Professor Martin Shepperd

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Head of Computer Science
Professor in Software Technologies and Modelling

Room: St John's 023b
Brunel University
Uxbridge
UB8 3PH
United Kingdom
Tel: +44 (0)1895 267188
Fax: +44 (0)1895 251686
Email: martin.shepperd@brunel.ac.uk

Web: Personal Website
Web: ResearcherID Profile
Web: Google Scholar Profile

Summary

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.

Research and Teaching

Research Interests

Software engineering, empirical research, cost modelling and prediction, machine learning (including case-based reasoning, metaheuristics, rule induction algorithms and Grey relational algebra), data imputation and noise handling.

University Research Centre Membership

Centre for Software and Systems

Current Research

Presently I’m interested in the impact of bias amongst computer scientists when conducting and reporting computational experiments. A meta-analysis conducted with Tracy Hall and David Bowes (Univ. of Hertfordshire) of 600 experimental results from studies exploring how we can induce classifiers to predict whether software will be faulty or not shows that who does the work is 25x more influential than what algorithms are deployed. This will be shortly published in IEEE TSE as "Researcher Bias: The Use of Machine Learning in Software Defect Prediction”.

I’m also working on a project with cognitive psychologists to experimentally investigate the various biases software professionals are vulnerable to when making predictions. Most noteworthy is the impact of the anchoring bias.

Teaching

Advanced topics in computer science (Level 3 undergraduate)
Research methods (doctoral students)

Research Supervision

Boyce Sigweni (Started 2013)

Boyce is exploring the use of metaheuristic search to find effective feature spaces for case-based reasoners. This will be accomplished by searching for feature weights and applying wrapper techniques. It will be an extension of:

[1] C. Kirsopp, M. J. Shepperd, and J. Hart, "Search heuristics, case-based reasoning and software project effort prediction," in GECCO 2002: Genetic and Evolutionary Computation Conf., New York, 2002.

[2]C. Kirsopp and M. J. Shepperd, "Case and feature subset selection for CBR-based software project effort prediction," in 22nd SGAI Intl. Conf. on Knowledge Based Systems & Applied Artificial Intelligence, Cambridge, UK, 2002.

We are working in the problem domain of software project effort prediction.

Activities

I am General Chair of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE 2014)

Publications

Publications

Journal Papers

(2013) Hassan, AE., Hindle, A., Runeson, P., Shepperd, M., Devanbu, P. and Kim, S., Roundtable: What's Next in Software Analytics, IEEE SOFTWARE 30 (4) : 53- 56

(2013) Shepperd, M., Song, Q., Sun, Z. and Mair, C., Data quality: Some comments on the NASA software defect datasets, IEEE Transactions on Software Engineering 39 (9) : 1208- 1215

(2013) Shepperd, M. and Shull, F., Guest Editorial for Special Section from Empirical Software Engineering & Measurement (ESEM) 2011, Information and Software Technology

(2012) Shepperd, M. and MacDonell, S., Evaluating prediction systems in software project estimation, Information and Software Technology 54 (8) : 820- 827 Download publication

(2012) Menzies, T. and Shepperd, M., Special issue on repeatable results in software engineering prediction, Empirical Software Engineering 17 (1-2) : 1- 17

(2011) Song, Q. and Shepperd, M., Predicting software project effort: a grey relational analysis based method, Expert Systems with Applications: An International Journal 38 (6) : 7302- 7316

(2011) Song, QB., Jia, ZH., Shepperd, M., Ying, S. and Liu, J., A general software defect-proneness prediction framework, IEEE Transactions on Software Engineering 37 (3) : 356- 370

(2011) Menzies, T. and Shepperd, M., Special issue on repeatable results in software engineering prediction, Empirical Software Engineering 1- 17

(2010) MacDonell, S., Shepperd, M., Kitchenham, B. and Mendes, E., How reliable are systematic reviews in empirical software engineering?, IEEE Transactions on Software Engineering 36 (5) : 676- 687 Download publication

