test(amber): add unit test coverage for FriesReconfigurationAlgorithm

[eugenegujing]

What changes were proposed in this PR?

The new FriesReconfigurationAlgorithmSpec (16 tests) pins the algorithm's observable behaviors through getReconfigurations, with positive and negative assertions:

• scope stays limited to the reconfigured operator when no one-to-many operator is upstream;
• an upstream one-to-many operator with a reconfigured descendant is pulled into the scope together with the connecting path, and becomes the epoch-marker source;
• one-to-many operators with no reconfigured descendant, one-to-many operators downstream of the target, and side branches are all excluded;
• parallel branches between a one-to-many operator and the target are all included (diamond);
• disconnected closures split into separate components with per-component reconfiguration sets and sources, while connected reconfigured operators merge into one component;
• multiple one-to-many operators converging on the target yield a single component with multiple marker sources;
• links are traversed on every input port, not just port 0;
• edge cases: single-operator region, target that is itself a region source, target that is itself one-to-many, multiple executing regions handled independently, and an empty result when no region contains a target.

Fixtures build small regions with PhysicalOp/PhysicalLink wiring (the closure walks per-operator port links) and stub WorkflowExecutionManager.getExecutingRegions, following the patterns of RegionSpec and WorkflowExecutionManagerSpec. No production code is changed.

Any related issues, documentation, discussions?

Closes #7573

How was this PR tested?

This PR is itself test-only. The new spec was run with:

sbt "WorkflowExecutionService/testOnly *FriesReconfigurationAlgorithmSpec"

All 16 tests pass. The suite was additionally mutation-checked: four manual mutations of the algorithm (dropping forward-closure propagation, disabling the connected-component split, disabling the one-to-many pull-in, and returning whole components instead of intersecting with the source set) each caused multiple test failures, and the source was restored afterwards. scalafmtCheck passes.

Was this PR authored or co-authored using generative AI tooling?

Co-authored by: Claude Code (Claude Fable 5)

[github-actions]

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[github-actions]

⚠️ Benchmark changes need a look

🟢 0 better · 🔴 9 worse · ⚪ 6 noise (<±5%) · 0 without baseline

Compared against main e878df3 benchmarked on this same runner, so the delta is largely free of cross-runner hardware noise. The "7d avg" column still reflects the gh-pages dashboard. Treat <±5% as noise unless repeated.

Dashboard · Run

	config	throughput	MB/s	latency	max Δ latest / 7d
🔴	bs=10 sw=10 sl=64	363	0.221	26,002/37,967/37,967 us	🔴 +13.8% / 🔴 +137.4%
🔴	bs=100 sw=10 sl=64	765	0.467	125,860/174,169/174,169 us	🔴 +24.8% / 🔴 +61.2%
⚪	bs=1000 sw=10 sl=64	914	0.558	1,094,344/1,157,512/1,157,512 us	⚪ within ±5% / 🔴 +11.5%

Baseline details

Latest main e878df3 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	363 tuples/sec	404 tuples/sec	784.3 tuples/sec	-10.1%	-53.7%
bs=10 sw=10 sl=64	MB/s	0.221 MB/s	0.247 MB/s	0.479 MB/s	-10.5%	-53.8%
bs=10 sw=10 sl=64	p50	26,002 us	22,844 us	12,590 us	+13.8%	+106.5%
bs=10 sw=10 sl=64	p95	37,967 us	33,720 us	15,991 us	+12.6%	+137.4%
bs=10 sw=10 sl=64	p99	37,967 us	33,720 us	18,694 us	+12.6%	+103.1%
bs=100 sw=10 sl=64	throughput	765 tuples/sec	818 tuples/sec	1,002 tuples/sec	-6.5%	-23.7%
bs=100 sw=10 sl=64	MB/s	0.467 MB/s	0.499 MB/s	0.612 MB/s	-6.4%	-23.6%
bs=100 sw=10 sl=64	p50	125,860 us	120,327 us	101,285 us	+4.6%	+24.3%
bs=100 sw=10 sl=64	p95	174,169 us	139,603 us	108,068 us	+24.8%	+61.2%
bs=100 sw=10 sl=64	p99	174,169 us	139,603 us	118,235 us	+24.8%	+47.3%
bs=1000 sw=10 sl=64	throughput	914 tuples/sec	918 tuples/sec	1,030 tuples/sec	-0.4%	-11.3%
bs=1000 sw=10 sl=64	MB/s	0.558 MB/s	0.56 MB/s	0.629 MB/s	-0.4%	-11.2%
bs=1000 sw=10 sl=64	p50	1,094,344 us	1,087,270 us	991,882 us	+0.7%	+10.3%
bs=1000 sw=10 sl=64	p95	1,157,512 us	1,140,726 us	1,038,496 us	+1.5%	+11.5%
bs=1000 sw=10 sl=64	p99	1,157,512 us	1,140,726 us	1,068,265 us	+1.5%	+8.4%

Raw CSV

config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,551.38,200,128000,363,0.221,26001.67,37966.62,37966.62
1,100,10,64,20,2613.17,2000,1280000,765,0.467,125860.43,174169.09,174169.09
2,1000,10,64,20,21878.04,20000,12800000,914,0.558,1094344.22,1157512.10,1157512.10

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 87.87%. Comparing base (e878df3) to head (b8baf7d).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #7578      +/-   ##
============================================
- Coverage     87.88%   87.87%   -0.02%     
+ Complexity     4276     4271       -5     
============================================
  Files          1176     1176              
  Lines         47018    47018              
  Branches       5245     5245              
============================================
- Hits          41323    41317       -6     
  Misses         3972     3972              
- Partials       1723     1729       +6     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)		Carriedforward from e878df3
agent-service	98.62% <ø> (ø)		Carriedforward from e878df3
amber	82.84% <ø> (-0.04%)	⬇️
computing-unit-managing-service	60.38% <ø> (ø)		Carriedforward from e878df3
config-service	65.97% <ø> (ø)		Carriedforward from e878df3
file-service	69.05% <ø> (ø)		Carriedforward from e878df3
frontend	89.94% <ø> (ø)		Carriedforward from e878df3
notebook-migration-service	78.89% <ø> (ø)		Carriedforward from e878df3
pyamber	97.52% <ø> (ø)		Carriedforward from e878df3
workflow-compiling-service	26.31% <ø> (ø)		Carriedforward from e878df3

*This pull request uses carry forward flags. Click here to find out more.

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[eugenegujing]

/request-review @aglinxinyuan