This change introduces various strategies for controlling the manner
in which fuzzer passes are applied repeatedly, including infrastructure
to allow fuzzer passes to be recommended based on which passes ran
previously.
Adds an option to run the validator on the SPIR-V binary after each
fuzzer pass has been applied, to help identify when the fuzzer has
made the module invalid. Also adds a helper method to allow dumping
of the sequence of transformations that have been applied to a JSON
file.
To aid in debugging issues in spirv-fuzz, this change adds an option whereby the SPIR-V module is validated after each transformation is applied during replay. This can assist in finding a transformation that erroneously makes the module invalid, so that said transformation can be debugged.
Adds to spirv-fuzz the option to shrink a sequence of transformations
that lead to an interesting binary to be generated, to find a smaller
sub-sequence of transformations that still lead to an interesting (but
hopefully simpler) binary being generated. The notion of what counts
as "interesting" comes from a user-provided script, the
"interestingness function", similar to the way the spirv-reduce tool
works. The shrinking process will give up after a maximum number of
steps, which can be configured on the command line.
Tests for the combination of fuzzing and shrinking are included, using
a variety of interestingness functions.
Adds a library for spirv-fuzz, consisting of a Fuzzer class that will
transform a module with respect to (a) facts about the module provided
via a FactManager class, and (b) a source of random numbers and
parameters to control the transformation process provided via a
FuzzerContext class. Transformations will be applied via classes that
implement a FuzzerPass interface, and both facts and transformations
will be represented via protobuf messages. Currently there are no
concrete facts, transformations nor fuzzer passes; these will follow.