Abstract Mission-time Linear Temporal Logic (MLTL), a widely used subset of popular specification logics like STL and MTL, is often used to model and verify real world systems in safety-critical contexts. As the results of formal verification are only as trustworthy as their input specifications, the WEST tool was created to facilitate writing MLTL specifications. Accordingly, it is vital to demonstrate that WEST itself works correctly. To that end, we verify the WEST algorithm, which converts MLTL formulas to (logically equivalent) regular expressions, in the theorem prover Isabelle/HOL. Our top-level result establishes the correctness of the regular expression transformation; we then generate a code export from our verified development and use this to experimentally validate the existing WEST tool. To facilitate this, we develop some verified support for checking the equivalence of two regular expressions.

Black-box context-free grammar inference is a hard problem as in many practical settings it only has access to a limited number of example programs. The state-of-the-art approach Arvada heuristically generalizes grammar rules starting from flat parse trees and is non-deterministic to explore different generalization sequences. We observe that many of Arvada's generalization steps violate common language concept nesting rules. We thus propose to pre-structure input programs along these nesting rules, apply learnt rules recursively, and make black-box context-free grammar inference deterministic. The resulting TreeVada yielded faster runtime and higher-quality grammars in an empirical comparison. The TreeVada source code, scripts, evaluation parameters, and training data are open-source and publicly available (https://doi.org/10.6084/m9.figshare.23907738).