fix(ffe): report rejected flags as parse errors

[leoromanovsky]

Motivation

Malformed per-flag UFC configuration is already isolated during ingestion: libdatadog stores a rejection error for that key while compiling valid neighboring flags normally. The FFI translation incorrectly exposed that rejection as a normal DEFAULT result with no error code, hiding a configuration bug from callers.

This implements the contract merged in DataDog/ffe-system-test-data#26: evaluating a rejected key returns the caller default with ERROR / PARSE_ERROR, while valid neighboring flags remain usable.

Changes

• Map FlagConfigurationInvalid to the FFI ERROR reason and PARSE_ERROR error code.
• Add regression coverage proving an invalid regex flag does not poison a valid neighboring flag.
• Bump the canonical fixture submodule to the revision merged in DataDog/ffe-system-test-data#26.
• Update the canonical adapter to expect PARSE_ERROR for rejected keys.
• Compare semantic versions by precedence so build metadata does not change equality or ordering.
• Correct the regex-ingestion documentation to match the parser behavior.

Decisions

• Keep validation in libdatadog so the same Rust regex and UFC parsers used for evaluation own rejection decisions.
• Retain only the per-key rejection error in the compiled configuration, not the malformed flag object.
• Preserve FLAG_NOT_FOUND for keys absent from the configuration.
• Use SemVer precedence comparisons, which ignore build metadata as required by the specification.

Validation

• cargo test -p libdd-ffe
• cargo test -p libdd-ffe-ffi rejected_flag_is_exposed_as_parse_error
• cargo test -p libdd-ffe-test-suite --test canonical_fixtures
• git diff --check

[datadog-official]

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 76.29% (+0.30%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: e735a87 | Docs | Datadog PR Page | Give us feedback!}

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-08-13 04:56:35

Comparing candidate commit e735a87 in PR branch agent/ffe-rejected-flag-errors with baseline commit 3da894a in branch main.

Found 2 performance improvements and 1 performance regressions! Performance is the same for 11 metrics, 0 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

scenario:flagevaluation_evp/payloads/stress/10flags_1000users_250fields

• 🟩 execution_time [-4.883ms; -4.684ms] or [-4.766%; -4.572%]
• 🟩 throughput [+468.319op/s; +487.669op/s] or [+4.798%; +4.996%]

scenario:sdk_test_data/rules-based

• 🟥 execution_time [+14.228µs; +16.374µs] or [+11.046%; +12.713%]

Candidate

Candidate benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e735a87	1786596267	agent/ffe-rejected-flag-errors

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
single_flag_killswitch/rules-based	execution_time	155.685ns	159.185ns ± 2.457ns	158.931ns ± 1.789ns	160.645ns	163.973ns	166.051ns	170.661ns	7.38%	1.045	1.758	1.54%	0.174ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
single_flag_killswitch/rules-based	execution_time	[158.845ns; 159.526ns] or [-0.214%; +0.214%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e735a87	1786596267	agent/ffe-rejected-flag-errors

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	execution_time	21.371ms	21.436ms ± 0.029ms	21.432ms ± 0.015ms	21.451ms	21.481ms	21.532ms	21.563ms	0.61%	1.119	3.315	0.13%	0.002ms	1	200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	115941.421op/s	116627.940op/s ± 155.172op/s	116649.587op/s ± 81.250op/s	116712.373op/s	116852.967op/s	116961.294op/s	116979.037op/s	0.28%	-1.103	3.257	0.13%	10.972op/s	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	96.826ms	97.666ms ± 0.467ms	97.681ms ± 0.171ms	97.829ms	98.227ms	98.867ms	102.163ms	4.59%	4.570	41.629	0.48%	0.033ms	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	9788.271op/s	10239.180op/s ± 47.953op/s	10237.431op/s ± 17.884op/s	10260.803op/s	10300.916op/s	10311.751op/s	10327.837op/s	0.88%	-4.256	37.783	0.47%	3.391op/s	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	590.546µs	592.398µs ± 0.608µs	592.450µs ± 0.391µs	592.798µs	593.336µs	593.653µs	594.628µs	0.37%	-0.005	0.415	0.10%	0.043µs	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	168172.478op/s	168805.471op/s ± 173.310op/s	168790.608op/s ± 111.328op/s	168922.333op/s	169093.619op/s	169195.365op/s	169334.696op/s	0.32%	0.013	0.410	0.10%	12.255op/s	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	execution_time	[21.432ms; 21.440ms] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	[116606.434op/s; 116649.445op/s] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	[97.602ms; 97.731ms] or [-0.066%; +0.066%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	[10232.534op/s; 10245.826op/s] or [-0.065%; +0.065%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	[592.314µs; 592.483µs] or [-0.014%; +0.014%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	[168781.452op/s; 168829.490op/s] or [-0.014%; +0.014%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e735a87	1786596267	agent/ffe-rejected-flag-errors

