scholarly journals On Benchmarking for Concurrent Runtime Verification

Author(s):  
Luca Aceto ◽  
Duncan Paul Attard ◽  
Adrian Francalanza ◽  
Anna Ingólfsdóttir

AbstractWe present a synthetic benchmarking framework that targets the systematic evaluation of RV tools for message-based concurrent systems. Our tool can emulate various load profiles via configuration. It provides a multi-faceted view of measurements that is conducive to a comprehensive assessment of the overhead induced by runtime monitoring. The tool is able to generate significant loads to reveal edge case behaviour that may only emerge when the monitoring system is pushed to its limit. We evaluate our framework in two ways. First, we conduct sanity checks to assess the precision of the measurement mechanisms used, the repeatability of the results obtained, and the veracity of the behaviour emulated by our synthetic benchmark. We then showcase the utility of the features offered by our tool in a two-part RV case study.

2020 ◽  
Vol 1 (2) ◽  
pp. 18-33
Author(s):  
Zarina Che Imbi ◽  
Tse-Kian Neo ◽  
Mai Neo

In the era of digital learning, multimedia-based classroom has been commonly used in higher education including Malaysian higher education institutions. A case study has been performed to evaluate web-based learning using Level 1 to 3 of Kirkpatrick's model in a multi-disciplinary course at Multimedia University, Malaysia. In this study, mixed method research was employed in which triangulation was performed from multiple sources of data collection to give deeper understanding. Students perceived that learning with multimedia was enjoyable. They were also motivated in learning and engaged through the use of web module as multimedia was perceived to motivate them and make learning fun. Students showed significant improvements in their knowledge based on the pre-test and post-test results on learning evaluation. Students were perceived to transfer the learning from web-based learning into the learning outcome. The systematic evaluation can provide the feedback that educators and institution as a whole need to improve the learning environment and programme quality. This study contributes to the research field by adding another perspective in evaluations of web-based learning. It also provides empirical evidence on student perspectives, learning and behaviour in a private university. It demonstrated that the Kirkpatrick's model is useful as an evaluation tool to be used in higher education.


2021 ◽  
Vol 43 (1) ◽  
pp. 1-46
Author(s):  
David Sanan ◽  
Yongwang Zhao ◽  
Shang-Wei Lin ◽  
Liu Yang

To make feasible and scalable the verification of large and complex concurrent systems, it is necessary the use of compositional techniques even at the highest abstraction layers. When focusing on the lowest software abstraction layers, such as the implementation or the machine code, the high level of detail of those layers makes the direct verification of properties very difficult and expensive. It is therefore essential to use techniques allowing to simplify the verification on these layers. One technique to tackle this challenge is top-down verification where by means of simulation properties verified on top layers (representing abstract specifications of a system) are propagated down to the lowest layers (that are an implementation of the top layers). There is no need to say that simulation of concurrent systems implies a greater level of complexity, and having compositional techniques to check simulation between layers is also desirable when seeking for both feasibility and scalability of the refinement verification. In this article, we present CSim 2 a (compositional) rely-guarantee-based framework for the top-down verification of complex concurrent systems in the Isabelle/HOL theorem prover. CSim 2 uses CSimpl, a language with a high degree of expressiveness designed for the specification of concurrent programs. Thanks to its expressibility, CSimpl is able to model many of the features found in real world programming languages like exceptions, assertions, and procedures. CSim 2 provides a framework for the verification of rely-guarantee properties to compositionally reason on CSimpl specifications. Focusing on top-down verification, CSim 2 provides a simulation-based framework for the preservation of CSimpl rely-guarantee properties from specifications to implementations. By using the simulation framework, properties proven on the top layers (abstract specifications) are compositionally propagated down to the lowest layers (source or machine code) in each concurrent component of the system. Finally, we show the usability of CSim 2 by running a case study over two CSimpl specifications of an Arinc-653 communication service. In this case study, we prove a complex property on a specification, and we use CSim 2 to preserve the property on lower abstraction layers.


2019 ◽  
Vol 11 (6) ◽  
pp. 1716 ◽  
Author(s):  
Luciano Raso ◽  
Jan Kwakkel ◽  
Jos Timmermans

Climate change raises serious concerns for policymakers that want to ensure the success of long-term policies. To guarantee satisfactory decisions in the face of deep uncertainties, adaptive policy pathways might be used. Adaptive policy pathways are designed to take actions according to how the future will actually unfold. In adaptive pathways, a monitoring system collects the evidence required for activating the next adaptive action. This monitoring system is made of signposts and triggers. Signposts are indicators that track the performance of the pathway. When signposts reach pre-specified trigger values, the next action on the pathway is implemented. The effectiveness of the monitoring system is pivotal to the success of adaptive policy pathways, therefore the decision-makers would like to have sufficient confidence about the future capacity to adapt on time. “On time” means activating the next action on a pathway neither so early that it incurs unnecessary costs, nor so late that it incurs avoidable damages. In this paper, we show how mapping the relations between triggers and the probability of misclassification errors inform the level of confidence that a monitoring system for adaptive policy pathways can provide. Specifically, we present the “trigger-probability” mapping and the “trigger-consequences” mappings. The former mapping displays the interplay between trigger values for a given signpost and the level of confidence regarding whether change occurs and adaptation is needed. The latter mapping displays the interplay between trigger values for a given signpost and the consequences of misclassification errors for both adapting the policy or not. In a case study, we illustrate how these mappings can be used to test the effectiveness of a monitoring system, and how they can be integrated into the process of designing an adaptive policy.


2013 ◽  
Vol 44 (6) ◽  
pp. 1114-1128 ◽  
Author(s):  
M. J. Gunnarsdottir ◽  
S. M. Gardarsson ◽  
H. O. Andradottir

This paper explores the fate and transport of microbial contamination in a cold climate and coarse aquifers. A confirmed norovirus outbreak in a small rural water supply in the late summer of 2004, which is estimated to have infected over 100 people, is used as a case study. A septic system, 80 m upstream of the water intake, is considered to have contaminated drinking water. Water samples tested were negative for coliform and strongly positive for norovirus. Modelling predicts that a 4.8-log10 removal was possible in the 8 m thick vadose zone, while only a 0.7-log10 and 2.7-log10 removal in the aquifer for viruses and Escherichia coli, respectively. The model results support that the 80 m setback distance was inadequate and roughly 900 m aquifer transport distance was needed to achieve 9-log10 viral removal. Sensitivity analysis showed that the most influential parameters on model transport removal rate are grain size diameter and groundwater velocity, temperature and acidity. The results demonstrate a need for systematic evaluation of septic systems in rural areas in lesser studied coarse strata at low temperatures, thereby strengthening data used for regulatory requirements for more confident determination on safe setback distances.


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