Fenton, N.E. and M. Neil, Risk Assessment and Decision Analysis with Bayesian Networks, Second Edition. 2018, Chapman and Hall/CRC Press, ISBN: 9781138035119, 2018
Fenton, N. E. and J. Bieman (2014) “Software Metrics: A Rigorous and Practical Approach” (3rd Edition). CRC Press, ISBN 9781439838228
Fenton, N.E. and M. Neil, Risk Assessment and Decision Analysis with Bayesian Networks. 2012, CRC Press, ISBN: 9781439809105 , ISBN 10: 1439809100, 2012
Fenton NE and Von Mayrhauser A (Editors), Proceedings of 1st Intl Software Metrics Symposium, IEEE Computer Society Press, 1993.
Fenton NE, 'Software Metrics: A Rigorous Approach', Chapman and Hall, 1991.
Fenton NE and Littlewood B (Eds), 'Software Reliability and Metrics', Elsevier, 1991.
NOTE: This page is no longer being updated. For the updated list of Norman Fenton's publications (grouped by subject category) see: https://www.normanfenton.com/publications-1
Fenton, N. E., and Lagnado, D (2021) "Bayesianism: Objections and Rebuttals", in G. Tuzet, C. Dahlman en A. Stein (eds.) Philosophical Foundations of Evidence Law. Oxford University Press, to appear.
Hartmann M, Fenton NE and Dobson R, “Current Review and Next Steps for Artificial Intelligence in Multiple Sclerosis Risk Research” (2021) Comput. Biol. Med. https://doi.org/10.1016/j.compbiomed.2021.104337 (also available here: Pre-print pdf)
Hartmann M, Fenton NE and Dobson R, “Recognizing and Adjusting for Paradoxes in Multiple Sclerosis Datasets Using Bayesian Networks” , submitted to ICHI 2021 IEEE International Conference on Healthcare Informatics (2021).
Constantinou AC, Fenton N and Neil M (2021), “How Do Some Bayesian Network Machine Learned Graphs Compare to Causal Knowledge?” , http://arxiv.org/abs/2101.10461.
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E. Neil, M. (2021). "A Bayesian network model for personalised COVID19 risk assessment and contact tracing" https://doi.org/10.1101/2020.07.15.20154286
Fenton, N. E. (2020) How to explain an increasing proportion of people testing positive for COVID if there is neither an increase in proportion of genuine cases nor increase in the false positive rate. https://doi.org/10.13140/RG.2.2.27902.20806
Collins, R., & Fenton, N. (2020). Bayesian network modelling for early diagnosis and prediction of Endometriosis. MedRxiv, 2020.11.04.20225946. https://doi.org/10.1101/2020.11.04.20225946
McLachlan S, Kyrimi E, Dube K, Hitman G, Simmonds J and Fenton N E, “Towards Standardisation of Evidence-Based Clinical Care Process Specifications” (2020) 26 Health Informatics J. 25 (4), 2512-2538, https://doi.org/10.1177/1460458220906069
McLachlan, S., Kyrimi, E., Dube, K., Fenton, N., & Webley, L. (2020). Lawmaps: Enabling Legal AI development through Visualisation of the Implicit Structure of Legislation and Lawyerly Process. http://arxiv.org/abs/2011.00586
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E. Neil, M. (2021). "A Bayesian network model for personalised COVID19 risk assessment and contact tracing" https://doi.org/10.1101/2020.07.15.20154286
Butcher, R., & Fenton, N. E. (2020). Extending the range of symptoms in a Bayesian Network for the Predictive Diagnosis of COVID-19, medRxiv https://doi.org/10.1101/2020.10.22.20217554
Prodhan, G., & Fenton, N. E. (2020). Extending the range of COVID-19 risk factors in a Bayesian network model for personalised risk assessment. medRxiv https://doi.org/10.1101/2020.10.20.20215814
Hunte, J., Fenton, N. E., & Neil, M. (2020). Product risk assessment: a Bayesian network approach. https://arxiv.org/abs/2010.06698
Lin, P., Neil, M., & Fenton, N.E. (2020). Improved High Dimensional Discrete Bayesian Network Inference using Triplet Region Construction. Journal of Artificial Intelligence Research, 69, 231–295. https://doi.org/10.1613/jair.1.12198
Fenton, N.E. , Jamieson, A., Gomes, S., & Neil, M. (2020). "On the limitations of probabilistic claims about the probative value of mixed DNA profile evidence". http://arxiv.org/abs/2009.08850
Osman, M., McLachlan, S., Fenton, N. E., Neil, M., Löfstedt, R., & Meder, B. (2020). "Learning from behavioural changes that fail". Trends in Cognitive Science, https://doi.org/10.1016/j.tics.2020.09.009 Blog post here. Accepted version (pdf).
Cruz, N., Hahn, U., Fenton, N. E., & Lagnado, D. A. (2020). Explaining away, augmentation, and the noisy assumption of independence. Frontiers in Psychology, 11, 502751. https://doi.org/10.3389/fpsyg.2020.502751 Accepted version (pdf). Blog post here.
Fenton N. E, Neil M, McLachlan S, Osman M (2020), "Misinterpreting statistical anomalies and risk assessment when analysing Covid-19 deaths by ethnicity", 10.13140/RG.2.2.18957.56807 Also here: preprint. Blog post here. To appear in Significance.
Fenton, N E., Neil, M., & Frazier, S. (2020). The role of collider bias in understanding statistics on racially biased policing. http://arxiv.org/abs/2007.08406
Fenton, N E. (2020). A Note on UK Covid19 death rates by religion: which groups are most at risk? http://arxiv.org/abs/2007.07083
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E., Neil, M. (2020). "A privacy-preserving Bayesian network model for personalised COVID19 risk assessment and contact tracing". MedRxiv, 2020.07.15.20154286. https://doi.org/10.1101/2020.07.15.20154286
Kyrimi, E., Neves, M., Neil, M., Marsh, W., McLachlan, S., & Fenton, N. E. (2020). "Medical idioms for clinical Bayesian network development". Journal of Biomedical Informatics, Vol 108, 103495, https://doi.org/10.1016/j.jbi.2020.103495. Accepted version available here
Neil, M., Fenton, N E., Osman, M., & McLachlan, S. (2020). "Coronavirus: our study suggests more people have had it than previously estimated", The Conversation, 26 June 2020
Neil, M., Fenton, N.E, Osman, M., & McLachlan, S. (2020). "Bayesian Network Analysis of Covid-19 data reveals higher Infection Prevalence Rates and lower Fatality Rates than widely reported". Journal of Risk Research, 23 (7-8), 866-879 https://doi.org/10.1080/13669877.2020.1778771 . Preprint: MedRxiv, 2020.05.25.20112466. https://doi.org/10.1101/2020.05.25.20112466 Blog post here
Pilditch, T., Hahn, U., Fenton, N. E., & Lagnado, D. A. (2020). "Dependencies in evidential reports: The case for informational advantages". Cognition, Vol 204, 104343 https://doi.org/10.1016/j.cognition.2020.104343 Preprint (accepted version) here. Blog post here
Osman, M., Fenton, N. E. , McLachlan, S., Lucas, P., Dube, K., Hitman, G. A., Kyrimi, E, Neil, M, (2020)."The thorny problems of Covid-19 Contact Tracing Apps: The need for a holistic approach", Journal of Behavioral Economics for Policy, Vol. 4, 57-61. Published version. Also available here.