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	execution_time	5.350ms	5.370ms ± 0.023ms	5.369ms ± 0.005ms	5.373ms	5.381ms	5.390ms	5.682ms	5.84%	11.933	156.536	0.43%	0.002ms	1	200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	439981.274op/s	465540.308op/s ± 1928.887op/s	465669.223op/s ± 407.120op/s	466123.904op/s	466576.105op/s	466984.114op/s	467265.636op/s	0.34%	-11.720	152.748	0.41%	136.393op/s	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	7.972ms	7.988ms ± 0.010ms	7.986ms ± 0.004ms	7.990ms	8.005ms	8.032ms	8.038ms	0.66%	2.554	8.965	0.12%	0.001ms	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	124403.408op/s	125193.863op/s ± 155.118op/s	125218.404op/s ± 60.392op/s	125273.625op/s	125358.449op/s	125420.460op/s	125434.086op/s	0.17%	-2.538	8.871	0.12%	10.969op/s	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	180.505µs	182.352µs ± 0.437µs	182.304µs ± 0.175µs	182.500µs	183.032µs	183.580µs	184.928µs	1.44%	1.253	8.806	0.24%	0.031µs	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	540752.457op/s	548392.977op/s ± 1309.074op/s	548534.362op/s ± 528.286op/s	549035.232op/s	549752.944op/s	551777.032op/s	554002.425op/s	1.00%	-1.187	8.600	0.24%	92.566op/s	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	execution_time	[5.367ms; 5.373ms] or [-0.060%; +0.060%]	None	None	None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	[465272.983op/s; 465807.633op/s] or [-0.057%; +0.057%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	[7.986ms; 7.989ms] or [-0.017%; +0.017%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	[125172.365op/s; 125215.361op/s] or [-0.017%; +0.017%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	[182.292µs; 182.413µs] or [-0.033%; +0.033%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	[548211.552op/s; 548574.402op/s] or [-0.033%; +0.033%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e735a87	1786596267	agent/ffe-rejected-flag-errors

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
sdk_test_data/rules-based	execution_time	140.655µs	144.103µs ± 5.621µs	142.961µs ± 0.672µs	143.774µs	148.678µs	165.613µs	203.120µs	42.08%	7.406	66.242	3.89%	0.397µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sdk_test_data/rules-based	execution_time	[143.324µs; 144.882µs] or [-0.541%; +0.541%]	None	None	None

Baseline

Baseline benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	3da894a	1786558862	main

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
single_flag_killswitch/rules-based	execution_time	158.337ns	161.973ns ± 2.739ns	161.678ns ± 1.805ns	163.434ns	166.870ns	171.205ns	172.402ns	6.63%	1.188	1.613	1.69%	0.194ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
single_flag_killswitch/rules-based	execution_time	[161.593ns; 162.353ns] or [-0.234%; +0.234%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	3da894a	1786558862	main

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	execution_time	22.184ms	22.250ms ± 0.028ms	22.255ms ± 0.018ms	22.269ms	22.289ms	22.311ms	22.330ms	0.34%	-0.307	-0.170	0.13%	0.002ms	1	200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	111954.592op/s	112359.613op/s ± 141.727op/s	112336.057op/s ± 88.909op/s	112449.939op/s	112611.837op/s	112688.016op/s	112695.970op/s	0.32%	0.313	-0.171	0.13%	10.022op/s	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	101.694ms	102.449ms ± 0.545ms	102.354ms ± 0.278ms	102.763ms	103.069ms	103.416ms	107.769ms	5.29%	4.761	43.259	0.53%	0.039ms	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	9279.106op/s	9761.186op/s ± 50.733op/s	9769.976op/s ± 26.568op/s	9794.980op/s	9812.673op/s	9827.011op/s	9833.439op/s	0.65%	-4.416	38.793	0.52%	3.587op/s	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	600.628µs	602.025µs ± 0.639µs	601.990µs ± 0.445µs	602.434µs	603.152µs	603.431µs	604.179µs	0.36%	0.301	-0.009	0.11%	0.045µs	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	165513.729op/s	166106.348op/s ± 176.282op/s	166115.750op/s ± 122.799op/s	166238.478op/s	166376.225op/s	166465.465op/s	166492.520op/s	0.23%	-0.295	-0.016	0.11%	12.465op/s	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	execution_time	[22.246ms; 22.254ms] or [-0.017%; +0.017%]	None	None	None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	[112339.971op/s; 112379.255op/s] or [-0.017%; +0.017%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	[102.374ms; 102.525ms] or [-0.074%; +0.074%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	[9754.154op/s; 9768.217op/s] or [-0.072%; +0.072%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	[601.936µs; 602.113µs] or [-0.015%; +0.015%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	[166081.917op/s; 166130.779op/s] or [-0.015%; +0.015%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	3da894a	1786558862	main

