Related papers: Sensor Placement for Online Fault Diagnosis
Answer Set Programming (ASP) is a truly-declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming, that has been recently employed in many applications. The development of efficient ASP systems…
Nowadays, sensors play a major role in several contexts like science, industry and daily life which benefit of their use. However, the retrieved information must be reliable. Anomalies in the behavior of sensors can give rise to critical…
Intensive testing using model-based approaches is the standard way of demonstrating the correctness of automotive software. Unfortunately, state-of-the-art techniques leave a crucial and labor intensive task to the test engineer:…
Context: As Industrial Cyber-Physical Systems (ICPS) become more connected and widely-distributed, often operating in safety-critical environments, we require innovative approaches to detect and diagnose the faults that occur in them.…
We are experiencing an explosion in the amount of sensors measuring our activities and the world around us. These sensors are spread throughout the built environment and can help us perform state estimation and control of related systems,…
Properly benchmarking Automated Program Repair (APR) systems should contribute to the development and adoption of the research outputs by practitioners. To that end, the research community must ensure that it reaches significant milestones…
Vehicle platooning has been a promising solution for improving traffic efficiency and throughput. However, a failure in a single vehicle, including communication loss with neighboring vehicles, can significantly disrupt platoon performance…
Fault localization is an imperative method in fault tolerance in a distributed environment that designs a blueprint for continuing the ongoing process even when one or many modules are non-functional. Visualizing a distributed environment…
This paper introduces an algorithm able to detect and localize the occurrance of a fault in an Active Distribution Network, using the measurements collected by Phasor Measurement Units (PMUs). First, a basic algorithm that works under the…
Identifying the cause of a system-level failure in a cyber-physical system (CPS) can be like tracing a needle in a haystack. This paper approaches the problem by assuming that the CPS has been designed compositionally and that each…
Reliable systems require effective monitoring techniques for fault identification. System-level diagnosis was originally proposed in the 1960s as a test-based approach to monitor and identify faulty components of a general system. Over the…
Optimal sensor placement (OSP) is critical for efficient, accurate monitoring, control, and inference in complex physical systems. We propose a machine-learning-based feature attribution (FA) framework to identify OSP for target…
We introduce an approach to detecting inconsistencies in large biological networks by using Answer Set Programming (ASP). To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and…
Debugging is one of the most time-consuming and expensive tasks in software development. Several formula-based fault localization (FBFL) methods have been proposed, but they fail to guarantee a set of diagnoses across all failing tests or…
Components of electrical power systems are susceptible to failures caused by lightning strikes, aging or human errors. These faults can cause equipment damage, affect system reliability, and results in expensive repair costs. As electric…
Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it…
Product configuration is a successful application of Answer Set Programming (ASP). However, challenges are still open for interactive systems to effectively guide users through the configuration process. The aim of our work is to provide an…
Accurate sensor placement is critical for modeling spatio-temporal systems such as environmental and climate processes. Neural Processes (NPs), particularly Convolutional Conditional Neural Processes (ConvCNPs), provide scalable…
Deep Neural Networks (DNNs) are used in a wide variety of applications. However, as in any software application, DNN-based apps are afflicted with bugs. Previous work observed that DNN bug fix patterns are different from traditional bug fix…
Large-scale decentralized systems of autonomous agents interacting via asynchronous communication often experience the following self-healing dilemma: fault detection inherits network uncertainties making a remote faulty process…