test_loop_properties.py walks the new loop with a seeded mix of operator and Gitea actions (go-aheads, stale go-aheads, answers, comments, merges, the comment-then-merge race, closes, abandon, a crash and restart) and an adaptive scripted model, checking every loop.qnt property after every step. It found two bugs, both fixed with regression tests: abandoning an item left its open PR open (the model's fix 1, now in code), and after a review fix became a follow-up PR, the next fix went to the merged branch. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PPQ14L3LikyefCMFBqEbKE
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Formal models
Quint models of designs where interleavings matter more than any single code path. A model is a hand-written reading of the code: it finds flaws the design and the code share, not places where the code strays from the design. So every counterexample is also reproduced as a failing test against the real code before anything is changed.
orchestrator.qnt: nisse-dev's control loop
Models nisse-dev/src/nisse_dev/control.py: the states, the gate, pending
questions, Gitea comment cursors, publish intents, and the worker queue.
Operator messages, Gitea comments, planner/executor/publisher outcomes
(exceptions included) and a crash at any point all interleave freely.
Each pure function is named after the method it mirrors.
The properties are at the end of the file (all_properties is their
conjunction). Counterexamples are written out as short traces in
orchestrator_scenarios.qnt, and replayed against the real code in
nisse-dev/tests/test_quint_counterexamples.py.
npm install -g @informalsystems/quint # 0.33 or later
# Random simulation, one property at a time:
quint run specs/orchestrator.qnt --invariant=no_stranding \
--max-steps=40 --max-samples=200000
# The counterexample traces (each expects its property to break):
quint test specs/orchestrator_scenarios.qnt
Exhaustive bounded checking (quint verify) uses Apalache and needs Java 17.
Keeping it true. When control.py changes how a state is entered or
left, change the matching function here in the same PR. When a
counterexample's fix lands, flip its scenario's expect to the property
holding, and drop the xfail from its Python reproduction.
loop.qnt: the agent loop, as the architecture describes it
Models the design in docs/Architecture.md rather than code, since the new
loop doesn't exist yet:
- work items from assigned issues and conversations;
- restatements and revision-bound go-aheads;
- park-and-switch, with branches pushed on parking;
- blocked dependencies;
- harness-owned milestones and waiting for merges;
- review follow-ups;
- record issues;
- crashes and build VM wipes at any point.
A counterexample here is a gap in the architecture, so it is fixed there,
and the model carries the fix (marked FIX n). loop_scenarios.qnt keeps each
counterexample as a trace of the fixed behaviour. Each trace fails if its fix
is reverted, and each property that never failed was checked against a
deliberately broken model.
quint run specs/loop.qnt --invariant=all_properties --max-steps=80 --max-samples=200000
quint test specs/loop_scenarios.qnt
Traces need about 80 steps to reach second milestones. The w_* values at the
end are reachability witnesses: each should be violated, which shows the
state it names is reachable.
Against the real code. nisse-dev/tests/test_loop_properties.py checks
the same properties against the new loop itself: a seeded random walk over
what the operator and Gitea can do (go-aheads, answers, comments, merges,
closes, abandon, a crash and restart), checking every property after every
step. It found two bugs the design model couldn't, because they were in the
code: abandon left an open PR, and a review fix after a follow-up PR went to
the merged branch. Each also has its own regression test.
Keeping it true. When the architecture changes a rule this models, change the model and the walk in the same PR.