(2010) Nasseri, E., Counsell, S. and Shepperd, M., Class movement and re-location: an empirical study of Java inheritance evolution, Journal of Systems and Software 83 (2) : 303- 315

(2009) Wang, Y., Song, Q., MacDonell, S., Shepperd, M. and Shen, J., Integrate the GM(1,1) and Verhulst models to predict software stage-effort, IEEE Transactions on Systems, Man and Cybernetics - Part C 39 (6) : 647- 658

(2009) Jayal, A. and Shepperd, M., The problem of labels in e-assessment of diagrams, Journal on Educational Resources in Computing (JERIC) 8 (4) : 12 Download publication

(2008) Song, Q., Shepperd, M., Chen, X. and Liu, J., Can k-NN imputation improve the performance of C4.5 with small software project data sets? a comparative evaluation, Journal of Systems and Software 81 (12) : 2361- 2370 Download publication

(2007) Song, Q. and Shepperd, M., Missing data imputation techniques, International Journal of Business Intelligence and Data Mining 2 (3) : 261- 291

(2007) Song, Q. and Shepperd, M., A new imputation method for small software project data sets, Journal of Systems and Software 80 (1) : 51- 62

(2007) Jorgensen, M. and Shepperd, M., A systematic review of software development cost estimation studies, IEEE Transactions on Software Engineering 33 (1) : 33- 53 Download publication

(2006) Song, Q., Shepperd, M., Cartwright, M. and Mair, C., Software defect association mining and defect correction effort prediction, IEEE Transactions on Software Engineering 32 (2) : 69- 82 Download publication

(2006) Song, Q. and Shepperd, M., Mining web browsing patterns for E-commerce, Computers in Industry 57 (7) : 622- 630

(2005) Shepperd, M. and Cartwright, M., A replication of the use of regression towards the mean (R2M) as an adjustment to effort estimation models, Proceedings - International Software Metrics Symposium 2005 351- 360

(2005) Song, Q., Shepperd, MJ. and Cartwright, M., A short note on safest default missingness mechanism assumptions, Empirical Software Engineering 10 (2) : 235- 243

(2005) Myrtveit, I., Stensrud, E. and Shepperd, MJ., Reliability and validity in comparative studies of software prediction models, IEEE Transactions on Software Engineering 31 (5) : 380- 391 Download publication

(2004) Deligiannis, I., Stamelos, I., Angelis, L., Roumeliotis, M. and Shepperd, M., A controlled experiment investigation of an object-oriented design heuristic for maintainability, Journal of Systems and Software 72 (2) : 129- 143

(2003) Deligiannis, I., Shepperd, M., Roumeliotis, M. and Stamelos, I., An empirical investigation of an object-oriented design heuristic for maintainability, Journal of Systems and Software 65 (2) : 127- 139

(2003) MacDonell, SG. and Shepperd, MJ., Combining techniques to optimize effort predictions in software project management, Journal of Systems and Software 66 (2) : 91- 98

(2003) Clarke, J., Dolado, JJ., Harman, M., Hierons, RM., Jones, B., Lumkin, M., Mitchell, B., Mancoridis, S., Rees, K., Roper, M. and Shepperd, M., Reformulating software engineering as a search problem, IEE Proceedings - Software 150 (3) : 161- 175 Download publication

(2002) Deligiannis, IS., Shepperd, M., Webster, S. and Roumeliotis, M., A review of experimental investigations into object-oriented technology, Empirical Software Engineering 7 (3) : 193- 231

(2002) Kirsopp, C. and Shepperd, M., Making inferences with small numbers of training sets, IEE Proceedings - Software 149 (5) : 123- 130 Download publication

(2001) Shepperd, M. and Kadoda, G., Comparing software prediction techniques using simulation, IEEE Transactions on Software Engineering 27 (11) : 1014- 1022 Download publication

(2001) Cartwright, M. and Shepperd, M., Predicting with sparse data, IEEE Transactions on Software Engineering 27 (11) : 987- 998 Download publication

