Dr Marc Roper


Computer and Information Sciences

Personal statement

My research is primarily focused on the area of software engineering, and in particular the development and evaluation of techniques to support the construction and evolution of more reliable and robust software systems. A common theme in much of this work is the application of machine learning to software engineering problems; for example, to automatically generate program test data, predict software project costs, perform intrusion detection, identify the root location of faults within systems, and automatically detect software system failures. The latter of these in particular makes extensive use of a range of both semi-supervised and unsupervised (clustering) machine learning algorithms to detect anomalous entries in large very high-dimensional and complex data sets. More recently I have also been turning my attention to the converse problem of testing AI systems.

My expertise and interests in machine learning extend outside the software engineering domain and I have employed clustering and classification algorithms in a variety of other contexts such as the automatic identification of potential road accident blackspots from crowdsourced smartphone sensor data, and the detection of objects within images.

I also have extensive experience of using machine learning in a variety of industrial projects such as forecasting customer buyer behaviour, predicting building energy performance, and modelling interventions to combat sedentary behaviour.


Has expertise in:

    • Software Engineering (particularly design, testing and debugging)
    • Data Analytics
    • Machine Learning
    • Conducting empirical studies of software engineering techniques and processes
    • Search-based software engineering
    • Software analytics (static analysis, dynamic analysis and repository mining)


Recognition system for Libyan vehicle license plate
Almabruk Tahani A A, Almaghairbe Rafig, Bukewitin talal, Roper Marc
ICEMIS'21 The 7th International Conference on Engineering &MIS 2021 The International Conference on Engineering & MIS (2021)
Machine learning techniques for automated software fault detection via dynamic execution data : empirical evaluation study
Almaghairbe Rafig, Roper Marc, Almabruk Tahani
Proceedings of the 6th International Conference on Engineering and MIS 2020, ICEMIS 2020 , pp. 1-12 (2020)
A systematic literature review of machine learning techniques for software maintainability prediction
Alsolai Hadeel, Roper Marc
Information and Software Technology Vol 119 (2020)
Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery
Lapp Linda, Bouamrane Matt-Mouley, Kavanagh Kimberley, Roper Marc, Young David, Schraag Stefan
Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol 11526 LNAI, pp. 376–385 (2019)
Using machine learning to classify test outcomes
Roper Richard
2019 IEEE International Conference On Artificial Intelligence Testing (AITest) , pp. 99-100 (2019)
Application of ensemble techniques in predicting object-oriented software maintainability
Alsolai Hadeel, Roper Marc
Proceedings of EASE 2019 - Evaluation and Assessment in Software Engineering EASE 2019 - Evaluation and Assessment in Software Engineering, pp. 370-373 (2019)

More publications


Over my career I have taught a lare range of classes, from 1st year undergraduate to postgraduate, mainly on areas related to programming, software engineering, software design, data analytics and machine learning.

My main current teaching responsibilities are:

I am also responsible for overseeing the MEng final year group project:

Research interests

  • Software engineering
  • Machine Learning

Professional activities

ESEM 2011: 5th International Symposium on Empirical Software Engineering and Measurement
Member of programme committee
Testing: Academic and Industrial Conference - Practice And Research Techniques (TAICPART)
Software Testing, Verification and Reliability (Journal)
Editorial board member
Information and Software Technology (Journal)
Editorial board member

More professional activities


AI and blockchain for construction, mining and infrastructure companies - Hypervine / Data Lab
Roper, Marc (Principal Investigator) Roberts, Jen (Co-investigator)
01-Jan-2022 - 31-Jan-2022
Providing confidence to encourage active travel through the application of AI
Dunlop, Mark (Principal Investigator) Roper, Marc (Co-investigator)
01-Jan-2020 - 28-Jan-2021
KTP - Maru Syngro
Barlow, Euan (Principal Investigator) Revie, Matthew (Co-investigator) Roper, Marc (Co-investigator)
15-Jan-2018 - 14-Jan-2020
Optimising Industrial Service Workforces using Mobile App Data
Roper, Marc (Principal Investigator) Minisci, Edmondo (Co-investigator) Riccardi, Annalisa (Co-investigator)
01-Jan-2018 - 01-Jan-2019
Development of a cross platform, personalised digital intervention to reduce sedentary behaviour and improve physical and mental well-being at work
Terzis, Sotirios (Principal Investigator) Kirk, Alison (Principal Investigator) Roper, Marc (Co-investigator) Wallace, William (Co-investigator) Gibson, Ann-Marie (Co-investigator) Cogan, Nicola (Co-investigator) Janssen, Xanne (Co-investigator)
01-Jan-2018 - 31-Jan-2018
Predicting user responses to wellness prompts
Terzis, Sotirios (Principal Investigator) Roper, Marc (Co-investigator) Lennon, Marilyn (Co-investigator) Wallace, William (Co-investigator)
18-Jan-2017 - 21-Jan-2017

More projects


Computer and Information Sciences
Livingstone Tower

Location Map

View University of Strathclyde in a larger map