Titlebook: NASA Formal Methods; 14th International S Jyotirmoy V. Deshmukh,Klaus Havelund,Ivan Perez Conference proceedings 2022 Springer Nature Switz

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書(shū)目名稱(chēng)NASA Formal Methods影響因子(影響力)




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音樂(lè)戲劇

Mucosa

tolerance

The Prusti Project: Formal Verification for?Rustem, which enforces by default that memory is either shared or mutable, but never both. This guarantee is used to prevent common pitfalls such as memory errors and data races. It can also be used to greatly simplify formal verification, as we demonstrated by developing the Prusti verifier, which can

fulmination

Reachability Analysis for?Cyber-Physical Systems: Are We There Yet?n set of unsafe states. Its importance lies in the ability to exhaustively explore the behaviors of a model over a finite or infinite time horizon. The problem of reachability analysis for Cyber-Physical Systems (CPS) is especially challenging because it involves reasoning about the continuous state

專(zhuān)心

Towards Better Test Coverage: Merging Unit Tests for?Autonomous Systemsits operating environment. The question of whether it is possible to design a single test for multiple requirements of the system motivates this work. First, we formally define three attributes of a test: a test specification that characterizes behaviors observed in a test execution, a test environm

停止償付

erythema

Hierarchical Contract-Based Synthesis for?Assurance Casese design space, and an algorithm for the automatic selection of one or more members from the design space that are provably guaranteed to satisfy the overall specification. A key challenge in automatic synthesis is the complexity of the design space. In this paper, we introduce a formal model, terme

RAG

Verified Probabilistic Policies for?Deep Reinforcement Learningre is also growing interest in formally verifying that such policies are correct and execute safely. Progress has been made in this area by building on existing work for verification of deep neural networks and of continuous-state dynamical systems. In this paper, we tackle the problem of verifying

燈泡

NNLander-VeriF: A Neural Network Formal Verification Framework for?Vision-Based Autonomous Aircraft processes images from a camera to guide the aircraft while approaching the runway. A central challenge for the safety and liveness verification of vision-based closed-loop systems is the lack of mathematical models that captures the relation between the system states (e.g., position of the aircraft)