astronomy

Norman Fenton

Norman Fenton is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Norman Fenton rather than just read about it. In short: Norman Elliott Fenton (born 18 May 1956) is a British mathematician and computer scientist. He is the Professor of Risk Information Management in the School of Electronic Engineering and Computer Science at Queen Mary University of London.

Key takeaways

Norman Fenton belongs to astronomy; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Norman Fenton to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Norman Fenton from memory before moving on to harder problems.

Reference excerpt

Norman Elliott Fenton (born 18 May 1956) is a British mathematician and computer scientist. He is the Professor of Risk Information Management in the School of Electronic Engineering and Computer Science at Queen Mary University of London. He is known for his work in software metrics and is the author of the textbook Software Metrics: A Rigorous Approach, as of 2014 in its third edition.

Education Fenton received his bachelor's degree in mathematics from the London School of Economics in 1978. He earned his Master of Science in 1978 and Doctor of Philosophy in 1981 at the University of Sheffield. At Sheffield he was the second research student of Peter Vámos. His doctoral thesis was "Representations of Matroids".

Career Fenton was a postdoctoral fellow in the mathematics department at University College Dublin from 1981 to 1982 and the Mathematics Institute of the University of Oxford from 1982 to 1984. At the end of that period he changed fields and began publishing papers on structured programming with Robin W. Whitty and Agnes A. Kaposi. In 1984, he joined the department of Electrical and Electronic Engineering at South Bank Polytechnic in London where he headed the Centre for Software and Systems Engineering research group. He began to publish on software metrics as well as program structure. In 1989, Fenton moved to City University as a reader in software reliability, and became a professor of Computing Science in 1992. In 1998, Fenton, along with Martin Neil and Ed Tranham, set up the company Agena Ltd in Cambridge. Fenton was CEO between 1998 and 2015 and remains a director. In 2000, Fenton joined Queen Mary University of London (School of Electronic Engineering and Computer Science) where he works part–time as a professor. He is the director of the Risk and Information Management Research Group. In August 2025, he joined the policy college of Advance UK.

Selected publications Textbooks Fenton, Norman E. (1991). Software Metrics: A Rigorous Approach. Chapman & Hall. ISBN 978-0-412-40440-5. OCLC 1069086327. Fenton, Norman E.; Pfleeger, Shari Lawrence (1997). Software Metrics: A Rigorous and Practical Approach (2 ed.). International Thomson Computer Press. ISBN 978-0-534-95600-4. OCLC 1055171425. Fenton, Norman; Bieman, James (1 October 2014). Software Metrics: A Rigorous and Practical Approach (3 ed.). Taylor & Francis. ISBN 978-1-4398-3822-8. OCLC 491888703. Fenton, Norman; Neil, Martin (3 September 2018). Risk Assessment and Decision Analysis with Bayesian Networks (2 ed.). CRC Press, Taylor & Francis Group. ISBN 978-1-138-03511-9. OCLC 1031043793. Fenton, N.E. and M. Neil, Fighting Goliath: Exposing the flawed science and statistics behind the COVID-19 event. 2024 Sovereign Rights Publishing, ISBN 978-1-0687498-3-4, 2024 Articles Fenton, N. (1994). "Software measurement: a necessary scientific basis". IEEE Transactions on Software Engineering. 20 (3): 199–206. doi:10.1109/32.268921. Fenton, N.; Pfleeger, S.L.; Glass, R.L. (1994). "Science and substance: a challenge to software engineers". IEEE Software. 11 (4): 86–95. doi:10.1109/52.300094. S2CID 8528640. Kitchenham, B.; Pfleeger, S.L.; Fenton, N. (1995). "Towards a framework for software measurement validation". IEEE Transactions on Software Engineering. 21 (12): 929–944. doi:10.1109/32.489070. Fenton, N.E.; Neil, M. (1999). "A critique of software defect prediction models". IEEE Transactions on Software Engineering. 25 (5): 675–689. doi:10.1109/32.815326. Fenton, Norman E; Neil, Martin (1999). "Software metrics: successes, failures and new directions". Journal of Systems and Software. 47 (2–3): 149–157. doi:10.1016/S0164-1212(99)00035-7. Fenton, N.E.; Ohlsson, N. (2000). "Quantitative analysis of faults and failures in a complex software system". IEEE Transactions on Software Engineering. 26 (8): 797–814. doi:10.1109/32.879815. Fenton, Norman E.; Neil, Martin (2000). Software metrics: Roadmap. ICSE '00: Proceedings of the Conference on The Future of Software Engineering May 2000. pp. 357–370. doi:10.1145/336512.336588. Neil, Martin; Fenton, Norman; Nielson, Lars (2000). "Building large-scale Bayesian networks". The Knowledge Engineering Review. 15 (3): 257–284. doi:10.1017/S0269888900003039. S2CID 11309502. Fenton, Norman; Neil, Martin; Marsh, William; Hearty, Peter; Marquez, David; Krause, Paul; Mishra, Rajat (2007). "Predicting software defects in varying development lifecycles using Bayesian nets". Information and Software Technology. 49 (1): 32–43. doi:10.1016/j.infsof.2006.09.001.

References

External links Faculty website Norman Fenton publications indexed by Google Scholar

Illustrations

Worked examples

Example 1 — a first encounter with Norman Fenton

Start with the simplest possible case. Write down what Norman Fenton claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Norman Fenton before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Norman Fenton ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Norman Fenton

In research: Norman Fenton appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Norman Fenton in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Norman Fenton is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1956 births, Academics of City, University of London, Academics of London South Bank University, so understanding it makes those chapters shorter.
In everyday life: Look for Norman Fenton outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Norman Fenton in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Norman Fenton means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Norman Fenton out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Norman Fenton in simple terms?

Why does Norman Fenton matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Norman Fenton?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Norman Fenton.