From 582cf99c8bd77f7be4e0cac855330ee911b49546 Mon Sep 17 00:00:00 2001
From: agent-14fd4b738639d573 <agent-14fd4b738639d573@gridmolt.local>
Date: Fri, 24 Apr 2026 19:40:43 +0200
Subject: [PATCH] build(agent): melter#14fd4b iteration

---
 crossvenue_arbx/fuzz.py  | 66 ++++++++++++++++++++++++++++++++++++++++
 tests/test_delta_fuzz.py | 33 ++++++++++++++++++++
 2 files changed, 99 insertions(+)
 create mode 100644 crossvenue_arbx/fuzz.py
 create mode 100644 tests/test_delta_fuzz.py

diff --git a/crossvenue_arbx/fuzz.py b/crossvenue_arbx/fuzz.py
new file mode 100644
index 0000000..0d770bd
--- /dev/null
+++ b/crossvenue_arbx/fuzz.py
@@ -0,0 +1,66 @@
+from __future__ import annotations
+
+import random
+from typing import Iterable, List, Tuple
+
+from .core import LocalArbProblem, SharedSignals
+from .coordinator import CentralCoordinator
+
+
+class ScenarioGenerator:
+    """Deterministic scenario generator for delta-fuzzing.
+
+    Produces a replayable sequence of (LocalArbProblem, SharedSignals) that can
+    be fed into CentralCoordinator.ingest_local. Uses an explicit seed to make
+    runs deterministic.
+    """
+
+    def __init__(self, seed: int = 0) -> None:
+        self._seed = seed
+
+    def generate(self, steps: int = 10) -> List[Tuple[LocalArbProblem, SharedSignals]]:
+        rnd = random.Random(self._seed)
+        venues = ["VenueA", "VenueB"]
+        assets = ["AAA", "BBB"]
+        out: List[Tuple[LocalArbProblem, SharedSignals]] = []
+        for i in range(steps):
+            venue = venues[rnd.randrange(len(venues))]
+            problem = LocalArbProblem(
+                id=f"prob-{venue}-{i}",
+                venue=venue,
+                assets=list(assets),
+                target_misprice=rnd.uniform(0.0, 0.01),
+                max_exposure=rnd.choice([100.0, 1000.0, 10000.0]),
+                latency_budget=rnd.uniform(0.01, 1.0),
+            )
+            # deterministic but varied price deltas and liquidity
+            price_deltas = {a: rnd.uniform(-0.005, 0.005) for a in assets}
+            # occasionally inject a shock
+            if rnd.random() < 0.15:
+                shock_asset = rnd.choice(assets)
+                price_deltas[shock_asset] = rnd.choice([-1.0, 1.0]) * rnd.uniform(0.001, 0.02)
+            signals = SharedSignals(
+                version=i,
+                price_delta_by_asset=price_deltas,
+                cross_corr={("AAA","BBB"): rnd.uniform(-1.0,1.0)},
+                liquidity_estimates={a: rnd.uniform(10.0, 10000.0) for a in assets},
+            )
+            out.append((problem, signals))
+        return out
+
+
+class ReplayRunner:
+    """Runs a generated scenario through a fresh CentralCoordinator and
+    returns the replay log (list of PlanDelta signatures) and the final plan
+    signature.
+    """
+
+    def __init__(self) -> None:
+        self.coordinator = CentralCoordinator()
+
+    def run(self, events: Iterable[Tuple[LocalArbProblem, SharedSignals]]):
+        for problem, sig in events:
+            self.coordinator.ingest_local(problem, sig)
+        # call reconcile to flush pending actions
+        self.coordinator.reconcile()
+        return list(self.coordinator.replay_log), (self.coordinator.last_plan.signature if self.coordinator.last_plan else None)
diff --git a/tests/test_delta_fuzz.py b/tests/test_delta_fuzz.py
new file mode 100644
index 0000000..fb80e23
--- /dev/null
+++ b/tests/test_delta_fuzz.py
@@ -0,0 +1,33 @@
+from crossvenue_arbx.fuzz import ScenarioGenerator, ReplayRunner
+
+
+def test_replay_determinism_same_seed():
+    gen = ScenarioGenerator(seed=42)
+    events = gen.generate(steps=20)
+
+    runner1 = ReplayRunner()
+    log1, final1 = runner1.run(events)
+
+    runner2 = ReplayRunner()
+    # regenerate to ensure fresh objects but same seed
+    gen2 = ScenarioGenerator(seed=42)
+    events2 = gen2.generate(steps=20)
+    log2, final2 = runner2.run(events2)
+
+    assert log1 == log2, "Replay logs must be identical for same seed"
+    assert final1 == final2, "Final plan signature must match for same seed"
+
+
+def test_replay_variation_different_seed():
+    gen = ScenarioGenerator(seed=1)
+    events = gen.generate(steps=20)
+    runner = ReplayRunner()
+    log1, final1 = runner.run(events)
+
+    genb = ScenarioGenerator(seed=2)
+    eventsb = genb.generate(steps=20)
+    runnerb = ReplayRunner()
+    log2, final2 = runnerb.run(eventsb)
+
+    # usually different seeds will produce different logs or final plan
+    assert (log1 != log2) or (final1 != final2)