Formal Verification
The growing adoption of declarative software specification languages, coupled with their inherent difficulty in debugging, has underscored the need for effective and automated repair techniques applicable to such languages. Researchers have recently explored various methods to automatically repair declarative software specifications, such as template-based repair, feedback-driven iterative repair, and bounded exhaustive approaches. The latest developments in Large Language Models (LLMs) provide new opportunities for the automatic repair of declarative specifications.
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MOM-OnSem (Ontology Semantics for MOM Standards) defines the formal semantics of object models within MOM standards IEC 62264 as a reusable ontology theory using an Event-B-based framework. This formalized and reusable ontology semantics serves as a foundation for designing MOM systems.
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This paper develops a correct-by-design controller for an autonomous vehicle interacting with opponent vehicles with unknown intentions. We define an intention-aware control problem incorporating epistemic uncertainties of the opponent vehicles and model their intentions as discrete-valued random variables. Then, we focus on a control objective specified as belief-space temporal logic specifications. From this stochastic control problem, we derive a sound deterministic control problem using stochastic expansion and solve it using shrinking-horizon model predictive control.
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A fully-labeled C++03 program dataset provides a unique resource to evaluate model checkers in respect to language coverage. To tackle modern aspects of the C++ language, a large-scale benchmark dataset includes more than 1,500 C++03-compliant programs, which cover different aspects of the language, including exception handling, templates, inheritance, polymorphism, the standard template library, and object-oriented design.
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