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Register a new userAssessing Support for Industry Standards in Reference Medical Software Architectures
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Added by
Roopak Sinha
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Industrial standards for developing medical device software provide requirements that conforming devices must meet. A number of reference software architectures have been proposed to develop such software. The ISO/IEC 25010:2011 family of standards provides a comprehensive software product quality model, including characteristics that are highly desirable in medical devices. Furthermore, frameworks like 4+1 Views provide a robust framework to develop the software architecture or high level design for any software, including for medical devices. However, the alignment between industrial standards and reference architectures for medical device software, on one hand, and ISO/IEC 25010:2011 and 4+1 Views, on the other, is not well understood. This paper aims to explore how ISO/IEC 25010:2011 and 4+1 Views are supported by current standards, namely ISO 13485:2016, ISO 14971:2012, IEC 62304:2006 and IEC 62366:2015, and current reference architectures for medical device software. We classified requirements from medical devices standards into qualities from ISO/IEC 25010:2011 and architectural views from 4+1 Views. A systematic literature review (SLR) method was followed to review current references software architectures and a mapping of their support for the identified ISO/IEC 25010:2011 qualities in the previous step was carried out. Our results show that ISO/IEC 25010:2011 qualities like functional suitability, portability, maintainability, usability, security, reliability and compatibility are highly emphasised in medical device standards. Furthermore, we show that current reference architectures only partially support these qualities. This paper can help medical device developers identify focus areas for developing standards-compliant software. A wider study involving under-development medical devices can help improve the accuracy of our findings in the future.
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