Quantitative Verification with Adaptive Uncertainty Reduction

Alasmari, Naif, Calinescu, Radu orcid.org/0000-0002-2678-9260, Paterson, Colin orcid.org/0000-0002-6678-3752 et al. (1 more author) (2022) Quantitative Verification with Adaptive Uncertainty Reduction. Journal of Systems and Software. 111275. ISSN 0164-1212



Copyright, Publisher and Additional Information: © 2022 Elsevier Inc. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.
Keywords: quantitative verification, probabilistic model checking, confidence intervals, uncertainty reduction, nonfunctional requirements, unit testing
  • Accepted: 16 February 2022
  • Published (online): 22 February 2022
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 18 Feb 2022 09:40
Last Modified: 25 Aug 2023 23:15
Published Version: https://doi.org/10.1016/j.jss.2022.111275
Status: Published online
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.jss.2022.111275


Filename: Quantitative_Verification_with_Adaptive_Uncertainty_Reduction.pdf

Description: Quantitative Verification with Adaptive Uncertainty Reduction

Licence: CC-BY-NC-ND 2.5