MCom(Otago), PhD(Cantab), MIITP
Professor
Room 8.13, Otago Business School
Tel +64 3 479 5032
Email stephen.macdonell@otago.ac.nz
Research Gate Stephen_MacDonell
Google Scholar Stephen G MacDonell
Background and interests
I hold a part-time appointment as Professor in Information Science at the University of Otago in Dunedin, New Zealand. I was awarded BCom(Hons) and MCom degrees from the University of Otago and a PhD from the University of Cambridge. My research has been published in IEEE Transactions on Software Engineering, ACM Transactions on Software Engineering and Methodology, ACM Computing Surveys, Empirical Software Engineering, Information & Management, the Journal of Systems and Software, Information and Software Technology, and the Project Management Journal, and I have presented my research findings at numerous international conferences.
I am a Fellow of IT Professionals NZ, Senior Member of the IEEE and the IEEE Computer Society, Member of the ACM, and I serve on the Editorial Board of Information and Software Technology.
I am also Theme Leader for IT, Data Analytics and Modelling in New Zealand’s National Science Challenge Science for Technological Innovation.
Research
I am a researcher of behavioural software engineering – my aim is to better understand and improve how we build and deploy software-intensive systems. My research is focused on four related aspects of empirical software engineering: teams, practices, analytics, and evidence. I use statistical, machine-learning and knowledge-based methods to model aspects of software practices, processes and projects, often in conjunction with expert-judgment approaches. My research on software processes and projects has attracted significant external funding, supporting the work of numerous postdoctoral researchers and postgraduate students.
See also my google scholar entry and my ResearchGate page (link above).
I am also part of the research group:
Information Systems and Software Engineering
International collaborative projects
China:
College of Information Science and Engineering, Ocean University of China, Phase-based Software Forecasting, 2017 to present
Hong Kong:
Department of Computer Science, City University of Hong Kong, Time-aware Software Effort Prediction, 2017 to present
Multi-national:
HELENA SURVEY - Hybrid dEveLopmENt Approaches in software systems development, 2016 to present
Germany:
Process Engineering Group, Fraunhofer Institute for Experimental Software Engineering, Evidence and Agile Practices, 2016 to present
United Kingdom:
School of Information Systems, Computing & Mathematics, Brunel University, Software Engineering Data Quality, Model Quality, and Sensitivity Analysis, 2008 to present
Supervision
I have supervised through to completion 26 Doctoral students and 21 Master's thesis students. I am always keen to hear from top students who are interested in undertaking postgraduate study, for PhD and Master's degrees. Before making contact with me please read and consider these two documents:
- Research Wish List (PDF)
- Postgraduate Supervision (PDF)
Currently co-supervising
- Chathrie Wimalasooriya
- Pascal Omondiagbe
Grants and awards
Research grants
- 2014, Ministry of Health (MOH0044) Review of antidote, antitoxin and antivenom stocks, $50,000 (PI)
- 2007-2012, Foundation for Research, Science and Technology – Research for Industry (PROJ-12552-NMTS-UOAX0712), Software process and product improvement, $840,000 p.a., 1.10.07-30.09.12 (with Profs. John Grundy and John Hosking, University of Auckland NZ, and others) (Co-PI)
- 2010-2011, Foundation for Research, Science and Technology Pre-Seed Tech Jumpstart, FuzzyManager II, $10,000 (PI)
Research awards and distinctions
- Best Paper Award (with S. Mensah, J. Keung, M.F. Bosu and K.E. Bennin), International Conference on Software Quality, Reliability and Security, 2017
- Best Paper Award (with B. Raza and T. Clear), 8th International Conference on Evaluation of Novel Approaches to Software Engineering, 2013
- Best Research Paper Award (with M.F. Bosu), 22nd Australasian Software Engineering Conference, 2013
- Best Short Paper Award (with M. Shepperd), 4th International Symposium on Empirical Software Engineering and Measurement, 2010
Teaching and Learning Grants
- Recipient of a SCIENCES Teaching and Learning Development Grant (University of Otago) to enable the development of animations to be incorporated in the teaching of difficult concepts in COMP 102.
- Recipient of an Educational Technology Support Services (ETSS) Teaching Technology grant (University of Otago) to support the development of:
(1) an automatic test assessment and feedback system for COMP 101
(2) formative and flexible self-assessment modules for COMP 102.
