This change adds a fuzzer pass that allows code from other SPIR-V
modules to be donated into the module under transformation. It also
changes the command-line options of the tools so that, in fuzzing
mode, a file must be specified that contains the names of available
donor modules.
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.
A new pass that allows the fuzzer to change the 'loop control' operand
(and associated literal operands) of OpLoopMerge instructions.
Fixes#2938.
Fixes#2943.
Adds a fuzzer pass and transformation to create a composite (array,
matrix, struct or vector) from available constituent components, and
inform the fact manager that each component of the new composite is
synonymous with the id that was used to construct it. This allows the
"replace id with synonym" pass to then replace uses of said ids with
uses of elements extracted from the composite.
Fixes#2858.
This change to spirv-fuzz uses ideas from "Swarm Testing" (Groce et al. 2012), so that a random subset of fuzzer passes are enabled. These passes are then applied repeatedly in a randomized fashion, with the aggression with which they are applied being randomly chosen per pass.
There is plenty of scope for refining the probabilities introduce in this change; this is just meant to be a reasonable first effort.
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.
The recently added fuzzer_replayer and fuzzer_shrinker tests were
rather heavyweight and were leading to CI timeouts. This change
reduces the runtime of those tests by having them do fewer iterations.
Similar to the existing 'add dead breaks' pass, this adds a pass to
add dead continues to blocks in loops where such a transformation is
viable. Various functionality common to this new pass and 'add dead
breaks' has been factored into 'fuzzer_util', and some small
improvements to 'add dead breaks' that were identified while reviewing
that code again have been applied.
Fixes#2719.
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.
* Represent uniform facts via descriptor set and binding.
Previously uniform facts were expressed with resepect to the id of a
uniform variable. Describing them with respect to a descriptor set
and binding is more convenient from the point of view of expressing
facts about a shader without requiring analysis of its SPIR-V.
* Fix equality testing for uniform buffer element descriptors.
The equality test now checks that the lengths of the index vectors
match. Added a test that exposes the previous omission.
Adds a new transformation that can replace a constant with a uniform known to have the same value, and adds a fuzzer pass that (a) replaces a boolean with a comparison of literals (e.g. replacing "true" with "42 > 24"), and then (b) obfuscates the literals appearing in this comparison by replacing them with identically-valued uniforms, if available.
The fuzzer_replayer test file has also been updated to allow initial facts to be provided, and to do error checking of the status results returned by the fuzzer and replayer components.
The replayer takes an existing sequence of transformations and applies
them to a module. Replaying a sequence of transformations that were
obtained via fuzzing should lead to an identical module to the module
that was fuzzed. Tests have been added to check for this.
