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Titlebook: Numerical Software Verification; 12th International W Majid Zamani,Damien Zufferey Conference proceedings 2019 Springer Nature Switzerland

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發(fā)表于 2025-3-23 11:36:58 | 只看該作者
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發(fā)表于 2025-3-23 16:26:13 | 只看該作者
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發(fā)表于 2025-3-23 19:23:55 | 只看該作者
An Evaluation of Monte-Carlo Tree Search for Property Falsification on Hybrid Flight Control Lawslo Tree Search property falsification algorithm, applied to select properties of a longitudinal hybrid flight control law: a threshold overshoot property, two frequential properties, and a discrete event-based property.
14#
發(fā)表于 2025-3-23 23:16:14 | 只看該作者
0302-9743 7 workshop is dedicated to the development of logical and mathematical techniques for the reasoning about programmability and reliability..978-3-030-28422-0978-3-030-28423-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
15#
發(fā)表于 2025-3-24 03:48:40 | 只看該作者
0302-9743 y, NY, USA, in July 2019 - colocated with the International Conference on Computer Aided Verification, CAV 2019...The 5 full papers presented together with 2 short papers, 3 abstracts of invited talks, and 2 tutorial papers were carefully reviewed and selected from numerous submissions...The NSV 201
16#
發(fā)表于 2025-3-24 08:29:33 | 只看該作者
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發(fā)表于 2025-3-24 12:05:55 | 只看該作者
Mutant Accuracy Testing for Assessing the Implementation of Numerical Algorithms degraded accuracy. We test the idea on . implementations of some basic numerical algorithms, and find that most mutants are worse while the few which are better show a distinctive pattern of mutation.
18#
發(fā)表于 2025-3-24 18:13:59 | 只看該作者
Conference proceedings 2019, in July 2019 - colocated with the International Conference on Computer Aided Verification, CAV 2019...The 5 full papers presented together with 2 short papers, 3 abstracts of invited talks, and 2 tutorial papers were carefully reviewed and selected from numerous submissions...The NSV 2017 workshop
19#
發(fā)表于 2025-3-24 20:01:29 | 只看該作者
20#
發(fā)表于 2025-3-24 23:40:22 | 只看該作者
Trust, Resilience and Interpretability of AI Modelstomated reasoning with connectionist learning methods that use deep neural networks. The increasing adoption of artificial intelligence and machine learning in systems, including safety-critical systems, has created a pressing need for developing scalable techniques that can be used to establish tru
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