest released version is available online.

The documentation is built locally by make doc and can be viewed via make view.

Papers

The paper Strong Automated Testing of OCaml Libraries by François Pottier describes the use and the design of Monolith in somewhat greater depth than the documentation.

Demos and Workflow

A number of demos are found under demos/. The demos under demos/working do not have any known bugs, so make test should run forever without finding any problem. The demos under demos/faulty intentionally contain bugs, so make test should very quickly find a number of problems.

Some demos require external libraries. Running make dependencies once at the top level should install all of the libraries needed by the demos.

These demos share a common workflow, which is implemented in Makefile.monolith. This file is installed at the same time as the library. The directory where it resides can be found via the command ocamlfind query monolith.

First, the external tool afl-fuzz must be installed. Here is a suggested installation script.

Then, an appropriate opam switch, such as 4.09.1+afl, must be created. The name of this switch is controlled by the variable SWITCH. This variable can be set by passing something like SWITCH=4.09.1+afl on the command line in every make invocation, or (better) in a parent Makefile which includes Makefile.monolith.

Creating an opam switch is done only once, as follows:

  make setup               # this takes a few minutes

If you are using MacOS, you will probably need to disable the system's built-in crash reporter by typing make unload. (Otherwise, afl-fuzz will complain.)

If you are using an antivirus, it is advisable to disable it. As a case in point, Kaspersky Endpoint Security on MacOS imposes a 5x speed penalty when its protection is turned on.

After these steps, you are ready to run a demo. In each subdirectory of demos, testing is carried out as follows:

  make test

This launches afl-fuzz, which keeps running forever, or until it is interrupted by Ctrl-C. The number of problematic scenarios (also known as crashes) found by afl-fuzz is displayed in red.

Once one or more crashes have been found and afl-fuzz has been interrupted, it is recommended to first minimize the problem scenarios by using make min.

Then, you can ask for a report using either make show (which produces OCaml code for each crash) or make summary (which shows a one-line summary of each crash, by decreasing order of length).

A typical workflow is to first use make summary, so as to reveal the length of the shortest crash, then type make show and search its output (by typing /) for the shortest crash.

To perform purely random testing, without using afl-fuzz, type:

  make random

This uses a single processor core and runs in an infinite loop until a problem is detected. Random testing is significantly faster than fuzz testing, so it may be a good idea to first look for obvious bugs using random testing, then look for nastier bugs using fuzz testing.

When running in random mode, after Monolith has a found a scenario, it reduces the amount of fuel and continues searching for a shorter scenario. It is therefore possible to start with a relatively large amount of fuel.

Parallel Fuzzing

The command make test launches only one afl-fuzz process. Once you are confident that it works, you can instead use make multicore or make tmux, which launch several processes in parallel. They differ in their user interface: whereas make multicore displays only periodic progress reports in the terminal, make tmux splits the terminal window using tmux and shows the activity of each afl-fuzz process in its own pane.

These commands launch one master process plus a number of slave processes. The number of slave processes can be adjusted via the command line: for instance, make SLAVES=1 tmux uses just one master process and one slave process.

While parallel fuzzing is ongoing, typing make whatsup displays a progress report. The most interesting line is Crashes found, which reports the number of violations found so far. The Cumulative speed line is also of interest, but be aware that it seems to take a few minutes for this information to become stable.

Performance

Performance is measured in executions per second. It is visible in the interactive interface, and is also reported by make whatsup.

Of course, the performance that you can expect depends on the cost of the operations that you are testing. As a single data point, in a version of the map demo, on a Linux machine equipped with two eight-core Intel Xeon CPUs (E5-2620 v4 @ 2.10GHz), I am seeing 12k execs/second when using a single afl-fuzz process, and about 5k execs/second/core when using all 32 cores in parallel (therefore, about 160k execs/second).

Fuzzing under MacOS appears to be about 10 times slower, although I do not know why; I have disabled both the MacOS crash reporter and the antivirus.

Real-World Applications

Monolith has been used to test Sek, a library that offers 4 abstract types and well over 100 operations on them.