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Record W2005212577 · doi:10.4018/jismd.2011040104

The Impact of Regulatory Compliance on Agile Software Processes with a Focus on the FDA Guidelines for Medical Device Software

2011· article· en· W2005212577 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Information System Modeling and Design · 2011
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsConcordia University
Fundersnot available
KeywordsAgile software developmentFood and drug administrationSoftwareRisk analysis (engineering)Work (physics)Medical softwareCompliance (psychology)Process (computing)BusinessProcess managementEngineeringKnowledge managementSoftware developmentComputer scienceSoftware engineeringSoftware quality

Abstract

fetched live from OpenAlex

The difficulty of complying with different regulations has become more evident as a large number of regulated businesses are mandated to follow an ever-increasing set of regulations. These regulations often drive significant changes in the way organizations operate to deliver value to their customers. This paper focuses on the impact of the Food and Drug Administration (FDA) regulations on agile software development processes, which in many ways can be considered as just another type of organizational processes. Particular focus is placed on the ability for Extreme Programming (XP) to support FDA requirements. Findings show that XP fails to meet many of the FDA guidelines for medical device software, which increases the risks of non-compliance for organizations that have adopted XP as their main software process. The results of this study can lead the work towards designing an extension to XP for FDA regulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.811
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.127
GPT teacher head0.338
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it