Dewitt, S., Fenton, N. E., & Liefgreen, AliceLagnado, D. A. (2020). Propensities and second order uncertainty: a modified taxi cab problem. Frontiers in Psychology, 11, 503233. https://doi.org/10.3389/fpsyg.2020.503233 Accepted version (pdf). Blog post here.
McLachlan, S., Dube, K., Hitman, G. A., Fenton, N. E., & Kyrimi, E. (2020). Bayesian networks in healthcare: Distribution by medical condition. Artificial Intelligence in Medicine, 107, 101912. https://doi.org/10.1016/J.ARTMED.2020.101912
Dube, K., Mclachlan, S., Zanamwe, N., Kyrimi, E., Thomson, J. S., & Fenton, N. E (2020.). "Managing Knowledge in Computational Models for Global Food, Nutrition and Health Technologies." 2020 IEEE Global Humanitarian Technology Conference (GHTC) (GHTC 2020) https://doi.org/10.1109/GHTC46280.2020.9342880
McLachlan, S., Lucas, P., Dube, K., McLachlan, G. S., Hitman, G. A., Osman, M., Kyrimi, E, Neil, M, Fenton, N. E. (2020). "COVID-19 and contact tracing: literature review and additional analysis", submitted to BMC Public Health
Fenton, N E (2020), "Why most studies into COVID19 risk factors may be producing flawed conclusions-and how to fix the problem", http://arxiv.org/abs/2005.08608 Blog post here
McLachlan, S., Lucas, P., Dube, K., McLachlan, G. S., Hitman, G. A., Osman, M., Kyrimi, E, Neil, M, Fenton, N. E. (2020). "The fundamental limitations of COVID-19 contact tracing methods and how to resolve them with a Bayesian network approach". https://doi.org/10.13140/RG.2.2.27042.66243
McLachlan, S., Lucas, P., Dube, K., Hitman, G. A., Osman, M., Kyrimi, E., … Fenton, N. E. (2020). Bluetooth Smartphone Apps: Are they the most private and effective solution for COVID-19 contact tracing? http://arxiv.org/abs/2005.06621
Fenton, N. E. (2020). "The Deer Hunter: A lesson in the basics of risk and probability assessment". https://doi.org/10.13140/RG.2.2.31675.98089. (also available here). Blog post here and video
Fenton, N. E., Neil, M., Osman, M., & McLachlan, S. (2020). "COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing". Journal of Risk Research, 1–4. https://doi.org/10.1080/13669877.2020.1756381
Fenton, N. E., Neil, M., & Constantinou, A. (2020). The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie, Basic Books (2018). Artificial Intelligence, 284, 103286. https://doi.org/10.1016/J.ARTINT.2020.103286
Fenton, N.E., Hitman, G. A., Neil, M., Osman, M., & McLachlan, S. (2020). Causal explanations, error rates, and human judgment biases missing from the COVID-19 narrative and statistics. PsyArXiv Preprints. https://doi.org/10.31234/OSF.IO/P39A4
Fenton, N. E., Osman, M., Neil, M., & McLachlan, S. (2020). Coronavirus: country comparisons are pointless unless we account for these biases in testing. The Conversation, April 2, 2020 Spanish version: Coronavirus: las comparaciones entre países no tienen sentido a menos que tengamos en cuenta los sesgos en las pruebas.
Fenton, N. E., Osman M, Neil, M., & McLachlan, S. (2020). Improving the statistics and analysis of coronavirus by avoiding bias in testing and incorporating causal explanations for the data. pdf
Kyrimi, E, McLachlan, S, Dube, K, Neves M R, Fahmi,A, Fenton, N E, (2020) "A Comprehensive Scoping Review of Bayesian Networks in Healthcare: Past, Present and Future", arXiv:2002.08627
Kyrimi, E., McLachlan, S., Dube, K., & Fenton, N.E (2020). Bayesian Networks in Healthcare: the chasm between research enthusiasm and clinical adoption. MedRxiv, 2020.06.04.20122911. https://doi.org/10.1101/2020.06.04.20122911
McLachlan S., Kyrimi E., Dube K., Fenton N. (2020) Standardising Clinical Caremaps: Model, Method and Graphical Notation for Caremap Specification. In: Roque A. et al. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2019. Communications in Computer and Information Science, vol 1211. Springer, Cham https://doi.org/10.1007/978-3-030-46970-2_21
Daley, B. J., Kyrimi, E., Dube, K., Fenton, N. E., Hitman, G. A., & McLachlan, S. (2020). Data Visualisation in Midwifery: The Challenge of Seeing what Datasets Hide. Studies in Health Technology and Informatics, 270, 1239–1240. https://doi.org/10.3233/SHTI200381
McLachlan, S., Kyrimi, E., & Fenton, N. (2020). Public Authorities as Defendants: Using Bayesian Networks to determine the Likelihood of Success for Negligence claims in the wake of Oakden. http://arxiv.org/abs/2002.05664
Wang, J., Neil, M., & Fenton, N. E. (2020). "A Bayesian Network Approach for Cybersecurity Risk Assessment Implementing and Extending the FAIR Model". Computers and Security, Vol 89. DOI: 10.1016/j.cose.2019.101659
See also blog post.
Mclachlan, S., Dube, K., Kyrimi, E., & Fenton, N. (2019). "LAGOS: learning health systems and how they can integrate with patient care". BMJ Health Care Inform, 26, 100037. https://doi.org/10.1136/bmjhci-2019-100037
Dube, K., McLachlan, S., Zanamwe, N., Kyrimi, E., Thomson, J., & Fenton, N. (2019). "Managing Knowledge Incorporated into Solution Models for Customisable Global Health Technologies". IEEE Global Humanitarian Technology Conference (GHTC), ISBN: 978-1-7281-1780-5/19 pages 303-310.
Zhang, H., Marsh, W. R., Fenton, N., & NEIL, M. (2019). "Realising the Potential for ML from Electronic Health Records". Proc. 1st International ‘Alan Turing’ Conference on Decision Support and Recommender Systems (DSRS-Turing 2019). London, UK. Accepted version (pdf)
McLachlan, Scott, Kudakwashe Dube, Thomas Gallagher, Jennifer A. Simmonds, and Norman Fenton. 2019. “Realistic Synthetic Data Generation: The ATEN Framework.” In , 497–523. Springer, Cham. https://doi.org/10.1007/978-3-030-29196-9_25.
Fenton, N. E. (2019). Book Review: Pat Wiltshire’s “Traces: The memoirs of a forensic scientist and criminal investigator” 535 Books, 2019. https://doi.org/10.13140/RG.2.2.29938.66247 Also available here.
Fenton, N. E. (2019). Book Review: David Spiegelhalter’s “The Art of Statistics: How to Learn from Data.” London UK. https://doi.org/10.13140/RG.2.2.28462.46400 Also available here
Daley, B., Hitman, G., Fenton, N.E., & McLachlan, S. (2019). "Assessment of the methodological quality of local clinical practice guidelines on the identification and management of gestational diabetes". BMJ Open, 9(6), e027285. https://doi.org/10.1136/bmjopen-2018-027285. Full paper (pdf)
Noguchi, T., Fenton, N. E., & Neil, M. (2019). Addressing the Practical Limitations of Noisy-OR using Conditional Inter-causal Anti-Correlation with Ranked Nodes. IEEE Transactions on Knowledge and Data Engineering, 31(4): 813-817, http://doi.org/10.1109/TKDE.2018.2873314. (This is open access).