(2001) Shepperd, MJ. and Cartwright, M., Predicting with sparse data, IEEE Transactions on Software Engineering 27 (11) : 1014- 1022

(2001) Kitchenham, BA., Pickard, LM., MacDonnell, SG. and Shepperd, MJ., What accuracy statistics really measure, IEE Proceedings - Software Engineering 148 (3) : 81- 85 Download publication

(2000) Cartwright, M. and Shepperd, MJ., An empirical investigation of an object-oriented software system, IEEE Trans. on Softw. Eng. 26 (8) : 786- 796 Download publication

(2000) Mair, C., Kadoda, G., Lefley, M., Phalp, K., Schofield, C., Shepperd, M. and Webster, S., An investigation of machine learning based prediction systems, J. of Systems Software 53 (1) : 23- 29

Conference Papers

(2012) Shepperd, M., The scientific basis for prediction research, PROMISE'12, the 8th International Conference on Predictive Models in Software Engineering, ACM International Conference Proceeding Series

(2011) Shepperd, M., Data quality: Cinderella at the software metrics ball?, 2nd International Workshop on Emerging Trends in Software Metrics (WeTSOM 2011)

(2011) Mair, C. and Shepperd, M., Human judgement and software metrics: vision for the future, 2nd international workshop on emerging trends in software metrics (WETSoM'11)

(2011) Shepperd, M., Group project work from the outset: an in-depth teaching experience report, , 2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011 - Proceedings 361- 370

(2010) MacDonell, SG. and Shepperd, M., Data accumulation and software effort prediction, 4th International Symposium on Empirical Software Engineering and Measurement (ESEM 2010)

(2009) Mair, C., Martincova, M. and Shepperd, M., A literature review of expert problem solving using analogy, 13th International Conference on Evaluation and Assessment in Software Engineering (EASE) Download publication

(2008) Liebchen, G. and Shepperd, M., Data sets and data quality in software engineering, PROMISE 2008 Download publication

(2007) MacDonell, S. and Shepperd, MJ., Comparing local and global software effort estimation models – reflections on a systematic review, 1st International Symposium on Empirical Software Engineering and Measurement

(2007) Liebchen, G., Twala, B., Shepperd, MJ., Cartwright, M. and Stephens, M., Filtering, robust filtering, polishing techniques for addressing quality in software data, 1st International Symposium on Empirical Software Engineering and Measurement

(2007) Shepperd, MJ., Software project economics: a roadmap, International Conference on Software Engineering 2007: Future of Software Engineering Download publication

(2006) Nasseri, E., Counsell, S. and Shepperd, MJ., An empirical study of evolution of inheritance in Java OSS, International Symposium on Empirical Software Engineering 2006 Download publication

(2006) Cartwright, M., Shepperd, M. and Twala, B., Ensemble of missing data techniques to improve software prediction accuracy, , 28th International Conference on Software Engineering (ICSE 2006), 20-28 May 2006, Shanghai, China 4-

(2006) Mair, C. and Shepperd, M., Looking at comparisons of regression and analogy-based software project cost prediction, Software Engineering Research and Practice

(2005) Shepperd, M. and Cartwright, M., A replication of the use of regression towards the mean (R2M) as an adjustment to effort estimation models, 11th International Symposium on Software Metrics

(2005) Mair, C., Shepperd, M. and Jørgensen, M., An analysis of data sets used to train and validate cost prediction systems, PROMISE 2005

(2005) Premraj, R., Shepperd, M., Kitchenham, B. and Forselius, P., An empirical analysis of software productivity over time, 11th IEEE International Software Metrics Symposium (Metrics05)

(2005) Twala, B., Cartwright, M. and Shepperd, M., Comparison of various methods for handling incomplete data in software engineering databases, 4th International Symposium on Empirical Software Engineering

(2005) Shepperd, M., Evaluating software project prediction systems, 11th International Symposium on Software Metrics

(2005) Liebchen, GA. and Shepperd, M., Software productivity analysis of a large data set and issues of confidentiality and data quality, 11th International Symposium on Software Metrics

