相关论文: Data-driven Mutation Analysis for Cyber-Physical S…

Both the level of conservativeness and the computational burden in robust optimization are critically influenced by uncertainty set design. However, contextual side information is rarely exploited in robust dispatch of power systems…

This paper presents the cyber-physcial model of a computer-mediated control system that is a seamless, fully synergistic integration of the physical system and the cyber system, which provides a systematic framework for synthesis of…

Deep neural network (DNN) mutation analysis is a promising approach to evaluating test set adequacy. Due to the large number of generated mutants that must be tested on large datasets, mutation analysis is costly. In this paper, we present…

Software verification may yield spurious failures when environment assumptions are not accounted for. Environment assumptions are the expectations that a system or a component makes about its operational environment and are often specified…

In the field of mutation analysis, mutation is the systematic generation of mutated programs (i.e., mutants) from an original program. The concept of mutation has been widely applied to various testing problems, including test set…

Cyber-Physical Systems (CPSs), such as Unmanned Aerial Vehicles (UAVs), use System-on-Chip (SoC) based computing platforms to perform multiple complex tasks in safety-critical applications that require a highly dependable operation. Due to…

In chemical and manufacturing processes, unit failures due to equipment degradation can lead to process downtime and significant costs. In this context, finding an optimal maintenance strategy to ensure good unit health while avoiding…

Real-world Cyber-Physical Systems (CPSs) are usually configurable. Through parameters, it is possible to configure, select or unselect different system functionalities. While this provides high flexibility, it also becomes a source for…

For a class of Cyber-Physical Systems (CPSs), we address the problem of performing computations over the cloud without revealing private information about the structure and operation of the system. We model CPSs as a collection of…

In this paper, we propose conformal inference based approach for statistical verification of CPS models. Cyber-physical systems (CPS) such as autonomous vehicles, avionic systems, and medical devices operate in highly uncertain…

Cyber-Physical Systems (CPS) are formed through interconnected components capable of computation, communication, sensing and changing the physical world. The development of these systems poses a significant challenge since they have to be…

Concerns for the resilience of Cyber-Physical Systems (CPS)s in critical infrastructure are growing. CPS integrate sensing, computation, control, and networking into physical objects and mission-critical services, connecting traditional…

In Cyber-Physical Systems (CPS) research, anomaly detection (detecting abnormal behavior) and diagnosis (identifying the underlying root cause) are often treated as distinct, isolated tasks. However, diagnosis algorithms require symptoms,…

Recent advancements in technology have led to the emergence of Cyber-Physical Systems (CPS), which seamlessly integrate the cyber and physical domains in various sectors such as agriculture, autonomous systems, and healthcare. This…

Background. Many mutation reduction strategies, which aim to reduce the number of mutants, have been proposed. Problem. It is important to measure the ability of a mutation reduction strategy to maintain test suite effectiveness evaluation.…

Deep learning (DL) models have seen increased attention for time series forecasting, yet the application on cyber-physical systems (CPS) is hindered by the lacking robustness of these methods. Thus, this study evaluates the robustness and…

Ensuring correctness of timed behaviors in cyber-physical systems (CPS) using closed-loop verification is challenging due to the hybrid dynamics in both systems and environments. Simulink and Stateflow are tools for model-based design that…

Researchers often have datasets measuring features $x_{ij}$ of samples, such as test scores of students. In factor analysis and PCA, these features are thought to be influenced by unobserved factors, such as skills. Can we determine how…

In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not…

Cyber-physical space systems are engineered systems operating within physical space with design requirements that depend on space, e.g., regarding location or movement behavior. They are built from and depend upon the seamless integration…