Dewitt S.H., Hsu A.S., Lagnado D.A., Desai S.C, Fenton N.E. (2019) "Nested Sets and Natural Frequencies", COGSCI 2019, 41st Annual Meeting of the Cognitive Science Society, Montreal, Canada, July 24th – Saturday July 27th, 2019 . Accepted paper (pdf)
Fenton, N. E., Lagnado, D. A., Dahlman, C., & Neil, M. (2019). "The Opportunity Prior: A proof-based prior for criminal cases", Vol 18(4), 237-253 Law, Probability and Risk, DOI 10.1093/lpr/mgz007. Full paper from OUP.
Fenton, N. E.. (2019). When “absence of forensic evidence” is not “neutral.” https://doi.org/10.13140/RG.2.2.14517.73440
Fenton, N. E.., Neil, M., Yet, B., & Lagnado, D. A. (2019). "Analyzing the Simonshaven Case using Bayesian Networks". Topics in Cognitive Science, 10.1111/tops.12417 . The published version can be read here: https://rdcu.be/bqYxp See also blog post
Fenton, N. E. (2019) "Hannah Fry’s 'Hello World' and the Example of Algorithm Bias", DOI 10.13140/RG.2.2.14339.55844 Download pdf See also blog post
Stephen Dewitt, Adler, N., Fenton, N. E., & Lagnado, D. (2019). "Categorical Propensity Updating: A Novel Form of Confirmation Bias". Cogn Psychol, sumitted.
de Zoete, J., Fenton, N. E., Noguchi, T., & Lagnado, D. A. (2019). "Countering the ‘probabilistic paradoxes in legal reasoning’ with Bayesian networks". Science & Justice 59 (4), 367-379 10.1016/j.scijus.2019.03.003 The pre-publication version (pdf) The models See also blog post.
McLachlan, S., Dube, K., Johnson, O., Buchanan, D., Potts, H. W. W., Gallagher, T., Marsh, D.W., Fenton, N. E. (2019). "A Framework for Analysing Learning Health Systems: Are we removing the most impactful barriers?", Learning Health Systems, March 2019, Vol 3 (4), e10189 10.1002/lrh2.10189.
McLachlan, S., Kyrimi, E., Dube, K., & Fenton, N. E.. (2019). "Clinical Caremap Development: How can caremaps standardise care when they are not standardised?" In HealthInf 13 Annual International Conference on Health Informatcis. Prague, Czech Republic. Feb 2019 Pre-publication version (pdf)
Neil, M., Fenton, N. E., Lagnado, D. A. & Gill, R. (2019), "Modelling competing legal arguments using Bayesian Model Comparison and Averaging". Artififical Intelligence and Law Vol 27, 403-430 . https://doi.org/10.1007/s10506-019-09250-3. The full published version can be read here. Pre-publication version (pdf)
Neil, M., Fenton, N. E., Osman, M., & Lagnado, D. A. (2019). Causality, the critical but often ignored component guiding us through a world of uncertainties in risk assessment. Journal of Risk Research, to 10.1080/13669877.2019.1606454. Pre-publication version (pdf).
Fenton, N. E., Noguchi, T. & Neil, M (2019). "An extension to the noisy-OR function to resolve the “explaining away” deficiency for practical Bayesian network problems". IEEE Transactions on Knowledge and Data Engineering, 31(12), 2441-2445 DOI: 10.1109/TKDE.2019.2891680 Accepted version (pdf)
Pilditch, T., Fenton, N. E., & Lagnado, D. A. (2019). "The zero-sum fallacy in evidence evaluation". Psychological Science Vol 30 (2), pp 250-260 http://doi.org/10.1177/0956797618818484 See also blog posting.
Fenton, N. E., (2018) "A Bayesian Network and Influence Diagram for a simple example of Drug Economics Decision Making", https://doi.org/10.13140/RG.2.2.33659.77600
Dewitt, S., Lagnado, D., & Fenton, N. E. (2018). "Updating Prior Beliefs Based on Ambiguous Evidence". In CogSci 2018 (pp. 306–311). Madison Wisconsin, 25-28 July 2018. ISBN: 978-0-9911967-8-4. see also Blog Post
Fenton N.E. (2018), "Handling Uncertain Priors in Basic Bayesian Reasoning", July 2018, https://doi.org/10.13140/RG.2.2.16066.89280
Fenton N.E. (2018). On the Role of Statistics in Miscarriages of Justice. In 3rd Meeting of the All-Party Parliamentary Group on Miscarriages of Justice. House of Commons, London 25 June 2018. https://doi.org/10.13140/RG.2.2.22791.70567
Fenton N.E.., & Neil, M. (2018). "How Bayesian Networks are pioneering
the ‘smart data’ revolution", Open Access Government, July 2018 pages 22-23. pdf version Also available here.
Fenton N.E., & Neil, M. (2018). "Improving Software Testing with Causal Modelling". In R. Kennet, F. Ruggeri, & F. Faltin (Eds.), Analytic Methods in Systems and Software Testing (pp. 27–63). John Wiley & Sons Ltd. https://doi.org/10.1002/9781119357056.ch2
McLachlan, S., Potts, H., Dube, K., Buchanan, D., Lean, S., Gallagher, T., Johnson, O., Daley, B., Marsh, W., & Fenton N.E. (2018), "The Heimdall Framework for Supporting Characterisation of Learning Health Systems", BCS Journal of Innovation in Health Informatics, 25(2):77–87, http://dx.doi.org/10.14236/jhi.v25i2.996
Osman, M., Fenton N.E.., Pilditch, T., Lagnado, D. A., & Neil. M. (2018). "Who do we trust on social policy interventions". Basic and Applied Social Psychology, Vol 40 (5), 249-268 https://doi.org/10.1080/01973533.2018.1469986. Open access version pdf
McLachlan, S., Dube, K., Buchanan, D., Lean, S., Johnson, O., Potts, H., Gallagher, T,. Marsh, W., Fenton N.E. (2018). "Learning health systems: The research community awareness challenge". Journal of Innovation in Health Informatics, 25(1), 038-040 http://doi.org/10.14236/jhi.v25i1.981
Constantinou, A., Fenton N.E., "Things to know about Bayesian networks", Significance, 15(2), 19-23 https://doi.org/10.1111/j.1740-9713.2018.01126.x Full pdf also available here.
Fenton N.E. (2018) "Evidence based decision making turns knowledge into power", EU Research 'Beyond the Horizon' Magazine, Spring 2018, pp 38-39. PDF version here.
