Professor Martin Shepperd
Professor - Software Tech & Modelling
Wilfred Brown Building 114
- Email: email@example.com
- Tel: +44 (0)1895 267188
Martin Shepperd received a PhD in computer science from the Open University in 1991 for his work in measurement theory, many sorted algebras and their application to empirical software engineering. He was seconded to the Parliamentary Office of Science & Technology. Presently he is Head of Department and holds the chair of Software Technology and Modelling at Brunel University London, UK. He has published more than 150 refereed papers and three books in the areas of software engineering and machine learning.
He is a fellow of the British Computer Society.
Previously Martin has worked as a software developer for HSBC.
I am General Chair of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE 2014).
I was General Chair of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE 2014)
I am Associate Editor of Empirical Software Engineering: An international Journal and on the Editorial Boards of Information & Software Technology and e-Informatica Software Engineering Journal.
Newest selected publications
Shepperd, M. and Yousefi, L. (2022) 'An analysis of retracted papers in Computer Science'. arXiv.Open Access Link
Gren, L. and Shepperd, M. (2022) 'Problem reports and team maturity in agile automotive software development'. Proceedings - 15th International Conference on Cooperative and Human Aspects of Software Engineering, CHASE 2022. pp. 41 - 45.
Yao, J. and Shepperd, M. (2021) 'The impact of using biased performance metrics on software defect prediction research'. Information and Software Technology, 139. pp. 106664 - 106664. ISSN: 0950-5849
Margoni, F. and Shepperd, M. (2020) 'Changing the logic of replication: A case from infant studies'. Infant Behavior and Development, 61. pp. 101483 - 101483. ISSN: 0163-6383 Open Access Link
Yao, J. and Shepperd, M. (2020) 'Assessing Software Defection Prediction Performance: Why Using the Matthews Correlation Coefficient Matters'.24th ACM International Conference on Evaluation and Assessment in Software Engineering (EASE). Trondheim. 15 - 17 April. ACM. pp. 120 - 129.Open Access Link