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Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …

保存引用被引用数: 251 関連記事全 14 バージョン

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[PDF] arxiv.org

Machine learning testing: Survey, landscapes and horizons

JM Zhang, M Harman, L Ma… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org

This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …

保存引用被引用数: 1012 関連記事全 14 バージョン

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[PDF] gigvvy.com

Survey on software defect prediction techniques

MK Thota, FH Sha**, P Rajesh - International Journal of Applied …, 2020 - gigvvy.com

Recent advancements in technology have emerged the requirements of hardware and
software applications. Along with this technical growth, software industries also have faced …

保存引用被引用数: 315 関連記事全 4 バージョン HTMLバージョン

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[PDF] wiley.com Full View

Autonomous vehicles and intelligent automation: Applications, challenges, and opportunities

G Bathla, K Bhadane, RK Singh… - Mobile Information …, 2022 - Wiley Online Library

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

保存引用被引用数: 191 関連記事全 9 バージョン

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[PDF] acm.org

DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems

M Zhang, Y Zhang, L Zhang, C Liu… - Proceedings of the 33rd …, 2018 - dl.acm.org

While Deep Neural Networks (DNNs) have established the fundamentals of image-based
autonomous driving systems, they may exhibit erroneous behaviors and cause fatal …

保存引用被引用数: 736 関連記事全 9 バージョン

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[PDF] acm.org

Collaboration challenges in building ml-enabled systems: Communication, documentation, engineering, and process

N Nahar, S Zhou, G Lewis, C Kästner - Proceedings of the 44th …, 2022 - dl.acm.org

The introduction of machine learning (ML) components in software projects has created the
need for software engineers to collaborate with data scientists and other specialists. While …

保存引用被引用数: 162 関連記事全 9 バージョン

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[PDF] hku.hk

Metamorphic testing: A review of challenges and opportunities

TY Chen, FC Kuo, H Liu, PL Poon, D Towey… - ACM Computing …, 2018 - dl.acm.org

Metamorphic testing is an approach to both test case generation and test result verification.
A central element is a set of metamorphic relations, which are necessary properties of the …

保存引用被引用数: 573 関連記事全 18 バージョン

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[PDF] arxiv.org

A software engineering perspective on engineering machine learning systems: State of the art and challenges

G Giray - Journal of Systems and Software, 2021 - Elsevier

Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

保存引用被引用数: 195 関連記事全 6 バージョン

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[PDF] whiterose.ac.uk

A survey on metamorphic testing

S Segura, G Fraser, AB Sanchez… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org

A test oracle determines whether a test execution reveals a fault, often by comparing the
observed program output to the expected output. This is not always practical, for example …

保存引用被引用数: 597 関連記事全 11 バージョン

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Machine learning testing: Survey, landscapes and horizons

Survey on software defect prediction techniques

Autonomous vehicles and intelligent automation: Applications, challenges, and opportunities

DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems

Collaboration challenges in building ml-enabled systems: Communication, documentation, engineering, and process

Metamorphic testing: A review of challenges and opportunities

A software engineering perspective on engineering machine learning systems: State of the art and challenges

A survey on metamorphic testing