Nyirenda, Misheck and Loughran, Roisin and Mc Hugh, Martin and Nugent, Christopher and McCaffery, Fergal (2023) Identifying Agile Practices to Reduce Defects in Medical Device Software Development. In: Systems, Software and Services Process Improvement 2023, 29 August to 2 September 2023, Grenoble, France.
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Abstract
Medical Device Software (MDS) defects have caused death of patients and continue to be the major cause of recalls of medical devices in the US and Europe. Despite various approaches proposed to address defects, dealing with defects in MDS is an increasingly difficult task as MDS has become more complex to support a growing number of functions. To increase quality in any software development project, it is essential that defects are identified and addressed quickly in the early stages of the software development life cycle. Agile methods have been advocated to increase software quality by minimising defects through their agile practices. However, agile methods on their own are deficient in satisfying the regulatory requirements for the MDS domain. Instead, the common approach is to integrate agile practices into the plan driven methods. Consequently, frameworks have been developed to help developers in the MDS domain to accrue the benefits of agile development while fulfilling regulatory requirements. Despite the adoption of agile practices in MDS development, it is still unclear as to which agile practice(s) is effective and how it is applied to address MDS defects. The purpose of this research is to identify agile practices that can assist in addressing defects in MDS development. This will help MDS developers to select the appropriate agile practice(s) to address defects.
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Computer Science > Computer Software |
Research Centres: | Regulated Software Research Centre |
Depositing User: | Misheck Nyirenda |
Date Deposited: | 24 Oct 2023 15:05 |
Last Modified: | 09 Nov 2023 09:35 |
License: | Creative Commons: Attribution-Noncommercial-Share Alike 4.0 |
URI: | https://eprints.dkit.ie/id/eprint/859 |
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