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	execution_time	5.417ms	5.436ms ± 0.028ms	5.434ms ± 0.004ms	5.438ms	5.446ms	5.466ms	5.809ms	6.90%	12.303	162.642	0.51%	0.002ms	1	200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	430341.559op/s	459876.975op/s ± 2207.817op/s	460024.408op/s ± 355.101op/s	460406.354op/s	461001.226op/s	461382.395op/s	461529.146op/s	0.33%	-12.098	158.873	0.48%	156.116op/s	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	7.925ms	7.957ms ± 0.010ms	7.956ms ± 0.005ms	7.962ms	7.971ms	7.983ms	7.997ms	0.52%	-0.089	2.127	0.13%	0.001ms	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	125042.264op/s	125680.560op/s ± 161.323op/s	125691.479op/s ± 72.625op/s	125757.544op/s	125930.294op/s	126133.488op/s	126176.469op/s	0.39%	0.104	2.119	0.13%	11.407op/s	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	181.480µs	187.364µs ± 51.443µs	183.653µs ± 0.151µs	183.884µs	184.507µs	185.267µs	911.212µs	396.16%	14.034	194.974	27.39%	3.638µs	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	109744.006op/s	542116.911op/s ± 30756.674op/s	544503.825op/s ± 448.666op/s	544853.511op/s	545446.379op/s	550048.311op/s	551026.424op/s	1.20%	-13.995	194.243	5.66%	2174.825op/s	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	execution_time	[5.433ms; 5.440ms] or [-0.071%; +0.071%]	None	None	None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	[459570.993op/s; 460182.957op/s] or [-0.067%; +0.067%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	[7.955ms; 7.958ms] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	[125658.202op/s; 125702.918op/s] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	[180.235µs; 194.494µs] or [-3.805%; +3.805%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	[537854.331op/s; 546379.490op/s] or [-0.786%; +0.786%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	3da894a	1786558862	main

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
sdk_test_data/rules-based	execution_time	125.519µs	128.802µs ± 5.327µs	127.757µs ± 0.719µs	128.703µs	132.930µs	149.882µs	186.722µs	46.15%	7.788	73.729	4.13%	0.377µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sdk_test_data/rules-based	execution_time	[128.064µs; 129.540µs] or [-0.573%; +0.573%]	None	None	None

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.20 MB	8.20 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	89.19 MB	89.18 MB	-0% (-7.32 KB) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	100.36 MB	100.35 MB	-0% (-7.37 KB) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.06 MB	11.06 MB	-0% (-152 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	26.63 MB	26.62 MB	--.01% (-4.00 KB) 💪
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	94.56 KB	94.56 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	191.42 MB	191.39 MB	--.01% (-32.00 KB) 💪
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	1001.43 MB	1001.42 MB	-0% (-8.96 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.71 MB	8.71 MB	--.01% (-1.00 KB) 💪
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	94.56 KB	94.56 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	25.62 MB	25.62 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	51.01 MB	51.01 MB	-0% (-3.59 KB) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.22 MB	23.21 MB	--.01% (-3.50 KB) 💪
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	96.04 KB	96.04 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	196.33 MB	196.32 MB	-0% (-8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	990.81 MB	990.80 MB	-0% (-8.92 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.73 MB	6.73 MB	--.01% (-1.00 KB) 💪
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	96.04 KB	96.04 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	27.55 MB	27.55 MB	--.02% (-8.00 KB) 💪
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	48.55 MB	48.55 MB	-0% (-3.65 KB) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	79.46 MB	79.45 MB	--.01% (-9.23 KB) 💪
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	9.12 MB	9.12 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	95.12 MB	95.11 MB	-0% (-9.20 KB) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.14 MB	11.14 MB	-0% (-96 B) 👌

[Copilot]

Pull request overview

This PR updates libdd-ffe’s Rust and FFI error semantics so that per-flag ingestion rejections (e.g., invalid regex) are surfaced to callers as parse errors, while leaving neighboring valid flags evaluatable. It also aligns SemVer comparisons with SemVer precedence rules (ignoring build metadata) and updates tests and canonical fixtures to match the revised contract.

Changes:

• Map FlagConfigurationInvalid to FFI Reason::Error with ErrorCode::ParseError (and update canonical fixtures accordingly).
• Add regression tests ensuring a rejected/invalid flag does not invalidate evaluation of a valid neighboring flag.
• Compare semantic versions by precedence (cmp_precedence) so build metadata does not affect comparisons; add coverage for +build variants.

Reviewed changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
libdd-ffe/src/rules_based/ufc/models.rs	Updates ingestion/evaluation comment to reflect regex compilation during ingestion (reject flag on compile failure).
libdd-ffe/src/rules_based/eval/eval_rules.rs	Switches SemVer equality/ordering to precedence comparison and adds tests for build metadata behavior.
libdd-ffe/src/rules_based/eval/eval_assignment.rs	Adds regression test proving an invalid flag does not poison a valid neighboring flag.
libdd-ffe/src/rules_based/error.rs	Clarifies FlagConfigurationInvalid contract: treat as per-flag parse error without invalidating the rest of the config.
libdd-ffe-test-suite/tests/canonical_fixtures.rs	Updates canonical adapter mappings so FlagConfigurationInvalid is treated as ERROR with PARSE_ERROR.
libdd-ffe-ffi/src/assignment.rs	Fixes FFI mapping: FlagConfigurationInvalid now yields ParseError, and adds a regression unit test.

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[sameerank]

I feel like this comment could also be updated with something like "Failures encountered while compiling an individual flag are converted to FlagConfigurationInvalid at the per-flag ingestion boundary."

[leoromanovsky]

Yea good call