591 citations · 697 across the 15 of their papers we have counts for
11 papers · 1 filter
Event-based Compositional Reasoning of Information-Flow Security for Concurrent Systems
Yongwang Zhao, David Sanan, Fuyuan Zhang +1
High assurance of information-flow security (IFS) for concurrent systems is challenging. A promising way for formal verification of concurrent systems is the rely-guarantee method.…
Mosaic: Model-based Safety Analysis Framework for AI-enabled Cyber-Physical Systems
Xuan Xie, Jiayang Song, Zhehua Zhou +2
Cyber-physical systems (CPSs) are now widely deployed in many industrial domains, e.g., manufacturing systems and autonomous vehicles. To further enhance the capability and applica…
Towards Benchmarking GUI Compatibility Testing on Mobile Applications
Jiaming Ye, Mulong Xie, Siyuan Chen +4
GUI is a bridge connecting user and application. Existing GUI testing tasks can be categorized into two groups: functionality testing and compatibility testing. While the functiona…
DeepGalaxy: Testing Neural Network Verifiers via Two-Dimensional Input Space Exploration
Xuan Xie, Fuyuan Zhang
Deep neural networks (DNNs) are widely developed and applied in many areas, and the quality assurance of DNNs is critical. Neural network verification (NNV) aims to provide formal…
Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing
Muhammad Numair Mansur, Maria Christakis, Valentin Wüstholz +1
Formal methods use SMT solvers extensively for deciding formula satisfiability, for instance, in software verification, systematic test generation, and program synthesis. However,…
An Event-based Compositional Reasoning Approach for Concurrent Reactive Systems
Yongwang Zhao, David Sanan, Fuyuan Zhang +1
Reactive systems are composed of a well defined set of input events that the system reacts with by executing an associated handler to each event. In concurrent environments, event…
Combinatorial Testing for Deep Learning Systems
Lei Ma, Fuyuan Zhang, Minhui Xue +4
Deep learning (DL) has achieved remarkable progress over the past decade and been widely applied to many safety-critical applications. However, the robustness of DL systems recentl…
DeepMutation: Mutation Testing of Deep Learning Systems
Lei Ma, Fuyuan Zhang, Jiyuan Sun +8
Deep learning (DL) defines a new data-driven programming paradigm where the internal system logic is largely shaped by the training data. The standard way of evaluating DL models i…
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Lei Ma, Felix Juefei-Xu, Fuyuan Zhang +9
Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data. We have seen…
High-Assurance Separation Kernels: A Survey on Formal Methods
Yongwang Zhao, David Sanan, Fuyuan Zhang +1
Separation kernels provide temporal/spatial separation and controlled information flow to their hosted applications. They are introduced to decouple the analysis of applications in…
Reasoning About Information Flow Security of Separation Kernels with Channel-based Communication
Yongwang Zhao, David Sann, Fuyuan Zhang +1
Assurance of information flow security by formal methods is mandated in security certification of separation kernels. As an industrial standard for separation kernels, ARINC 653 ha…