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Improving the accuracy of oracle verdicts through automated model steering
2014
Proceedings of the 29th ACM/IEEE international conference on Automated software engineering - ASE '14
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We propose an automated steering framework that can adjust the behavior of the model to better match the behavior of the SUT to reduce the rate of false positives. ...
The oracle-a judge of the correctness of the system under test (SUT)-is a major component of the testing process. ...
Case study results indicate that steering improves the accuracy of the final oracle verdicts-outperforming both default testing practice and step-wise filtering. ...
doi:10.1145/2642937.2642989
dblp:conf/kbse/GayRH14
fatcat:x5nfzss6i5e7lf53qhdiqfnrii
Steering model-based oracles to admit real program behaviors
2014
Companion Proceedings of the 36th International Conference on Software Engineering - ICSE Companion 2014
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We therefore propose steering the model when used as an oracle, to admit an expanded set of behaviors when judging the SUT's adherence to its requirements. ...
Behavioral models of such systems, often built for analysis and simulation, are appealing for reuse as oracles. However, these models typically provide an idealized view of the system. ...
We also calculate the F-measure-the harmonic mean of precision and recall-in order to judge the accuracy of oracle verdicts. ...
doi:10.1145/2591062.2591120
dblp:conf/icse/GayRH14
fatcat:f5adamdcyncalahwdz756j465q
Automated Steering of Model-Based Test Oracles to Admit Real Program Behaviors
2017
IEEE Transactions on Software Engineering
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Improving the Accuracy of Oracle Verdicts through Automated Model Steering. In Proceedings of the 29th ACM/IEEE international conference on Automated software engineering (ASE '14). ...
Automated Steering of Model-Based Test Oracles to Admit Real Program Behaviors. ...
Obtaining the Source Code and Models In the interest of allowing others to extend, reproduce, or otherwise make use of the work that we have conducted, the current version of our steering framework and ...
doi:10.1109/tse.2016.2615311
fatcat:iholcljqenbcnjs3lklzdpg6aq
Test oracles for simulink-like models
2016
Automated Software Engineering : An International Journal
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steering. ...
automated oracle generator for Simulink models. ...
Angle of attack The angle between the chord line of the wing of an aircraft and the vector representing the relative motion between the aircraft and the atmosphere. ...
doi:10.1007/s10515-016-0207-9
fatcat:d436nlhag5hpxmplx4m344fuz4
Oracles for Testing Software Timeliness with Uncertainty
2018
ACM Transactions on Software Engineering and Methodology
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To address the above challenge, we propose STUIOS (Stochastic Testing with Unique Input Output Sequences), an approach for the automated generation of stochastic oracles that verify the capability of a ...
Such stochastic oracles entail the statistical analysis of repeated test case executions based on test output probabilities predicted by means of statistical model checking. ...
For example, the accuracy of HOD might be altered by overheating caused by a malfunctioning steering wheel heater. ...
doi:10.1145/3280987
fatcat:jxnaeihilbeezaahq7jtl3uete
Learning-Based Testing of Cyber-Physical Systems-of-Systems: A Platooning Study
[chapter]
2017
Lecture Notes in Computer Science
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We consider the challenges faced, and some initial results obtained in an effort to scale up LBT to testing co-operative open cyber-physical systems-of-systems (CO-CPS). ...
Learning-based testing (LBT) is a paradigm for fully automated requirements testing that combines machine learning with modelchecking techniques. ...
So, a judicious choice of model accuracy, combinatorial test strategy and model abstraction can all be applied to improve the efficiency of learning and testing. ...
doi:10.1007/978-3-319-66583-2_9
fatcat:4yxfzw2vnnfvhokvlxumd4lh44
A mapping study on testing non-testable systems
2017
Software quality journal
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The prevalence of the oracle problem has inspired the research community to develop several automated testing techniques that can detect functional software faults in such programs. ...
The terms "Oracle Problem" and "Non-testable system" interchangeably refer to programs in which the application of test oracles is infeasible. ...
We would also like to express our gratitude to all of the authors of the papers that were processed by this Mapping Study, who assisted us through email correspondence. ...
doi:10.1007/s11219-017-9392-4
fatcat:hjipm2vrhfdtlbzshdkckvcuka
Astraea: Grammar-based Fairness Testing
[article]
2022
arXiv
pre-print
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Furthermore, ASTRAEA improves software fairness by ~76%, via model-retraining. ...