(2005) Mair, C. and Shepperd, MJ., The consistency of empirical comparisons of regression and analogy-based software project cost prediction, 4th International Symposium on Empirical Software Engineering (ISESE) Download publication

(2005) Song, Q., Shepperd, M. and Mair, C., Using grey relational analysis to predict software effort with small data sets, 11th IEEE International Software Metrics Symposium (Metrics05)

(2004) Hart, J. and Shepperd, M., The Evolution of Concurrent Control Software Using Genetic Programming, , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (3003) : 289- 298

(2003) Kirsopp, C., Mendes, E., Premraj, R. and Shepperd, M., An empirical analysis of linear adaptation techniques for case-based prediction, 5th International Conference on Case-Based Reasoning, Lecture Notes in Artificial Intelligence (2689) : 231- 245 Download publication

(2003) Passing, U. and Shepperd, M., An experiment on software project size and effort estimation, ACM-IEEE International Symposium on Empirical Software Engineering (ISESE 2003)

(2003) Cartwright, M., Shepperd, M. and Song, Q., Dealing with missing software project data, 9th IEEE International Metrics Symposium

(2003) Lefley, M. and Shepperd, M., Using genetic programming to improve software effort estimation based on general data sets, GECCO 2003

(2003) MacDonell, S. and Shepperd, M., Using prior-phase effort records for re-estimation during software projects, 9th IEEE Intl. Metrics Symp.

(2002) Kirsopp, C. and Shepperd, MJ., Case and feature subset selection for CBR-based software project effort prediction, 22nd SGAI Intl. Conf. on Knowledge Based Systems & Applied Artificial Intelligence

(2002) Kirsopp, C. and Shepperd, MJ., Making inferences with small numbers of training sets, Intl. Conf. on Empirical Assessment of Software Engineering

(2002) Kirsopp, C., Shepperd, MJ. and Hart, J., Search heuristics, case-based reasoning and software project effort prediction, Genetic and Evolutionary Computation Conference (GECCO 2002) Download publication

(2001) Shepperd, M. and Kadoda, G., Using simulation to evaluate prediction techniques [for software], METRICS 2001, Proceedings of the Seventh International Software Metrics Symposium 349- 359

(2001) Shepperd, MJ. and Kadoda, G., Using simulation to evaluate prediction techniques, 7th IEEE Intl. Metrics Symp.

(2011) Mair, C., Martincova, M. and Shepperd, M., An empirical study of software project managers using a case-based reasoner, , Proceedings of the Annual Hawaii International Conference on System Sciences 1030- 1039

(2006) Twala, B., Cartwright, M. and Shepperd, M., Ensemble of missing data techniques to improve software prediction accuracy, , Proceedings - International Conference on Software Engineering (2006) : 909- 912

(2005) Twala, B., Cartwright, M. and Shepperd, M., Comparison of various methods for handling incomplete data in software engineering databases, , 2005 International Symposium on Empirical Software Engineering, ISESE 2005 105- 114

Book Chapters

(2007) Twala, B., Cartwright, M. and Shepperd, M., Applying rule induction in software prediction. In: Zhang, H. and Tsai, J. eds. Advances in machine learning applications in software engineering. Hershey, PA : Idea Group Publishing 265- 286

(2003) Shepperd, MJ., Case-based reasoning and software engineering. In: Aurum, A., Jeffrey, R., Wohlin, C. and Handzic, M. eds. Managing Software Engineering Knowledge. New York : Springer 181- 198 Download publication

(2003) Mair, C., Shepperd, MJ., Cartwright, M., Kirsopp, C. and Heathcote, D., Understanding object feature binding through experimentation and modelling. In: Progress in Neural Processing - Proceedings of the Eighth Neural Computation and Psychology Workshop. 295- 305

(2001) Kadoda, G., Cartwright, M. and Shepperd, M., Issues on the effective use of CBR technology for software project prediction. In: Case-Based Reasoning Research and Development, Proceedings. Berlin : Springer-Verlag 276- 290

Page last updated: Tuesday 13 May 2014