Yet, B., Constantinou, A., Fenton N.E.. & Neil, M. (2018) "Expected Value of Partial Perfect Information in Hybrid Models using Dynamic Discretization", IEEE Access, Vol 6, pp 7802-7817 https://doi.org/10.1109/ACCESS.2018.2799527. Full pdf version also available here
Yet B, Neil M, Fenton N.E., Dementiev E, Constantinou A. (2018), "An Improved Method for Solving Hybrid Influence Diagrams", International J Approx Reasoning, Vol 95, pp 93-112, https://doi.org/10.1016/j.ijar.2018.01.006, pdf preprint version available here
Fenton N.E., & Neil, M. (2018). Response to Nick Thieme's: "Statistic of the Year", not "Statistic of the Next Ten Years", 10.13140/RG.2.2.30958.72002
Fenton N.E., & Neil, M. (2018). "Lawnmowers versus terrorists: A highly misleading view of risk", Significance 15(1), 12-15. http://onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2018.01104.x/full Full pdf also available here
Fenton N.E., & Neil, M. (2018). "Criminally Incompetent Academic Misinterpretation of Criminal Data - and how the Media Pushed the Fake News", Open Access Report 10.13140/RG.2.2.32052.55680. .
Fenton N.E., & Neil, M. (2018). "Is decision-making using historical data alone more dangerous than lawnmowers?", Open Access Report here. Also available here.
Fenton N.E, & Neil, M. (2018). "Are lawnmowers a greater risk than terrorists?", Open Access Report here. Also available here.
Fenton N.E., Lagnado D, de Zoete, J, "Modeling complex legal cases as a Bayesian network (BN) using idioms and sensitivity analysis with the Collins case as a complete example", ICFIS2017 (10th International Conference on Forensic Inference and Statistics), Mineapolis, USA, Sept 2017. 10.13140/RG.2.2.35414.55360
de Zoete, J, Fenton N.E. ,"Automatic Generation of Bayesian networks in Forensic Science", ICFIS2017 (10th International Conference on Forensic Inference and Statistics), Mineapolis, USA, Sept 2017, 10.13140/RG.2.2.17798.47689
Constantinou, A., & Fenton, N.E (2017). "The future of the London Buy-To-Let property market: Simulation with Temporal Bayesian Networks". PLoS ONE 12(6): e0179297 doi.org/10.1371/journal.pone.0179297 (open access) 27 June 2017
Balding, D., Fenton, N. E., Gill, R., Lagnado, D. & Schneps, L. "Twelve Guiding Principles and Recommendations for Dealing with Quantitative Evidence in Criminal Law". (2017). Isaac Newton Institute Report INI 16061, http://www.newton.ac.uk/files/preprints/ni16061.pdf
Neil, M. & Fenton, N.E. "Risk Management Using Bayesian Networks" in Wiley StatsRef: Statistics Reference Online 1–6 (John Wiley & Sons, Ltd, 2017). doi:10.1002/9781118445112.stat07943
Fenton, N.E., Constantinou, A., & Neil, M. (2017). "Combining judgments with messy data to build Bayesian Network models for improved intelligence analysis and decision support". In Subjective Probability, Utility and Decision Making Conference (SPUDM 17). Haifa, Israel.
Fenton, N. E., Lagnado, D. A., Dahlman, C., & Neil, M. (2017). The Opportunity Prior: A Simple and Practical Solution to the Prior Probability Problem for Legal Cases. ICAIL '17 Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law, ACM, pp 69-76, 10.1145/3086512.3086519 Published by ACM. Pre-publication draft.
Constantinou, A. C. and Fenton, N.E. (2017). Towards Smart-Data: Improving predictive accuracy in long-term football team performance. Knowledge-Based Systems, Vol 124, pages 93-104, http://dx.doi.org/10.1016/j.knosys.2017.03.005 Open access pre-publication version. See blog posting.
Fenton NE, Neil M, Lagnado D, Marsh W, Yet B, Constantinou A, "How to model mutually exclusive events based on independent causal pathways in Bayesian network models", Knowledge-Based Systems, Dec 2016 Vol 113, pages 39-50. Gold access full version http://dx.doi.org/10.1016/j.knosys.2016.09.012 See also blog posting
Dementiev E and Fenton N E, "Bayesian Torrent Classification by File Name and Size Only", International Conference on Probabilistic Graphical Models, Lugano, Switzerland, 06 Sep 2016 - 09 Sep 2016. Journal of Machine Learning Research. 52: 136-147. 09 Sep 2016. Published version.
Constantinou A and Fenton NE. "Improving predictive accuracy using Smart-Data rather than Big-Data: A case study of soccer teams' evolving performance" In Proceedings of the 13th UAI Bayesian Modeling Applications Workshop (BMAW 2016), 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), New York City, USA, June 25-29, 2016. Published version
Zhou, Y., Fenton, N. E., Zhu, C. (2016), "An Empirical Study of Bayesian Network Parameter Learning with Monotonic Causality Constraints", Decision Support Systems Vol 87, pages 69-79. http://dx.doi.org/10.1016/j.dss.2016.05.001 pre-publication version here. See also blog posting
Yet, B., Constantinou, A. C., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016). A Bayesian Network Framework for Project Cost, Benefit and Risk Analysis with an Agricultural Development Case Study. Expert Systems with Applications, Volume 60 Oct 2016, pages 141-155 http://dx.doi.org/10.1016/j.eswa.2016.05.005 pre-publication version here See also blog posting
Fenton N.E, Neil M, Berger D, “Bayes and the Law”, Annual Review of Statistics and Its Application, Volume 3, 2016 (June), pp 51-77 http://dx.doi.org/10.1146/annurev-statistics-041715-033428 .Pre-publication version here and here is the Supplementary Material See also blog posting
Smit, N. M., Lagnado, D. A., Morgan, R. M., & Fenton, N. E. (2016). "Using Bayesian networks to guide the assessment of new evidence in an appeal case". Crime Science, 2016, 5: 9, DOI 10.1186/s40163-016-0057-6 (open source). Published version pdf. See also blog posting
Constantinou, A. C., Fenton, N.E, & Neil, M. (2016). Integrating expert knowledge with data in causal probabilistic networks: preserving the data-driven expectations when the expert variables remain unobserved. Expert Systems with Apllications, 56 pp 197-208, http://dx.doi.org/10.1016/j.eswa.2016.02.050. Pre-publication version.
Zhou, Y., Hospedales, T., Fenton, N. E. (2016), "When and where to transfer for Bayes net parameter learning", Expert Systems with Applications. 55, 361-373 http://dx.doi.org/10.1016/j.eswa.2016.02.011. See also blog posting
Constantinou, A. C., Fenton, N., Marsh, W., & Radlinski, L. (2016). "From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support", Artificial Intelligence in Medicine, 2016. Vol 67 pages 75-93. http://dx.doi.org/10.1016/j.artmed.2016.01.002, Pre-publication version here.
Constantinou, A. C., Yet, B., Fenton, N., Neil, M., & Marsh, W. (2016). Value of Information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences. Artificial Intelligence in Medicine. 66, pp 41-52 doi:10.1016/j.artmed.2015.09.002 Pre-publication version here.
Constantinou, A.C., Yet, B., Fenton, N.E., Neil, M., Marsh, D.W.R., 2015. What is the value of missing information when assessing decisions that involve actions for intervention? . Atlas Sci. 2015
Yet, B., Constantinou, A. C., Fenton, N., & Neil, M. (2015). Partial Expected Value of Perfect Information of Continuous Variables using Dynamic Discretisation. Under review, 2015
Fenton, N.E., 2015. Debunking report that claims gender diverse executive Boards outperform male-only Boards, Queen Mary University of London, Report Number BK_TR_05_15, http://dx.doi.org/10.13140/RG.2.1.1221.4160/1
Fenton NE, Neil M, Constantinou A (2015) "Simpson’s Paradox and the implications for medical trials". Working paper. Associared model.
