chore(deps): Bump assert_cmd from 2.0.15 to 2.0.16

[dependabot]

Bumps assert_cmd from 2.0.15 to 2.0.16.

Changelog

Sourced from assert_cmd's changelog.

[2.0.16] - 2024-08-09

Features

• Add getters to Command to mirror those added to the standard library

Commits

• bf1025e chore: Release assert_cmd version 2.0.16
• 50e8293 docs: Update changelog
• 6539f0a Merge pull request #213 from mcky/feat-add-command-getters
• b037f96 feat: Add getters to mirror those available on std::process::Command
• 4d3dbd3 chore(deps): Update Rust crate escargot to v0.5.12
• 936e453 Merge pull request #210 from epage/min
• 26a368c chore: Clean up minimal deps hack
• 3229492 chore(deps): Update Rust Stable to v1.80
• 7c63917 Merge pull request #208 from epage/template
• 3dc2b41 fix: Workaround bad minimal-versions
• Additional commits viewable in compare view

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[github-actions]

Regression Detector Results

Run ID: c0ec2598-6dc9-4710-8bf5-4f63e53b6b49 Metrics dashboard

Baseline: 559e069
Comparison: e99ed52

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.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	links
❌	file_to_blackhole	egress throughput	-14.53	[-21.19, -7.88]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	links
➖	syslog_log2metric_splunk_hec_metrics	ingress throughput	+2.24	[+2.11, +2.37]
➖	syslog_splunk_hec_logs	ingress throughput	+1.74	[+1.65, +1.82]
➖	datadog_agent_remap_datadog_logs	ingress throughput	+1.37	[+1.16, +1.58]
➖	datadog_agent_remap_blackhole	ingress throughput	+1.00	[+0.90, +1.11]
➖	otlp_http_to_blackhole	ingress throughput	+0.82	[+0.67, +0.98]
➖	datadog_agent_remap_datadog_logs_acks	ingress throughput	+0.75	[+0.56, +0.94]
➖	fluent_elasticsearch	ingress throughput	+0.72	[+0.23, +1.22]
➖	otlp_grpc_to_blackhole	ingress throughput	+0.33	[+0.20, +0.46]
➖	http_text_to_http_json	ingress throughput	+0.28	[+0.16, +0.41]
➖	syslog_loki	ingress throughput	+0.27	[+0.19, +0.34]
➖	http_to_http_noack	ingress throughput	+0.12	[+0.05, +0.19]
➖	http_to_http_json	ingress throughput	+0.05	[-0.00, +0.10]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	+0.01	[-0.07, +0.09]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	+0.01	[-0.09, +0.10]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	-0.00	[-0.12, +0.12]
➖	http_to_s3	ingress throughput	-0.01	[-0.28, +0.26]
➖	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	-0.06	[-0.19, +0.08]
➖	syslog_humio_logs	ingress throughput	-0.08	[-0.26, +0.11]
➖	syslog_log2metric_humio_metrics	ingress throughput	-0.25	[-0.42, -0.08]
➖	socket_to_socket_blackhole	ingress throughput	-0.63	[-0.73, -0.54]
➖	syslog_regex_logs2metric_ddmetrics	ingress throughput	-0.88	[-1.00, -0.75]
➖	datadog_agent_remap_blackhole_acks	ingress throughput	-0.91	[-1.02, -0.80]
➖	http_to_http_acks	ingress throughput	-1.15	[-2.46, +0.15]
➖	splunk_hec_route_s3	ingress throughput	-1.77	[-2.10, -1.43]
➖	http_elasticsearch	ingress throughput	-2.09	[-2.28, -1.89]
❌	file_to_blackhole	egress throughput	-14.53	[-21.19, -7.88]

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".