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2019 | OriginalPaper | Buchkapitel

Improving ML Safety with Partial Specifications

verfasst von : Rick Salay, Krzysztof Czarnecki

Erschienen in: Computer Safety, Reliability, and Security

Verlag: Springer International Publishing

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Abstract

Advanced autonomy features of vehicles are typically difficult or impossible to specify precisely and this has led to the rise of machine learning (ML) from examples as an alternative implementation approach to traditional programming. Developing software without specifications sacrifices the ability to effectively verify the software yet this is a key component of safety assurance. In this paper, we suggest that while complete specifications may not be possible, partial specifications typically are and these could be used with ML to strengthen safety assurance. We review the types of partial specifications that are applicable for these problems and discuss the places in the ML development workflow that they could be used to improve the safety of ML-based components.

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Titel: Improving ML Safety with Partial Specifications
verfasst von: Rick Salay
Krzysztof Czarnecki
Verlag: Springer International Publishing
Buch: Computer Safety, Reliability, and Security
Print ISBN: 978-3-030-26249-5

Electronic ISBN: 978-3-030-26250-1

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-26250-1_23

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