Fenton NE, Neil M (2015), "Book Review: Malcom Kendrick “Doctoring Data: How to sort out medical advice from medical nonsense”. Download. Also http://dx.doi.org/10.13140/RG.2.1.4904.8804
Fenton NE, "Handling Anonymous Witness Evidence using Bayesian Network idioms" Working paper.
Shepherd, K., Hubbard, D., Fenton, N. E., Claxton, K., Luedeling, E., de Leeuw, J., (2015) "Development goals should enable decision-making", Nature 532: 152-154, 9 July 2015, http://dx.doi.org/10.1038/523152a
Constantinou, A., Freestone M., Marsh, W., Fenton, N. E. , Coid, J. (2015) "Risk assessment and risk management of violent reoffending among prisoners", Expert Systems With Applications 42 (21), 7511-7529. Pre-publication draft here. Published version: http://dx.doi.org/10.1016/j.eswa.2015.05.025
Zhou, Y., Fenton, N. E., Hospedales, T, & Neil, M. (2015). "Probabilistic Graphical Models Parameter Learning with Transferred Prior and Constraints", 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, 13-15 July 2015.
Yet, B., Constantinour A., Fenton N. E., Neil M., Leudeling E., Shepherd, K., "Project Cost, Benefit and Risk Analysis using Bayesian Networks", Bayesian Applications Workshop, 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, 16 July 2015. Published as abstract.
Chockler, H., Fenton N.E., Koeppens J., Lagnado, D. (2015), "Causal Analysis for Attributing Responsibility in Legal Cases", 15th International Conference on Artificial Intelligence & Law (ICAIL 2015), San Diego, June 8-12, 2015, pp 33-42, ACM ISBN 978-1-4503-3522-5. Open access version.
Fenton, N. E, "Another machine learning fable", March 2015
Fenton, N. E, "Moving from big data and machine learning to smart data and causal modelling: a simple example from consumer research and marketing", March 2015. DOI: http://dx.doi.org/10.13140/RG.2.1.3292.8166
de Zoete, J, Sjerps, M, Lagnado,D, Fenton, N.E. (2015), "Modelling crime linkage with Bayesian Networks" Law, Science & Justice, 55(3), 209-217. http://doi:10.1016/j.scijus.2014.11.005 Pre-publication draft here. Slides from ICFIS 2014 Presentation
Fenton, N. E. (2014). Assessing evidence and testing appropriate hypotheses. Science & Justice, 54(6), 502-504. Pre-publication draft. Published version: http://dx.doi.org/10.1016/j.scijus.2014.10.007
Lin, P., Neil, M. & Fenton, N. E. Risk Aggregation in the presence of Discrete Causally Connected Random Variables. Ann. Actuar. Sci. 8, 298–31 (2014). http://dx.doi.org/10.1017/S1748499514000098. Pre-publication draft here.
Fenton, N. E., & Neil, M. (2014). "Decision Support Software for Probabilistic Risk Assessment Using Bayesian Networks". IEEE Software, 31(2), 21–26. http://dx.doi.org/10.1109/MS.2014.32 Author's final version here.
Fenton, N.E, Lagnado, D., Hsu, A., Berger, D., & Neil, M. (2014). Response to “on the use of the likelihood ratio for forensic evaluation: response to Fenton et al.”. Science & Justice : Journal of the Forensic Science Society, 54(4), 319–20. doi:10.1016/j.scijus.2014.05.005
Constantinou, A. C., Fenton, N. E., & Pollock, L. (2014). Bayesian networks for unbiased assessment of referee bias in Association Football. Psychology of Sport & Exercise, 15(5) 538–547, http://dx.doi.org/10.1016/j.psychsport.2014.05.009. Pre-publication draft here.
Zhou, Y., Fenton, N. E., & Neil, M. (2014). An Extended MPL-C Model for Bayesian Network Parameter Learning with Exterior Constraints. In L. van der Gaag & A. J. Feelders (Eds.), Probabilistic Graphical Models: 7th European Workshop. PGM 2014, Utrecht. The Netherlands, September 17-19, 2014 (pp. 581–596). Springer Lecture Notes in AI 8754. Pre-publication draft here.
Fenton, N. E., Neil, M., & Hsu, A. (2014). "Calculating and understanding the value of any type of match evidence when there are potential testing errors". Artificial Intelligence and Law, 22. 1-28 . http://dx.doi.org/10.1007/s10506-013-9147-x Pre-publication draft here. Note that Table 2 is wrong in the published version. See change.
Fenton, N. E.(2014) "A Bayesian Network for a simple example of Drug Economics Decision Making", working paper DOI: http://10.13140/RG.2.1.1130.1281
Fenton, N. E., Neil, M. (2014) "Who put Bella in the wych elm? A Bayesian analysis of a 70 year-old mystery", Technical Report produced for BBC Radio 4 Programme Punt-PI, 2 August 2014
Lin, P., Neil, M., & Fenton, N. E. (2014). "Risk Aggregation in the presence of Discrete Causally Connected Random Variables". Annals of Actuarial Science, 8(2), 298-319, http://dx.doi.org/10.1017/S1748499514000098. Pre-publication draft here.
Fenton, N. E., D. Berger, D. Lagnado, M. Neil and A. Hsu, (2014). "When ‘neutral’ evidence still has probative value (with implications from the Barry George Case)", Science and Justice, 54(4), 274-287 http://dx.doi.org/10.1016/j.scijus.2013.07.002 (pre-publication draft here)
Zhou, Y., Fenton, N., & Neil, M. (2014). Bayesian network approach to multinomial parameter learning using data and expert judgments. International Journal of Approximate Reasoning, 55(5), 1252-1268 http://dx.doi.org/10.1016/j.ijar.2014.02.008
Yet, B., Perkins Z., Fenton, N.E., Tai, N., Marsh, W., (2014) "Not Just Data: A Method for Improving Prediction with Knowledge", Journal of Biomedical Informatics, Vol 48, 28-37 http://dx.doi.org/10.1016/j.jbi.2013.10.012 (see here for details of model)
Constantinou, Anthony C. & Fenton, N. E. (2013). Profiting from arbitrage and odds biases of the European football gambling market, Journal of Gambling Business and Economics, Vol. 7(2), 41-70. Journal link here. Pre-publication draft here.
Constantinou, A., N. E. Fenton and M. Neil (2013) "Profiting from an Inefficient Association Football Gambling Market: Prediction, Risk and Uncertainty Using Bayesian Networks". Knowledge-Based Systems. Vol 50, 60-86 http://dx.doi.org/10.1016/j.knosys.2013.05.008
Fenton, N. E., D. Lagnado and M. Neil (2013). "A General Structure for Legal Arguments Using Bayesian Networks." Cognitive Science 37, 61-102 http://dx.doi.org/10.1111/cogs.12004. Pre-publication version here.
Constantinou, A. C. and N. E. Fenton (2013). "Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries." Journal of Quantitative Analysis in Sports 9(1): 37-50. Pre-publication version http://dx.doi.org/10.1515/jqas-2012-0036
Lagnado, D. A., N. E. Fenton and M. Neil (2013). "Legal idioms: a framework for evidential reasoning." Argument and Computation, 2013, 4(1), 46-63 http://dx.doi.org/10.1080/19462166.2012.682656
Zhou, Y., Fenton, N. E., Neil, M., & Zhu, C. (2013). Incorporating Expert Judgement into Bayesian Network Machine Learning. In 23rd International Joint Conference on Artificial Intelligence (IJCAI2013) (pp. 3249–3250). China: AAAI Press.