Publications
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2020). Health workforce planning under conditions of uncertainty: Identifying supportive integrated care policies using scenario analysis. Journal of Integrated Care. Advance online publication. doi: 10.1108/JICA-08-2020-0052
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2020). Rethinking workforce planning for integrated care: Using scenario analysis to facilitate policy development. BMC Health Services Research, 20, 429. doi: 10.1186/s12913-020-05304-4
Bosu, M. F., MacDonell, S. G., & Whigham, P. A. (2020). Analyzing the Stationarity Process in Software Effort Estimation Datasets. International Journal of Software Engineering & Knowledge Engineering, 30(11-12), 1607-1640. doi: 10.1142/S0218194020400239
Bosu, M. F., MacDonell, S. G., & Whigham, P. (2020). Testing the stationarity assumption in software effort estimation datasets. Proceedings of the 33nd International Conference on Software Engineering and Knowledge Engineering (SEKE). (pp. 198-203). Pittsburgh, PA: KSI Research and Knowledge Systems Institute Graduate School. doi: 10.18293/SEKE2020
Bosu, M. F., MacDonell, S. G., & Whigham, P. (2020). Time-aware models for software effort estimation. Proceedings of the 33nd International Conference on Software Engineering and Knowledge Engineering (SEKE). (pp. 164-167). Pittsburgh, PA: KSI Research and Knowledge Systems Institute Graduate School. doi: 10.18293/SEKE2020
Chapter in Book - Research
Schmidt, F., MacDonell, S. G., & Connor, A. M. (2012). An automatic architecture reconstruction and refactoring framework. In R. Lee (Ed.), Software engineering research, management and applications 2011: Studies in computer intelligence (Vol. 377). (pp. 95-111). Berlin, Germany: Springer. doi: 10.1007/978-3-642-23202-2
Frantzeskou, G., MacDonell, S. G., & Stamatatos, E. (2010). Source code authorship analysis for supporting the cybercrime investigation process. In C.-T. Li (Ed.), Handbook of research on computational forensics, digital crime, and investigation: Methods and solutions. Hersey, PA: IGI Global. doi: 10.4018/978-1-60566-836-9.ch020
Kasabov, N., Song, Q., Benuskova, L., Gottgtroy, P., Jain, V., Verma, A., … MacDonell, S. (2008). Integrating local and personalised modelling with global ontology knowledge bases for biomedical and bioinformatics decision support. In T. G. Smolinski, M. G. Milanova & A.-E. Hassanien (Eds.), Computational intelligence in biomedicine and bioinformatics: Studies in computational intelligence (Vol. 151). (pp. 93-116). Berlin, Germany: Springer. doi: 10.1007/978-3-540-70778-3
Bacic, B., Kasabov, N., MacDonell, S., & Pang, S. (2008). Evolving connectionist systems for adaptive sport coaching. In M. Ishikawa, K. Doya, H. Miyanoto & T. Yamakawa (Eds.), Neural information processing: Lecture notes in computer science (Vol. 4985). (pp. 416-425). Berlin, Germany: Springer. doi: 10.1007/978-3-540-69162-4_43
Min, K., MacDonell, S., & Moon, Y.-J. (2006). Heuristic and rule-based knowledge acquisition: Classification of numeral strings in text. In A. Hoffman, B.-H. Kang, D. Richards & S. Tsumoto (Eds.), Advances in knowledge acquisition and management: Lecture notes in artificial intelligence (Vol. 4303). (pp. 40-50). Berlin, Germany: Springer. doi: 10.1007/11961239_4
Gottgtroy, P., Kasabov, N., & MacDonell, S. (2006). Evolving ontologies for intelligent decision support. In E. Sanchez (Ed.), Fuzzy logic and the semantic web. (pp. 415-439). Amsterdam: Elsevier. doi: 10.1016/S1574-9576(06)80023-7
MacDonell, S. G., & Gray, A. R. (2001). Software engineering management. In P. Bourque & R. Dupuis (Eds.), Guide to the Software Engineering Body of Knowledge (SWEBOK). (pp. 121-135). Los Alamitos, CA: IEEE Computer Society Software Engineering Co-ordinating Committee.
