Expert review of Taxonomy based testing – a testing framework for medical device software

Ketheswarasarma Rajaram, Hamsini and Loane, John and McCaffery, Fergal and MacMahon, Silvana Togneri (2021) Expert review of Taxonomy based testing – a testing framework for medical device software. In: ENASE 2021. 16th international conference on evaluation of novel approaches to software engineering..

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This paper details the expert review of a framework developed to implement a novel testing approach called taxonomy-based testing (TBT) for the medical device software domain. This framework proposes three approaches to implement TBT and has been validated by experts from the software testing industry and the medical device software domain. This paper details the results from the expert review. The expert review focused on validating the three approaches to TBT, the benefits of TBT to medical device software development, the accuracy of mappings of testing techniques from ISTQB and ISO/IEC/IEEE 29119-4:2015 to defects from a defect taxonomy, the integration of TBT into the standard test processes, ISTQB and ISO/IEC/IEEE 29119-2:2013 and the structure of the framework. The contribution of this paper is to reveal that (i) the framework is implementable in medical device software organisations that follow the IEC 62304:2006+A1:2015 software development process or that use standard test processes, (ii) using a defect taxonomy could standardise the application of experience-based approaches to software testing and (iii) considering potential defects before writing test cases could identify additional defects for test cases.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: The US FDA; Taxonomy; SW91; ISO/IEC/IEEE 29119; IEC 62304; Framework; Expert review; Software testing; Recalls.
Subjects: Computer Science
Computer Science > Computer Software
Research Centres: Regulated Software Research Centre
Depositing User: Sean McGreal
Date Deposited: 23 Apr 2021 13:48
Last Modified: 23 Apr 2021 13:48
License: Creative Commons: Attribution-Noncommercial-Share Alike 4.0

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