T3, a Combinator-Based Random Testing Tool for Java: Benchmarking

2014 ◽  
pp. 101-110 ◽  
Author(s):  
I. S. Wishnu B. Prasetya
Keyword(s):  
Random Testing ◽  
Testing Tool

scholarly journals Testing noninterference, quickly

2016 ◽  
Vol 26 ◽  
Author(s):  
CĂTĂLIN HRIŢCU ◽  
LEONIDAS LAMPROPOULOS ◽  
ANTAL SPECTOR-ZABUSKY ◽  
ARTHUR AZEVEDO DE AMORIM ◽  
MAXIME DÉNÈS ◽  
...  
Keyword(s):  
Design Process ◽  
Information Flow ◽  
Random Testing ◽  
Control Mechanisms ◽  
Information Flow Control ◽  
Effective Technique ◽  
Complex Information ◽  
Abstract Machines ◽  
Testing Tool ◽  
Testing Techniques

AbstractInformation-flow control mechanisms are difficult both to design and to prove correct. To reduce the time wasted on doomed proof attempts due to broken definitions, we advocate modern random-testing techniques for finding counterexamples during the design process. We show how to use QuickCheck, a property-based random-testing tool, to guide the design of increasingly complex information-flow abstract machines, leading up to a sophisticated register machine with a novel and highly permissive flow-sensitive dynamic enforcement mechanism that is sound in the presence of first-class public labels. We find that both sophisticated strategies for generating well-distributed random programs and readily falsifiable formulations of noninterference properties are critically important for efficient testing. We propose several approaches and evaluate their effectiveness on a collection of injected bugs of varying subtlety. We also present an effective technique for shrinking large counterexamples to minimal, easily comprehensible ones. Taken together, our best methods enable us to quickly and automatically generate simple counterexamples for more than 45 bugs. Moreover, we show how testing guides the discovery of the sophisticated invariants needed for the noninterference proof of our most complex machine.

Perceived Effectiveness of Random Testing for Alcohol and Drugs in the Australian Aviation Community

2012 ◽  
Vol 2 (2) ◽  
pp. 72-81
Author(s):  
Christina M. Rudin-Brown ◽  
Eve Mitsopoulos-Rubens ◽  
Michael G. Lenné
Keyword(s):  
Logistic Regression ◽  
Online Survey ◽  
Random Testing ◽  
Regression Analyses ◽  
Perceived Effectiveness ◽  
Student Pilots ◽  
Alcohol And Drugs ◽  
Positive Attitudes ◽  
One Year ◽  
Alcohol And Other Drugs

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.

scholarly journals Evaluating the contributions of strategies to prevent SARS-CoV-2 transmission in the healthcare setting: a modelling study

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e044644
Author(s):  
Xueting Qiu ◽  
Joel C Miller ◽  
Derek R MacFadden ◽  
William P Hanage
Keyword(s):  
Healthcare Workers ◽  
Healthcare Setting ◽  
Stochastic Simulations ◽  
Limited Resources ◽  
Base Case ◽  
Protective Equipment ◽  
Random Testing ◽  
Weekly Basis ◽  
Force Of Infection ◽  
Effective Use

IntroductionSince its onset, the COVID-19 pandemic has caused significant morbidity and mortality worldwide, with particularly severe outcomes in healthcare institutions and congregate settings. To mitigate spread, healthcare systems have been cohorting patients to limit contacts between uninfected patients and potentially infected patients or healthcare workers (HCWs). A major challenge in managing the pandemic is the presence of currently asymptomatic/presymptomatic individuals capable of transmitting the virus, who could introduce COVID-19 into uninfected cohorts. The optimal combination of personal protective equipment (PPE), testing and other approaches to prevent these events is unclear, especially in light of ongoing limited resources.MethodsUsing stochastic simulations with a susceptible-exposed-infected-recovered dynamic model, we quantified and compared the impacts of PPE use, patient and HCWs surveillance testing and subcohorting strategies.ResultsIn the base case without testing or PPE, the healthcare system was rapidly overwhelmed, and became a net contributor to the force of infection. We found that effective use of PPE by both HCWs and patients could prevent this scenario, while random testing of apparently asymptomatic/presymptomatic individuals on a weekly basis was less effective. We also found that even imperfect use of PPE could provide substantial protection by decreasing the force of infection. Importantly, we found that creating smaller patient/HCW-interaction subcohorts can provide additional resilience to outbreak development with limited resources.ConclusionThese findings reinforce the importance of ensuring adequate PPE supplies even in the absence of testing and provide support for strict subcohorting regimens to reduce outbreak potential in healthcare institutions.

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