Yun Zhou, Norman Fenton, Martin Neil, Cheng Zhu, "Incorporating Expert Judgement into Bayesian Network Machine Learning", 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), 2013
Fenton, N.E., Neil M, Lagnado, D, "Using soft evidence to model mutually exclusive causes in Bayesian networks", Technical Report, 2012
Constantinou, A., N. E. Fenton and M. Neil (2012). ""pi-football: A Bayesian network model for forecasting Association Football match outcomes." Knowledge Based Systems, 36, 322-339. Pre-publication version. http://dx.doi.org/10.1016/j.knosys.2012.07.008
Fenton NE, "A simple story illustrating why pure machine learning (without expert input) may be doomed to fail and totally unnecessary", 12 Nov 2012
Neil, M, Chen X, Fenton, N E, "Optimizing the Calculation of Conditional Probability Tables in Hybrid Bayesian Networks using Binary Factorization", IEEE Transactions on Knowledge and Data Engineering, 24(7), 1306 - 1312, 2012 http://dx.doi.org/10.1109/TKDE.2011.87
Fenton, N.E. and Neil, M.(2012), 'On limiting the use of Bayes in presenting forensic evidence', Extended draft available here.
Constantinou, A. , Fenton, N.E., "Solving the problem of inadequate scoring rules for assessing probabilistic football forecasting models", Journal of Quantitative Analysis in Sports, Vol. 8 (1), Article 1, 2012. http://dx.doi.org/10.1515/1559-0410.1418 Preprint draft here.
Fenton, N. E. (2011). "Science and law: Improve statistics in court." Nature 479: 36-37. Paper on Nature online website is here. http://dx.doi.
Fenton, N.E. and Neil, M. (2011), 'Avoiding Legal Fallacies in Practice Using Bayesian Networks', Australian Journal of Legal Philosophy 36, 114-151, 2011 ISSN 1440-4982 (extended preprint draft here).
Fenton, N.E. and Neil, M., 'The use of Bayes and causal modelling in decision making, uncertainty and risk', UPGRADE, the Journal of CEPIS (Council of European Professional Informatics Societies), 12(5), 10-21, 2011. Published verion here.
Yet, B., Perkins Z.,Marsh, W., Fenton, N.E., "Towards a Method of Building Causal Bayesian Networks for Prognostic Decision Support", ProBioMed 11, Bled, Slovenia, July 2011
Fenton, N. E. (2011). "Rational software developers as pathological code hackers" in The Dark Side of Software Engineering: Evil on Computing Projects. (Eds Rost, J. and Glass, R. L.), IEEE Computer Society Press, ISBN: 978-0-470-59717-0, pp 264-268
Fenton, N. and Neil, M. (2010). "Comparing risks of alternative medical diagnosis using Bayesian arguments." Journal of Biomedical Informatics, 43: 485-495, http://dx.doi.org/10.1016/j.jbi.2010.02.004
Xiangjun, Li and Fenton, N. E. "Applying Extended Support Vector Machines to Discover Temporal Periodic Patterns", Second Global Congress on Intelligent Systems (GCIS 2010), Wuhan, China 2010.
Neil, M., Marquez, D. and Fenton, N. E. (2010). "Improved Reliability Modeling using Bayesian Networks and Dynamic Discretization." Reliability Engineering & System Safety, 95(4), 412-425, http://dx.doi.org/10.1016/j.ress.2009.11.012
Fenton, N. E., Hearty, P., Neil, M. and Radliński, Ł. (2009). "Software Project and Quality Modelling Using Bayesian Networks Artificial Intelligence" in Applications for Improved Software Engineering Development: New Prospects. (Eds Meziane, F. and Vadera, S. Hershey), New York, USA, IGI Global: Chapter 1,1-25.
Fineman, M., Radlinski, L. and Fenton, N. E. (2009). Modelling Project Trade-off Using Bayesian Networks. IEEE Int. Conf. Computational Intelligence and Software Engineering. Wuhan, China, IEEE Computer Society. http://dx.doi.org/10.1109/CISE.2009.5364789
Fineman, M. and Fenton, N. E. (2009). Quantifying Risks Using Bayesian Networks. IASTED Int. Conf. Advances in Management Science and Risk Assessment (MSI 2009). Beijing, China, IASTED. 662-219, pp 1227-1233
Radliński, Ł. & Fenton, N., 2009. Causal Risk Framework for Software Projects. In Z. Wilimowska et al. Information Systems Architecture and Technology. IT Technologies in Knowledge Oriented Management Process. Wrocław, Poland: Oficyna Wydawnicza Politechniki Wrocławskiej, pp. 49-59.
Hearty, P., Fenton, N., Marquez, D., and Neil, M., Predicting Project Velocity in XP using a Learning Dynamic Bayesian Network Model. IEEE Trans Software Eng, 2009. 35(1): 124-137.
Fenton, N. E. (2009). Position Statement on the Role and Future of Search Based Software Engineering. 1st International Symposium on Search Based Software Engineering. Windsor, UK, IEEE Computer Society: xxii-xxiii.
Radliński Ł , Fenton N E, Neil M, Zarządzaniu II w, "A Learning Bayesian Net for Predicting Number of Software Defects Found in a Sequence of Testing",
Polish Journal of Environmental Studies 17 (3B), 359-364, 2008
Fenton, N.E. and Neil, M., Avoiding Legal Fallacies in Practice Using Bayesian Networks (Seventh International Conference on Forensic Inference and Statistics. 2008: Lausanne, Switzerland).
Fenton, N.E., Neil, M., and Marquez, D., Using Bayesian Networks to Predict Software Defects and Reliability. Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 2008. 222(O4): p. 701-712, 10.1243/1748006XJRR161
Fenton, N.E., Neil, M., Marsh, W., Hearty, P., Radlinski, L., and Krause, P., On the effectiveness of early life cycle defect prediction with Bayesian Nets. Empirical Software Engineering, 2008. 13: p. 499-537.
Marquez, D., Neil, M., and Fenton, N., Solving Dynamic Fault Trees using a New Hybrid Bayesian Network Inference Algorithm, in 16th Mediterranean Conference on Control and Automation (MOD 08). 2008: Ajaccio, Corsica, France, pp 609-614, http://dx.doi.org/10.1109/MED.2008.4602222
Marquez, D., Neil, M., and Fenton, N.E., Reliability Modelling Using Hybrid Bayesian Networks, in ISBIS-2008 International Symposium on Business and Industrial Statistics. 2008: Prague, Czech Republic.
Neil, M., Marquez, D., and Fenton, N., Using Bayesian Networks to Model the Operational Risk to Information Technology Infrastructure in Financial Institutions. Journal of Financial Transformation, 2008. 22: p. 131-138.
Neil, M., Tailor, M., Marquez, D., Fenton, N.E., and Hearty, P., Modelling dependable systems using hybrid Bayesian networks. Reliability Engineering and System Safety, 2008. 93(7): p. 933-939.
Radliński, Ł., Fenton, N.E., Neil, M., and Marquez, D., Improved Decision-Making for Software Managers Using Bayesian Networks, in 11th IASTED Int. Conf. Software Engineering and Applications (SEA). 2007: Cambridge, MA, USA p. 13–19.