Gray, A. R., & MacDonell, S. G. (1998). Fuzzy logic techniques for software metric models of development effort. In W. Pedrycz & J. F. Peters (Eds.), Computational Intelligence in Software Engineering: Advances in fuzzy systems: Applications and theory (Vol. 16). (pp. 321-388). Singapore: World Scientific. doi: 10.1142/9789812816153_0012
Journal - Research Article
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2020). Health workforce planning under conditions of uncertainty: Identifying supportive integrated care policies using scenario analysis. Journal of Integrated Care. Advance online publication. doi: 10.1108/JICA-08-2020-0052
Bosu, M. F., MacDonell, S. G., & Whigham, P. A. (2020). Analyzing the Stationarity Process in Software Effort Estimation Datasets. International Journal of Software Engineering & Knowledge Engineering, 30(11-12), 1607-1640. doi: 10.1142/S0218194020400239
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2020). Rethinking workforce planning for integrated care: Using scenario analysis to facilitate policy development. BMC Health Services Research, 20, 429. doi: 10.1186/s12913-020-05304-4
Bosu, M. F., & MacDonell, S. G. (2019). Experience: Quality benchmarking of datasets used in software effort estimation. Journal of Data & Information Quality, 11(4), 19. doi: 10.1145/3328746
Licorish, S. A., & MacDonell, S. G. (2018). Exploring the links between software development task type, team attitudes and task completion performance: Insights from the Jazz repository. Information & Software Technology, 97, 10-25. doi: 10.1016/j.infsof.2017.12.005
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2018). Rethinking health workforce planning: Capturing health system social and power interactions through actor analysis. Futures, 99, 16-27. doi: 10.1016/j.futures.2018.03.009
Rees, G. H., Crampton, P., Gauld, R., & MacDonell, S. (2018). The promise of complementarity: Using the methods of foresight for health workforce planning. Health Services Management Research, 31(2), 97-105. doi: 10.1177/0951484818770408
Holvitie, J., Licorish, S. A., Spínola, R. O., Hyrynsalmi, S., MacDonell, S. G., Mendes, T. S., … Leppänen, V. (2018). Technical debt and agile software development practices and processes: An industry practitioner survey. Information & Software Technology, 96, 141-160. doi: 10.1016/j.infsof.2017.11.015
Mensah, S., Keung, J., MacDonell, S. G., Bosu, M. F., & Bennin, K. E. (2018). Investigating the significance of the Bellwether effect to improve software effort prediction: Further empirical study. IEEE Transactions on Reliability, 67(3), 1176-1198. doi: 10.1109/TR.2018.2839718
Licorish, S. A., & MacDonell, S. G. (2017). Exploring software developers’ work practices: Task differences, participation, engagement, and speed of task resolution. Information & Management, 54(3), 364-382. doi: 10.1016/j.im.2016.09.005
Rees, G. H., & MacDonell, S. (2017). Data gathering for actor analyses: A research note on the collection and aggregation of individual respondent data for MACTOR. Future Studies Research Journal, 9(1), 115-137.
Licorish, S. A., & MacDonell, S. G. (2015). Communication and personality profiles of global software developers. Information & Software Technology, 64, 113-131. doi: 10.1016/j.infsof.2015.02.004
Whigham, P. A., Owen, C. A., & MacDonell, S. G. (2015). A baseline model for software effort estimation. ACM Transactions on Software Engineering & Methodology, 24(3), 20. doi: 10.1145/2738037
Fountain, J. S., Sly, B., Holt, A., & MacDonell, S. (2015). Availability of antidotes, antivenoms, and antitoxins in New Zealand hospital pharmacies. New Zealand Medical Journal, 128(1411). Retrieved from https://www.nzma.org.nz/journal
Licorish, S. A., & MacDonell, S. G. (2014). Understanding the attitudes, knowledge sharing behaviors and task performance of core developers: A longitudinal study. Information & Software Technology, 56(12), 1578-1596. doi: 10.1016/j.infsof.2014.02.004
Shepperd, M., & MacDonell, S. (2012). Evaluating prediction systems in software project estimation. Information & Software Technology, 54(8), 820-827. doi: 10.1016/j.infsof.2011.12.008
Felizardo, K. R., MacDonell, S. G., Mendes, E., & Maldonado, J. C. (2012). A systematic mapping on the use of visual data mining to support the conduct of systematic literature reviews. Journal of Software, 7(2), 450-461. doi: 10.4304/jsw.7.2.450-461
McLeod, L., Doolin, B., & MacDonell, S. G. (2012). A perspective-based understanding of project success. Project Management Journal, 43(5), 68-86. doi: 10.1002/pmj.21290
Clear, T., & MacDonell, S. G. (2011). Understanding technology use in global virtual teams: Research methodologies and methods. Information & Software Technology, 53(9), 994-1011. doi: 10.1016/j.infsof.2011.01.011
Frantzeskou, G., MacDonell, S. G., Stamatatos, E., Georgiou, S., & Gritzalis, S. (2011). The significance of user-defined identifiers in Java source code authorship identification. Computer Systems Science & Engineering, 26(2), 123-132.
