An increasing number of Advanced Persistent Threat (APT) organizations are utilizing DNS (Domain Name System) covert channels to evade network intrusion detection systems and establish private authoritative servers fo...
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In the context of mobile edge computing, achieving dynamic service caching and updating to guarantee the QoS of users and reduce system costs is a challenging problem. However, existing research still has certain defi...
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In the process of data cleaning, there are problems of high difficulty and low efficiency for processing IIS (incomplete information system) that has large size data. As this problem, distributed IMR (DIMR) is a metho...
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In general, energy sources and electronics loads are connected to DC microgrids via power electronic converters. However, interactions of these power converters may introduce instability issues into the system. One ty...
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Out-of-distribution detection is critical to a reliable application of deep neural networks. To reduce model uncertainty, we propose a simple yet effective approach of ensemble knowledge distillation. We blend ensembl...
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With the rapid development of deep learning, the parameters of modern neural network models, especially in the field of Natural Language Processing (NLP) are extremely huge. When the parameters of the model are larger...
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With the growing popularity of Unmanned Aerial Vehicles (UAVs) in civilian, commercial, and military applications, the need for robust drone detection systems has become increasingly urgent. However, due to the small ...
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Autonomous-driving systems require real-time processing for safety. Detecting the deadline miss (disabling to execute the process until the designated time) of autonomous-driving software is essential for executing re...
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In the wake of the post-epidemic era, the gradual standardization of coronavirus detection has given rise to concerns about the efficiency of corona virus self-test result identification. This study primarily employs ...
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Live testing is about testing a subsystem in production without causing any unacceptable disturbance to the production traffic. A subsystem is tested in production for multiple purposes such as deployment verification...
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ISBN:
(纸本)9781665476799
Live testing is about testing a subsystem in production without causing any unacceptable disturbance to the production traffic. A subsystem is tested in production for multiple purposes such as deployment verification, fault prediction, fault localization, etc. The main challenge of live testing is alleviating the risk of test interferences as it may lead to a violation of a system's functional or non-functional requirements. To properly handle this risk, one needs to know which components present a risk of test interferences and what is the cost of the countermeasures to handle that risk. Existing literature relies heavily on human judgement, which can be time consuming, not always feasible, may provide misleading insight. In this paper we go through the challenges of automating this evaluation process and propose a solution to overcome them. Our solution consists of a method for components evaluation which goes through three steps, evaluation oftest interferences that may manifest in external behaviour, evaluation of test interferences that may manifest in resource consumption, and finally the evaluation of the cost of implementing the countermeasures to overcome the risk of test interferences.
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