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Titlebook: Software Verification; 13th International C Roderick Bloem,Rayna Dimitrova,Natasha Sharygina Conference proceedings 2022 Springer Nature Sw

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书目名称Software Verification
副标题13th International C
编辑Roderick Bloem,Rayna Dimitrova,Natasha Sharygina
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Software Verification; 13th International C Roderick Bloem,Rayna Dimitrova,Natasha Sharygina Conference proceedings 2022 Springer Nature Sw
描述This book constitutes the refereed proceedings of the 13th International Conference on Verified Software, VSTTE 2021, and the 14.th. International Workshop on Numerical Software Verification, NSV 2021, held online, in July/ October 2021. Due to COVID-19 pandemic the conference was held virtually..There were 10 papers presented in this volume were carefully reviewed and selected from 20 submissions...The papers focuses on challenges of the verification of cyber-physical systems with machine learning components and making large-scale verified software a practical reality and much more. .
出版日期Conference proceedings 2022
关键词architecting; architecture verification and validation; artificial intelligence; computer hardware; comp
版次1
doihttps://doi.org/10.1007/978-3-030-95561-8
isbn_softcover978-3-030-95560-1
isbn_ebook978-3-030-95561-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

书目名称Software Verification影响因子(影响力)




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Partial Order Reduction for Timed Actorses (states where the only outgoing transition shows the progress of time). We generate the state space of a case study in the domain of air traffic control systems based on the proposed POR. The results on our benchmarks illustrate that our POR method, on average, reduces the time and memory consump
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Uncertainty-Aware Signal Temporal Logic Inferenced or violated by the interval trajectory. The second approach relies on the first learning algorithm and exploits the decision trees to infer STL formulas to classify behaviors of a given system. The proposed approaches also work for non-separable data by optimizing the . in inferring an STL formula
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Designing and Proving Properties of the Abaco Autoscaler Using TLA+ new design using both the TLC model checker and the TLAPS proof system. We include results of our use of TLC for manually checking safety and liveness properties for some small state spaces, and we provide proofs in TLAPS of all safety properties. To the best of our knowledge, our work is the first
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Case Study: Analysis of Autonomous Center Line Tracking Neural Networksness and safety properties of the model. We show the use of these patterns to identify features of the input that explain correct and incorrect behavior. We also use the patterns to provide guarantees of consistent behavior. We explore a novel idea of using sequences of images (instead of single ima
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