Using probabilistic grammars, ASTRAEA also provides fault diagnosis by isolating the cause of observed software bias. ASTRAEA's diagnoses facilitate the improvement of ML fairness. ...
This work was partially supported by the University of Luxembourg, Ezekiel Soremekun acknowledges the financial support of the Institute for Advanced Studies of the University of Luxembourg through an ...
arXiv:2010.02542v5
fatcat:n6ka7pbchrdczpnsgcjpomybfm
Is the Dawn of the Robot Lawyer upon us? The Fourth Industrial Revolution and the Future of Lawyers
2020
Potchefstroom Electronic Law Journal
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A number of technologies that fall under the AI umbrella, such as machine learning, natural language processing, deep learning and others, have already brought about the automation of many tasks that were ...
The practice of law has been largely shielded from technological developments in the course of the past 50 years. ...
to a higher degree of accuracy Much of the debate surrounding the impact of AI on the practice of law has centred on automation, and not augmentation. ...
doi:10.17159/1727-3781/2020/v23i0a6794
fatcat:avdgvmthejfkpc7grjdlzckpz4
Automatic Generation of Acceptance Test Cases from Use Case Specifications: an NLP-based Approach
2020
IEEE Transactions on Software Engineering
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More specifically, UMTG automates the generation of acceptance test cases based on use case specifications and a domain model for the system under test, which are commonly produced in many development ...
In this paper, we present Use Case Modeling for System-level, Acceptance Tests Generation (UMTG), an approach that supports the generation of executable, system-level, acceptance test cases from requirements ...
Luxembourg, the grant FNR/P10/03, the Canada Research Chair program, and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No ...
doi:10.1109/tse.2020.2998503
fatcat:f7ve42c7qzdnjjqrjr24f6apsm
Automatic Generation of Acceptance Test Cases from Use Case Specifications: an NLP-based Approach
[article]
2020
arXiv
pre-print
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More specifically, UMTG automates the generation of acceptance test cases based on use case specifications and a domain model for the system under test, which are commonly produced in many development ...
thus enabling the generation of test data. ...
Improved Specifications and Models. ...
arXiv:1907.08490v2
fatcat:lph77r5to5cc5mlczlee6sgk4e
Adaptive Metamorphic Testing with Contextual Bandits
[article]
2020
arXiv
pre-print
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Adaptive Metamorphic Testing efficiently identifies weaknesses of the tested systems in context of the source test case. ...
In this article, we propose Adaptive Metamorphic Testing as a generalization of a simple yet powerful reinforcement learning technique, namely contextual bandits, to select one of the multiple metamorphic ...
Declarations of Interest None of the authors declares a conflict of interest. ...
arXiv:1910.00262v3
fatcat:6y25b53dlffqxovcsyret7snqe
Three Risks That Caution Against a Premature Implementation of Artificial Moral Agents for Practical and Economical Use
2021
Science and Engineering Ethics
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The second thought experiment deals with the idea of a 'moral calculator'. ...
AbstractIn the present article, I will advocate caution against developing artificial moral agents (AMAs) based on the notion that the utilization of preliminary forms of AMAs will potentially negatively ...
The author would ...
doi:10.1007/s11948-021-00283-z
pmid:33496885
fatcat:xqagczpzsne2jf2dvbq3jprctu
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System
[article]
2022
arXiv
pre-print
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New safety standards and technical guidelines are under development to support the safety of ML-based systems, e.g., ISO 21448 SOTIF for the automotive domain and the Assurance of Machine Learning for ...
We present the outcome of applying AMLAS on SMIRK for a minimalistic operational design domain, i.e., a complete safety case for its integrated ML-based component. ...
This work was carried out within the SMILE III project financed by Vinnova, FFI, Fordonsstrategisk forskning och innovation under the grant number 2019-05871 and partially supported by the Wallenberg AI ...
arXiv:2204.07874v1
fatcat:u5ivkq344va7xib43dnjb6dcdy
D2.1 5G Security: Current Status and Future Trends
2020
Zenodo
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cases, and the elicitation of security requirements from relevant stakeholders in 5G; the current status of 5G networks, the solutions state for securing 5G systems, the standardization effort in the ...
This Deliverable presents the current security landscape of 5G networks, as well as the evolution of requirements and trends in 5G security. ...
Statistical behaviour analysis allows determining the clusters and an adjustment process improves the accuracy of the diagnoses. ...
doi:10.5281/zenodo.3947893
fatcat:bg7jnn5ph5fv3gjp7pqacy3us4
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