Marquez D, Neil M, Fenton NE, "Improved Dynamic Fault Tree modelling using Bayesian Networks", The 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2007, Edinburgh 2007
Radliński, Ł., Fenton, N.E., Neil, M., and Marquez, D., Modelling Prior Productivity and Defect Rates in a Causal Model for Software Project Risk Assessment. Polish Journal of Environmental Studies, 2007. 16(4A): p. 256-260
Fenton NE, Neil M, Marsh W, Hearty P, Krause P, Radliński Ł. , "Project Data Incorporating Qualitative Factors for Improved Software Defect Prediction, ICSE PROMISE 2007 The dataset and model associated with this paper can be found here.
Fenton NE, Neil M, and Caballero JG, "Using Ranked nodes to model qualitative judgements in Bayesian Networks" IEEE TKDE 19(10), 1420-1432, Oct 2007
Fenton NE, Neil M, Hearty P, Marsh W, Marquez D, Krause P, Mishra R, "Predicting Software Defects in Varying Development Lifecycles using Bayesian Nets", Information & Software Technology, Vol 49, pp 32-43, Jan 2007
Fenton NE, "New Directions for Software Metrics", Keynote presentation, CIO Annual Symposium on Software Process Improvement, Savoy Hotel, London, 27 Sept 2006. Pictures from the event are here and here
Fenton NE "The Prosecutor's
invited video address for the Annual Conference of the
Society for Expert Witnesses, Studley Castle, Warwickshire, 6-7 October
2006 . Here
is a film
about legal reasoning in which
my (heavily edited) interview
contained (this is a Quick Time file of about 6Mb and my interview is
in the middle).
Norman Fenton, Łukasz Radliński, Martin Neil "Improved Bayesian Networks for Software Project Risk Assessment Using Dynamic Discretisation, IFIP Conference Software Engineering Techniques (SET 2006), Warsaw, Poland, 17-20 Oct 2006, in "Software Engineering Techniques: Design for Quality ", pp 139-148, Springer Boston, ISBN 978-0-387-39387-2, http://dx.doi.org/10.1007/978-0-387-39388-9_14
Joseph A, Fenton NE, Neil M, "Predicting football results using Bayesian Nets and other Machine Learning Techniques", Knowledge Based Systems, Volume 19, Issue 7, Pages 544-553, Nov 2006
Neil M, Marquez D, Fenton N, Tailor M, Hearty P, "Modelling Dependable Systems using Hybrid Bayesian Networks", First International Conference on Availability, Reliability and Security (ARES 2006), 20-22 April 2006, Vienna, Austria
Hearty P, Fenton NE, Neil M, Cates P, "Automated population of causal models for improved software risk assessment", 20th IEEE/ACM International Conference on Automated Software Engineering, Long Beach, California, USA, November 7-11, 2005, pp 433-435, ACM Press, ISBN: 1-59593-993-4
Neil M, Fenton N, "Improved Methods for building large-scale Bayesian Networks", The Third Bayesian Modeling Applications Workshop, Uncertainty in Artificial Intelligence (UAI) 2005, Edinburgh University, 26 July, 2005
Fenton NE and
Critique of Software Defect Prediction Models'', in Machine
Learning Applications in Software Engineering (eds: Zhang D, Tsai JJP),
pp 72-86, ISBN 981-256-094-7, World Scientific Publishing Co, 2005
Fenton NE, Marsh W, Neil M, Cates P, Forey S, Tailor T, "Making Resource Decisions for Software Projects", 26th International Conference on Software Engineering (ICSE 2004), May 2004, Edinburgh, United Kingdom. IEEE Computer Society 2004, ISBN 0-7695-2163-0, pp. 397-406
Neil M, Krause P, Fenton NE, "Software Quality Prediction Using Bayesian Networks" in Software Engineering with Computational Intelligence, (Ed Khoshgoftaar TM), Kluwer, ISBN 1-4020-7427-1, Chapter 6, 2003
Neil M, Fenton N, Forey S and Harris R. "Assessing Vehicle Reliability using Bayesian Networks" in Global Vehicle Reliability, Edited by J. E. Strutt and P.L. Hall. Professional Engineering Publishing, 25-42, 2003.
Fenton N, Krause P, Neil M, "Probabilistic Modelling for Software Quality Control", Journal of Applied Non-Classical Logics 12(2), 173-188, 2002
Fenton N, Krause P, Neil M, "Software Metrics: Uncertainty and Causal Modelling",. EuroSPI conference, Limerick Institute of Technology, Limerick, 10th-12th October 2001.
Fenton N, Krause P, Neil M, "Probabilistic Modelling for Software Quality Control", Sixth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty September 19-21, 2001, Toulouse, France.
Fenton NE and Neil M, ''Bayesian belief nets: a causal model for predicting defect rates and resource requirements'', Software Testing and Quality Engineering 2(1), 48-53, 2000
Fenton NE and Neil M, "Software Metrics: Roadmap", in 'The Future of Software Engineering' (Editor: Anthony Finkelstein) 22nd International Conference on Software Engineering, ACM Press ISBN 1-58113-253-0, pp.357-370, 2000
Littlewood B, Strigini L, Wright D, Fenton NE, Neil M, "Bayesian Belief Networks for Safety Assessment of Computer-based Systems", in System Performance Evaluation Methodologies and Applications (Ed: Gelenbe E), CRC Press, Boca Raton ISBN 0-8493-2357-6, pp 349-364, 2000
Fenton NE, ''Software Measurement Programs'', Software Testing & Quality Engineering 1(3), 40-46, 1999.
Fenton NE, ''Why most software quality metrics do not measure software quality'', Proc 2nd Annual SQI Symp. Austin. Texas, pp28-52, published by Software Quality Institute, the University of Texas at Austin, April, 1998.
Fenton NE, Littlewood B, Neil M, Strigini L, Sutcliffe A, Wright D, ''Assessing Dependability of Safety Critical Systems using Diverse Evidence'', IEE Proceedings Software Engineering, 145(1), 35-39, 1998.
Fenton NE, How to improve safety-critical standards, in 'Safer Systems' (Ed: Redmill F and Anderson T), Proc 5th Ann Safety Critical Systems Symp, pages 96-111, 1997.
Ohlsson N and Fenton NE, 'Experience with data collection in a large scale environment', Proc of 8th Internat Conf on Applications of Software Measurement, Atlanta, USA, October, 157-224, 1997.
Ohlsson N and Fenton NE, 'Let's start testing some basic software hypotheses!', Proc of Workshop on Empirical Studies of Software Maintenance (WESS 97), Monterey, Calif, Nov, 27-29, 1997.
Hall T and Fenton NE, Implementing effective software metrics programmes, IEEE Software, 14(2), 55-66, 1997.
Fenton NE, The role of measurement in software safety assessment, in 'Safety and Reliability of Software Based Systems' (Ed Shaw, R), Springer Verlag, 217-248, 1996.
Neil M and Fenton NE, Predicting software quality using Bayesian belief networks, Proc 21st Annual Software Eng Workshop, NASA Goddard Space Flight Centre, 217-230, Dec, 1996.
