Speed up stateful testing with many rules#4746
Merged
Zac-HD merged 1 commit intoMay 27, 2026
Merged
Conversation
Selecting which rule to run next repeated work that scales with the number of rules on every step - most notably recomputing the uncached label of the rule-selection strategy, which was rebuilt from scratch each step. Reuse a single filtered strategy across steps, and cache the per-class setup (sorting the rules and building the underlying strategy) so it runs once per class rather than each time the machine is instantiated. https://claude.ai/code/session_01AnXgxUP11ftXiFNH8wXATk
Liam-DeVoe
approved these changes
May 27, 2026
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Selecting which rule to run next repeated work that scales with the number of rules on every step - most notably recomputing the uncached label of the rule-selection strategy, which was rebuilt from scratch each step. Reuse a single filtered strategy across steps, and cache the per-class setup (sorting the rules and building the underlying strategy) so it runs once per class rather than each time the machine is instantiated.
Closes #4465; while derandomize gives us different workloads per n_rules the trend is pretty clear: