chore(deps): Bump rstest from 0.18.2 to 0.19.0

[dependabot]

Bumps rstest from 0.18.2 to 0.19.0.

Release notes

Sourced from rstest's releases.

Introduce MSRV and minor fixes

Changelog

Sourced from rstest's changelog.

[0.19.0] 2024/4/9

Changed

• Defined rust-version for each crate (see #227)

Fixed

• #[once] fixtures now require the returned type to be Sync to prevent UB when tests are executed in parallel. (see #235 for more details)

• #[future(awt)] and #[awt] now properly handle mutable (mut) parameters by treating futures as immutable and treating the awaited rebinding as mutable.

Commits

• 3ffd682 Fix license links
• 36ab06d Fix license link
• 941d8ac Update changelog
• cdff674 Bump version
• e0624fe Fix clippy warning
• f7b4b57 Shutup warning on nightly (tests)
• 49a7d38 Shutup warning in night
• b58ce22 Set resolver in virtual manifest
• 3c2fb9c Properly handle mutability for awaited futures (#239)
• 61a7007 We're not interested about msrv for tests
• Additional commits viewable in compare view

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[github-actions]

Regression Detector Results

Run ID: 682ae864-6bb1-41ca-aaf1-f0ddfb49805e
Baseline: d6ae1ae
Comparison: a56da92
Total CPUs: 7

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	datadog_agent_remap_blackhole_acks	ingress throughput	+3.21	[+3.10, +3.32]
➖	datadog_agent_remap_blackhole	ingress throughput	+2.23	[+2.13, +2.32]
➖	syslog_log2metric_splunk_hec_metrics	ingress throughput	+2.08	[+1.91, +2.25]
➖	syslog_regex_logs2metric_ddmetrics	ingress throughput	+1.07	[+0.89, +1.24]
➖	syslog_splunk_hec_logs	ingress throughput	+1.03	[+0.92, +1.14]
➖	syslog_humio_logs	ingress throughput	+0.98	[+0.85, +1.12]
➖	syslog_loki	ingress throughput	+0.92	[+0.85, +0.98]
➖	http_text_to_http_json	ingress throughput	+0.65	[+0.52, +0.78]
➖	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+0.59	[+0.45, +0.73]
➖	splunk_hec_route_s3	ingress throughput	+0.45	[-0.01, +0.92]
➖	datadog_agent_remap_datadog_logs_acks	ingress throughput	+0.32	[+0.24, +0.41]
➖	http_to_http_noack	ingress throughput	+0.22	[+0.13, +0.31]
➖	fluent_elasticsearch	ingress throughput	+0.20	[-0.28, +0.68]
➖	http_to_http_json	ingress throughput	+0.03	[-0.05, +0.10]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	+0.00	[-0.14, +0.15]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	+0.00	[-0.14, +0.14]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	-0.04	[-0.16, +0.07]
➖	enterprise_http_to_http	ingress throughput	-0.07	[-0.13, -0.01]
➖	http_to_s3	ingress throughput	-0.18	[-0.46, +0.10]
➖	file_to_blackhole	egress throughput	-0.19	[-2.67, +2.28]
➖	socket_to_socket_blackhole	ingress throughput	-0.20	[-0.28, -0.12]
➖	http_elasticsearch	ingress throughput	-0.21	[-0.28, -0.13]
➖	otlp_grpc_to_blackhole	ingress throughput	-0.26	[-0.35, -0.17]
➖	datadog_agent_remap_datadog_logs	ingress throughput	-0.35	[-0.48, -0.23]
➖	http_to_http_acks	ingress throughput	-1.00	[-2.34, +0.35]
➖	otlp_http_to_blackhole	ingress throughput	-1.85	[-1.99, -1.72]
➖	syslog_log2metric_humio_metrics	ingress throughput	-3.55	[-3.70, -3.39]

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".