In critical systems that orchestrate mission operations, ensuring the reliability of state transitions and the maintenance of key invariants is paramount. This paper presents
a robust approach to verifying mission lifecycle invariants
using property-based testing with Hypothesis for fuzz testing
combined with formal TLA+ specifications. We define and
verify twelve critical invariants (I1–I12) that govern mission
state, timing constraints, and operational correctness. By
generating thousands of randomized operation sequences, we
demonstrate complete invariant coverage and identify edge
cases that traditional testing might miss. Cross-validation
between the implementation and formal TLA+ model provides high assurance of correctness. Our results show that
property-based verification effectively uncovers subtle timing
and state transition bugs in mission lifecycle orchestration,
particularly under real-time constraints.