McLeod, L., & MacDonell, S. G. (2011). Factors that affect software systems development project outcomes: A survey of research. ACM Computing Surveys, 43(4), 24. doi: 10.1145/1978802.1978803
McLeod, L., MacDonell, S. G., & Doolin, B. (2011). Qualitative research on software development: A longitudinal case study methodology. Empirical Software Engineering, 16(4), 430-459. doi: 10.1007/s10664-010-9153-5
MacDonell, S., Shepperd, M., Kitchenham, B., & Mendes, E. (2010). How reliable are systematic reviews in empirical software engineering? IEEE Transactions on Software Engineering, 36(5), 676-687. doi: 10.1109/TSE.2010.28
Connor, A. M., Limbu, D. K., MacDonell, S. G., & Pears, R. (2010). Improving web information retrieval using shared contexts. International Journal of Information Sciences & Computer Engineering, 1(2), 26-35.
Wang, Y., Song, Q., MacDonell, S., Shepperd, M., & Shen, J. (2009). Integrate the GM(1,1) and Verhulst models to predict software stage effort. IEEE Transactions on Systems, Man & Cybernetics: Part C, 39(6), 647-658. doi: 10.1109/TSMCC.2009.2020690
McLeod, L., MacDonell, S., & Doolin, B. (2009). IS development practice in New Zealand organisations. Journal of Research & Practice in Information Technology, 41(1), 3-24.
Frantzeskou, G., MacDonell, S., Stamatatos, E., & Gritzalis, S. (2008). Examining the significance of high-level programming features in source code author classification. Journal of Systems & Software, 81(3), 447-460. doi: 10.1016/j.jss.2007.03.004
McLeod, L., MacDonell, S., & Doolin, B. (2007). Standard method use in contemporary IS development: An empirical investigation. Journal of Systems & Information Technology, 9(1), 6-29. doi: 10.1108/13287260710817665
McLeod, L., MacDonell, S. G., & Doolin, B. (2007). User participation in contemporary IS development: An IS management perspective. Australasian Journal of Information Systems, 15(1), 113-136.
Marshall, M. R., Song, Q., Ma, T. M., MacDonell, S. G., & Kasabov, N. K. (2005). Evolving connectionist system versus algebraic formulas for prediction of renal function from serum creatinine. Kidney International, 67(5), 1944-1954. doi: 10.1111/j.1523-1755.2005.00293.x
MacDonell, S. G., & Gray, A. R. (2005). The viability of fuzzy logic modeling in software development effort estimation: Opinions and expectations of project managers. International Journal of Software Engineering & Knowledge Engineering, 15(5), 893-918. doi: 10.1142/S0218194005002555
Limbu, D. K., Connor, A. M., & MacDonell, S. G. (2005). A contextual information retrieval framework. Bulletin of Applied Computing & Information Technology. Retrieved from http://www.citrenz.ac.nz/bacit/0303/0303index.html
MacDonell, S. G. (2003). Software source code sizing using fuzzy logic modeling. Information & Software Technology, 45(7), 389-404. doi: 10.1016/S0950-5849(03)00011-9
MacDonell, S. G., & Shepperd, M. J. (2003). Combining techniques to optimize effort predictions in software project management. Journal of Systems & Software, 66(2), 91-98. doi: 10.1016/S0164-1212(02)00067-5
MacDonell, S. G., Buckingham, D., Gray, A. R., & Sallis, P. J. (2002). Software forensics: Extending authorship analysis techniques to computer programs. Journal of Law & Information Science, 13(1), 34-69.
Kitchenham, B. A., Pickard, L. M., MacDonell, S. G., & Shepperd, M. J. (2001). What accuracy statistics really measure. Software, IEE Proceedings, 148(3), 81-85.
MacDonell, S. G., & Gray, A. R. (2001). Software forensics applied to the task of discriminating between program authors. Systems Research & Information Systems, 10, 113-127.
Gray, A. R., & MacDonell, S. G. (1999). Software metrics data analysis: Exploring the relative performance of some commonly used modeling techniques. Empirical Software Engineering, 4(4), 297-316.
MacDonell, S. G., Fletcher, T., & Wong, B. L. W. (1999). Industry practices in project management for multimedia information systems. International Journal of Software Engineering & Knowledge Engineering, 9(6), 801-815. doi: 10.1142/S0218194099000413
Gray, A. R., & MacDonell, S. G. (1997). A comparison of techniques for developing predictive models of software metrics. Information & Software Technology, 39(6), 425-437.
MacDonell, S. G. (1997). Establishing relationships between specification size and software process effort in CASE environments. Information & Software Technology, 39(1), 35-45.
MacDonell, S. G. (1994). Comparative review of functional complexity assessment methods for effort estimation. Software Engineering Journal, 9(3), 107-116.
