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This paper presents a novel framework for synthesizing finite-state controllers for Partially Observable Markov Decision Processes (POMDPs) by integrating sampling, automata learning, and model-checking. The approach provides formal guarantees for threshold-safety problems that elude existing formal synthesis tools.
Researchers from the Specula team created SysMoBench, a benchmark evaluating whether LLMs can faithfully model real-world computing systems in TLA+ or merely recite textbook specifications. The benchmark tests 11 systems across four phases and reveals systematic gaps in current LLMs' ability to accurately model system implementations versus reference papers.
TLA+ semantics guarantee nonordered updates, but the TLC model checker breaks these guarantees by requiring ordered assignments and adding effectful operators like PrintT, causing confusion for beginners.
Explains the concept of possibility properties in formal methods, complementing safety and liveness, and discusses their use in specification and model checking.