Theoretical Foundations for Runtime Monitoring

Réalisation : 10 septembre 2019 Mise en ligne : 10 septembre 2019
  • document 1 document 2 document 3
  • niveau 1 niveau 2 niveau 3
  • audio 1 audio 2 audio 3

Runtime monitoring/verification is a lightweight technique that complements other verification methods in a multi-pronged approach towards ensuring software correctness. The technique poses novel questions to software engineers: it is not easy to see which specifications are amenable to runtime monitoring, and it is not clear which monitors perform the required runtime analysis correctly.

In this talk, I will present a theoretical framework that can be used to provide answers to those questions. I will view monitorability as a spectrum: the fewer monitor guarantees are required, the more properties become monitorable. I will then present a monitorability hierarchy and provide operational characterisations for its levels. Existing monitorability definitions are mapped into the proposed hierarchy, providing a unified framework that makes the operational assumptions and guarantees of each definition explicit. This provides a rigorous foundation that can inform design choices and correctness claims for runtime verification tools.

The talk is based on joint work with my collaborators in the project Theoretical Foundations for Monitorability

Lieu de réalisation
Inria Sophia Antipolis
Langue :
CNRS - Centre National de la Recherche Scientifique (Publication), INRIA (Institut national de recherche en informatique et automatique) (Production), INRIA (Institut national de recherche en informatique et automatique) (Publication), UNS (Publication)
Conditions d'utilisation
Droit commun de la propriété intellectuelle
Citer cette ressource:
Inria. (2019, 10 septembre). Theoretical Foundations for Runtime Monitoring. [Vidéo]. Canal-U. (Consultée le 20 mai 2022)



  • [1] P Armitage and Doll. The age distribution of cancer and a multi-stage theory of carcinogenesis. Br J Cancer, 8(1) :1–12, 1954.
  • [2] S H Moolgavkar, N E Day, and R G Stevens. Two-stage model for carcinogenesis : Epidemiology of breast cancer in females. Journal of the National Cancer Institute, 65 :559–569, 1980.
  • [3] M. C. Pike, M. D. Krailo, B. E. Henderson, J. T. Casagrande, and D. G. Hoel. ’hormonal’ risk factors, ’breast tissue age’ and the age-incidence of breast cancer. Nature, 303(5920) :767–770, 1983.
  • [4] E B Claus, N Risch, and W D Thompson. The calculation of breast cancer risk for women with a first degree family history of ovarian cancer. Breast cancer research and treatment, 28 :115–120, Nov 1993.
  • [5] M H Gail and J Benichou. Validation studies on a model for breast cancer risk. Journal of the National Cancer Institute, 86 :573–575, Apr 1994.
  • [6] G Plu-Bureau, M G Lê, R Sitruk-Ware, J C Thalabard, and P Mauvais-Jarvis. Progestogen use and decreased risk of breast cancer in a cohort study of premenopausal women with benign breast disease. British journal of cancer, 70 :270–277, 1994.
  • [7] Eiliv Lund and Vanessa Dumeaux. Systems epidemiology in cancer. Cancer epidemiology, biomarkers & prevention, 17 :2954–2957, 2008.
  • [8] Eiliv Lund, Vanessa Dumeaux, Tonje Braaten, Anette Hjartåker, Dagrun Engeset, Guri Skeie, and Merethe Kumle. Cohort profile : The norwegian women and cancer study–nowac–kvinner og kreft. International journal of epidemiology, 37 :36–41, 2008.
  • [9] Marco Gerlinger, Andrew J Rowan, Stuart Horswell, James Larkin, David Endesfelder, Eva Gronroos, Pierre Martinez, Nicholas Matthews, Aengus Stewart, Patrick Tarpey, Ignacio Varela, Benjamin Phillimore, Sharmin Begum, Neil Q McDonald, Adam Butler, David Jones, Keiran Raine, Calli Latimer, Claudio R Santos, Mahrokh Nohadani, Aron C Eklund, Bradley Spencer-Dene, Graham Clark, Lisa Pickering, Gordon Stamp, Martin Gore, Zoltan Szallasi, Julian Downward, P Andrew Futreal, and Charles Swanton. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England journal of medicine, 366 :883–892, Mar 2012.
  • [10] Eiliv Lund, Nicolle Mode, Marit Waaseth, and Jean-Christophe Thalabard. Overdiagnosis of breast cancer in the norwegian breast cancer screening program estimated by the norwegian women and cancer cohort study. BMC cancer, 13 :614, 2013.
  • [11] Mary-Claire King. « the race » to clone brca1. Science, 343 :1462–1465, 2014.
  • [12] Vanessa Dumeaux, Josie Ursini-Siegel, Arnar Flatberg, Hans E Fjosne, Jan-Ole Frantzen, Marit Muri Holmen, Enno Rodegerdts, Ellen Schlichting, and Eiliv Lund. Peripheral blood cells inform on the presence of breast cancer : a population-based case-control study. International journal of cancer, 136 :656–667, 2015.
  • [13] Eiliv Lund, Lars Holden, Hege Bøvelstad, Sandra Plancade, Nicolle Mode, Clara-Cecilie Günther, Gregory Nuel, Jean-Christophe Thalabard, and Marit Holden. A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the nowac postgenome cohort as a proof of principle. BMC medical research methodology, 16 :28, 2016.
  • [14] NE Breslow and NE Day. Statistical Methods in Cancer Research Volume II – The Design and Analysis of Cohort Studies, volume II of IARC Scientific Publications No 82. IARC, 1987.
  • [15] NE Breslow and NE Day. Statistical Methods in Cancer Research. Volume I :The analysis of case- control studies, volume I of IARC Scientific Publications No. 32. IARC, 1980.

Sur le même thème