Neil M, Littlewood B, Fenton NE, Applying Bayesian belief networks to systems dependability assessment, in Proceedings of 4th Safety Critical Systems Symposium, Springer Verlag, 71-93, 1996.
Fenton NE, Critical burden of being correct, Times Higher Education, Sept 13, 1996.
Strigini L and Fenton NE, Rigorously assessing software reliability and safety, Proc Product Assurance Symposium and Software Product Assurance Workshop, 19-21 March 1996, ESA SP-377, May, 1996.
Fenton NE, Do standards improve product quality?, IEEE Software, 13(1), 22-24, Jan, 1996.
Hall T and Fenton NE 1996, Software quality programmes: a snapshot of theory versus reality, Software Quality J, 5(4), 235-242, 1996.
Finney K and Fenton NE, Evaluating the effectiveness of using Z: the claims made about CICS and where we go from here, J Systems Software, 35(3), 206-219, Dec 1996.
Kitchenham BA, Pfleeger SL, Fenton NE, Towards a framework for software measurement validation, IEEE Tans Software Eng 21(12), 929-944, 1995
Fenton NE, Directions and progress in software measurement, Software Reliability and Metrics Newsletter, Issue 17, 1995.
Fenton NE and Melton A, Measurement theory and software measurement, in 'Software Measurement' Ed: Melton A, International Thomson Computer Press, 27-37, 1995.
Hall T and Fenton NE, Software pracitioners and software quality improvement, 5th International Conference on Software Quality, (published by ASQC), Austin, Texas, 313-323, 1995.
Bieman JM, Fenton NE, Gustafson DA, Melton A, Ott LM, Fundamental issues in software measurement, in 'Software Measurement' Ed: Melton A, International Thomson Computer Press, 39-52, 1995.
Fenton NE, The empirical basis for software engineering, in 'Software Measurement' Ed: Melton A, International Thomson Computer Press,197-217, 1995.
Fenton NE, Pfleeger, SL, Glass B, "What's wrong with incremental development: a reply", IEEE Software 5(11), p8, 1994
Hall T, Fenton NE, "Implementing software metrics" 5th International Applied Software Measurement Conference, California, Nov 1994
Fenton NE, Software measurement: a necessary scientific basis, IEEE Transactions Software Engineering, 20 (3), 199-206, 1994.
Pfleeger SL, Fenton NE, Page P, Evaluating software engineering standards, IEEE Computer, Sept, 1994, 71-79, 1994.
Fenton NE, Pfleeger SL, Glass R, Science and Substance: A Challenge to Software Engineers, IEEE Software, 86-95, July, 1994.
Hall T and Fenton NE, Implementing software metrics - the critical success factors, Software Quality Journal 3 (4), 195-208, 1994.
Fenton NE, The effectiveness of software engineering methods, in Proc. AQuIS '93 (2nd Intl Conf on Achieving Quality in Software), 295-305, 1993.
Fenton NE, Objectives and context of measurement and experimentation, in Experimental Software Engineering Issues, (Ed: Rombach DH, Basili VR, Selby RW), Springer Verlag, pp 82-86, 1993.
Fenton NE, Pfleeger SL and Page S, Making your data match your measurement objectives, Proc 4th Intl Conf on Applications of Software Measurement (ASM93) 696-723, 1993.
Fenton NE and Page S, Towards the evaluation of software engineering standards, Proc. Software Engineering Standards Symposium (SESS 93) IEEE Computer Society Press, pp 100--107, 1993.
Fenton NE, Littlewood B, and Page S, Evaluating software engineering standards and methods, in Software Engineering: A European Perspective (Ed: Thayer R, McGettrick AD), IEEE Computer Society Press, pp 463--470, 1993.
Devine C, Fenton NE, Page S, Deficiencies in existing software engineering standards as exposed by SMARTIE, in Safety Critical Systems, (Ed: Redmill F and Anderson T), Chapman and Hall, pp.255--272, 1993.
Fenton NE, Page S, and Devine C, Software engineering standards: evaluation and improvements, Proceedings of the DTI-JFIT Conference, 1993.
Fenton NE, "How effective are software engineering methods?", J Systems Software 20, 93-100, 1993.
Littlewood B, Brocklehurst S, Fenton NE, Mellor P, Page S, Wright D, Dobson, Towards operational measures of security, J Computer Security 2, 211-229, 1993.
Fenton NE , Software measurement: why a formal approach?, in 'Formal Aspects of Software Measurement' (Ed:Denvir, T, Herman R, Whitty RW), Springer Verlag, pp.3--27, 1992.
Bieman J, Fenton NE, Gustafson D, Melton A, Whitty RW, Moving from philosophy to practice in software measurement, in 'Formal Aspects of Software Measurement' (Ed::Denvir, T, Herman R, Whitty R), 1992.
Fenton NE and Kitchenham BA, Validating software measures, J Software Testing, Verification & Reliability 1(2), 27-42, 1991.
Fenton NE, The mathematics of complexity in computing and software engineering, in The Mathematical Revolution inspired by Computing, (Eds. Johnson JH, Loomes M), Oxford University Press, 243-256, 1991.
Fenton NE and Whitty RW, Program structures: some new characterizations, J Computer and System Sciences, 43(3), 467-483, 1991.
Fenton NE and Melton A, Deriving structurally based software measures, J Systems Software 12, 177-187, 1990
Fenton NE, Software measurement: theory, tools and validation, Software Eng J, Vol 5 (1), 65-78, 1990.
Bush M, Fenton NE, Software measurement: a conceptual framework, J Systems Software, Vol 12, 223-231, July, 1990.
Baker AL, Bieman JM, Fenton NE, Gustafson D, Melton A, A philosophy for software measurement, J Systems Software, Vol 12 , 277-281, July, 1990.
Fenton NE and Mole D, A note on the use of Z for flowgraph decomposition, J Information & Software Tech,Vol 30 (7), 432-437, 1988.
Fenton NE and Kaposi AA, Metrics and software structure, J. Information & Software Tech, 301-320, July, 1987.
Fenton NE and Whitty RW, Axiomatic approach to software metrication through program decomposition, Computer J, 29(4), 329-339, 1986.
Whitty RW, Fenton NE, Kaposi AA, Structured programming: a tutorial guide, IEE Software and Microsystems3(3), 54-65, 1985.
Whitty RW, Fenton NE, Kaposi AA,, A rigorous approach to structural analysis and metrication of software, IEE Software and Microsystems 4(1), 2-16, 1985.
Whitty RW, Fenton NE, An axiomatic approach to systems complexity, in Pergamon InfotechState-of-the-art reports: Designing for systems maturity PergamonInfotech Ltd., 113-137, 1985.
Fenton NE, Whitty RW and Kaposi AA, A generalised mathematical theory of structured programming, Theor Comp Sci, 36, 145-171, 1985.
Fenton NE, The structural complexity of flowgraphs, in Graph Theory and its applications to Algorithms and Computer Science Wiley, New York, 273-282, 1985.
Fenton NE, Representations of projective geometries, European J. Combinatorics (5), 123-126, 1984.
Fenton NE, Characterisation of Atomic Matroids, Quart. J. Math. Oxford 34(2), 49-60, 1983. 10.1093/qmath/34.1.49
Fenton NE, Vamos P, Matroid interpretation of maximal k-arcs in projective spaces, Rend. di Matematica 3 (2), Serie VII, 573-580, 1982.
On-line publications (software metrics)
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