Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Engineering in software testing: statistical testing based on a usage model applied to medical device development.

P L Jones1, W T Swain, C J Trammell

  • 1Center for Devices and Radiological Health, Food and Drug Administration, Rockville, MD 20857, USA. pxj@cdrh.fda.gov

Biomedical Instrumentation & Technology
|August 25, 1999
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Divergent climate impacts despite similar response to temperature in a widespread aerial insectivore.

bioRxiv : the preprint server for biology·2025
Same author

Early Vision for the CTSA Program Trial Innovation Network: A Perspective from the National Center for Advancing Translational Sciences.

Clinical and translational science·2017
Same author

Risky ripples allow bats and frogs to eavesdrop on a multisensory sexual display.

Science (New York, N.Y.)·2014
Same author

Rodlet cells in Murray cod, Maccullochella peelii peelii (Mitchell), affected with chronic ulcerative dermatopathy.

Journal of fish diseases·2013
Same author

Biennial reproductive cycle in an extensive matrotrophic viviparous batoid: the sandyback stingaree Urolophus bucculentus from south-eastern Australia.

Journal of fish biology·2012
Same author

LC-PUFA biosynthesis in rainbow trout is substrate limited: use of the whole body fatty acid balance method and different 18:3n-3/18:2n-6 ratios.

Lipids·2011
Same journal

Improving Sterile Processing Operational Efficiency through Organizational Change.

Biomedical instrumentation & technology·2026
Same journal

Detecting Secondary Medication Infusion Errors via Spectrophotometry.

Biomedical instrumentation & technology·2026
Same journal

Inactivation of Endotoxin by Moist Heat, Electron Beam, and Gamma Irradiation.

Biomedical instrumentation & technology·2026
Same journal

Biological Indicators and Process Challenge Devices for Nitrogen Dioxide Sterilization.

Biomedical instrumentation & technology·2026
Same journal

Laparoscopic Instrument Defect Detection: A Prospective, Multisite Study.

Biomedical instrumentation & technology·2026
Same journal

Impact of Leadership Structures on Sterile Processing Performance and Patient Safety.

Biomedical instrumentation & technology·2026
See all related articles

Statistical testing uses Markov chain usage models to represent software use cases. This approach enables early product development insights and scientifically quantifies software reliability.

Area of Science:

  • Software Engineering
  • Statistical Analysis
  • Reliability Engineering

Background:

  • Software systems often have too many potential uses for complete testing.
  • Statistical sampling is necessary for drawing valid inferences about software behavior.
  • Markov chain usage models offer a formal method to represent software use populations.

Purpose of the Study:

  • To introduce Markov chain usage models for statistical software testing.
  • To leverage Markov chain theory for improved product development and test planning.
  • To establish a scientific foundation for quantifying software reliability.

Main Methods:

  • Developing Markov chain usage models based on software specifications.
  • Applying analytical results from Markov chain theory to software testing.

Related Experiment Videos

  • Utilizing model-derived insights for early-stage product decision-making.

    • Main Results:

    • Markov chain usage models provide a framework for statistical software testing.
    • Insights from model building can influence product design early in development.
    • This methodology allows for the scientific quantification of software reliability.

    Conclusions:

    • Markov chain usage models offer a robust approach to statistical software testing.
    • Early insights from usage models significantly enhance product development.
    • Statistical testing based on usage models provides a reliable measure of software quality.