Design of Prioritized N-Wise Testing

Choi, Eun-Hye; Kitamura, Takashi; Artho, Cyrille; Oiwa, Yutaka

doi:10.1007/978-3-662-44857-1_14

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…A common method to handle continuous parameters is discretization, which is a process of quantizing continuous attributes by converting the continuous data into a finite set of intervals and assigning some 11. N-wise coverage states that all N-tuples of parameter values must be tested at least once, given an SoI model with the parameter list, values, and constraints to define parameter interactions [131] specific data values to each interval [133]. In some other studies, Tuncali et al [65] circumvented the problem by a two-step approach.…”

Section: Exploration Methodsmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Zhang¹,

Tao²,

Tan

et al. 2023

IIEEE Trans. Software Eng.

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Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an Automated Driving System or Advanced Driving-Assistance System may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic mapping study in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

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Section: Exploration Methodsmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Zhang¹,

Tao²,

Tan

et al. 2023

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…6. N-wise coverage states that all N-tuples of parameter values must be tested at least once, given an SoI model with the parameter list, values, and constraints to define parameter interactions [128] The choice of optimizer highly depends on the problem formulation, especially the transparency and complexity of the underlying models. A simulator is commonly employed when estimating criticality measures.…”

Section: Exploration Methodsmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

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Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic literature review in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

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“…Our goal is to obtain a small test suite where important test cases appear early and frequently. In earlier work [2], we have proposed our basic idea of priority integration for weighted combinatorial testing, which integrates the three criteria of CS, CO, and CF. We assume that a priority order for combining the three criteria CS, CO, and CF is given, and we construct an algorithm for test generation according to the given prioritization order.…”

Section: Proposed Weighted Pairwise Testingmentioning

confidence: 99%

Priority Integration for Weighted Combinatorial Testing

Choi

Kitamura

Artho

et al. 2015

2015 IEEE 39th Annual Computer Software and Applications Conference

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Priorities (weights) for parameter values can improve the effectiveness of combinatorial testing. Previous approaches have employed weights to derive high-priority test cases either earlier or more frequently. Our approach integrates these order-focused and frequency-focused prioritizations. We show that our priority integration realizes a small test suite providing high-priority test cases early and frequently in a good balance. We also propose two algorithms that apply our priority integration to existing combinatorial test generation algorithms. Experimental results using numerous test models show that our approach improves the existing approaches w.r.t. Order-focused and frequency-focused metrics, while overheads in the size and generation time of test suites are small.

QC 20170109

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Design of Prioritized N-Wise Testing

Abstract:
QC 20170105

Cited by 5 publications

References 5 publications

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Priority Integration for Weighted Combinatorial Testing

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Design of Prioritized N-Wise Testing

Abstract: QC 20170105

Cited by 5 publications

References 5 publications

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Priority Integration for Weighted Combinatorial Testing

Contact Info

Product

Resources

About

Abstract:
QC 20170105