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Computer Science

D-Index
38
Citations
6194
World Ranking
10229
National Ranking
27

Overview

Stephen G. MacDonell is affiliated with Auckland University of Technology in New Zealand. Their research predominantly falls within the field of Computer Science, with a focus on several subfields including Information Systems, Artificial Intelligence, Computer Science Applications, Computer Networks and Communications, and Software.

The primary topics addressed in their work encompass Software Engineering Research, Software Engineering Techniques and Practices, Open Source Software Innovations, Advanced Malware Detection Techniques, Software Reliability and Analysis Research, Advanced Software Engineering Methodologies, and Non-Destructive Testing Techniques.

Their recent publications reflect a concentration on software development methodologies, fault diagnostics, and data-driven prediction models. Notable papers include:

  • What Makes Agile Software Development Agile?, 2021, IEEE Transactions on Software Engineering
  • Finding faults: A scoping study of fault diagnostics for Industrial Cyber-Physical Systems, 2020, Journal of Systems and Software
  • An empirical study on the effectiveness of data resampling approaches for cross-project software defect prediction, 2021, IET Software
  • Soil texture prediction with automated deep convolutional neural networks and population-based learning, 2023, Geoderma
  • Towards the statistical construction of hybrid development methods, 2020, Journal of Software Evolution and Process

Stephen G. MacDonell frequently collaborates with several co-authors. Those with the most joint publications include Sherlock A. Licorish, Ifeanyi G. Ndukwe, Amjed Tahir, Roopak Sinha, and Krassie Petrova.

Their works are regularly published in venues such as arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, Journal of Systems and Software, and IEEE Transactions on Software Engineering.

Best Publications

  • What accuracy statistics really measure

    Barbara A. Kitchenham;Lesley Pickard;Stephen G. MacDonell;Martin J. Shepperd

  • Evaluating prediction systems in software project estimation

    Martin Shepperd;Steve MacDonell

  • Factors that affect software systems development project outcomes: A survey of research

    Laurie McLeod;Stephen G. MacDonell

  • A Perspective-Based Understanding of Project Success:

    Laurie McLeod;Bill Doolin;Stephen G. MacDonell

  • A comparison of techniques for developing predictive models of software metrics

    Andrew R. Gray;Stephen G. MacDonell

  • Factors systematically associated with errors in subjective estimates of software development effort: the stability of expert judgment

    A.R. Gray;S.G. MacDonell;M.J. Shepperd

  • How Reliable Are Systematic Reviews in Empirical Software Engineering

    S MacDonell;M Shepperd;B Kitchenham;E Mendes

  • Software Forensics: Extending Authorship Analysis Techniques to Computer Programs

    Stephen G MacDonell;Donna Buckingham;Andrew R Gray;Philip J Sallis

  • Combining techniques to optimize effort predictions in software project management

    Stephen G. MacDonell;Martin J. Shepperd

  • A Baseline Model for Software Effort Estimation

    Peter A. Whigham;Caitlin A. Owen;Stephen G. Macdonell

  • Applications of fuzzy logic to software metric models for development effort estimation

    A. Gray;S. MacDonell

  • Source Code Authorship Analysis For Supporting the Cybercrime Investigation Process.

    Georgia Frantzeskou;Stephen G. MacDonell;Efstathios Stamatatos

  • Using Visual Text Mining to Support the Study Selection Activity in Systematic Literature Reviews

    Katia R. Felizardo;Norsaremah Salleh;Rafael M. Martins;Emilia Mendes

  • Understanding the attitudes, knowledge sharing behaviors and task performance of core developers: A longitudinal study

    Sherlock A. Licorish;Stephen G. MacDonell

  • Software Metrics Data Analysis—Exploring the RelativePerformance of Some Commonly Used Modeling Techniques

    Andrew R. Gray;Stephen G. Macdonell

  • A systematic mapping study on dynamic metrics and software quality

    Amjed Tahir;Stephen G. MacDonell

  • A comparison of modeling techniques for software development effort prediction

    Stephen G. MacDonell;Andrew R. Gray

  • What Makes Agile Software Development Agile

    Marco Kuhrmann;Paolo Tell;Regina Hebig;Jil Ann Christin Klunder

  • Examining the significance of high-level programming features in source code author classification

    Georgia Frantzeskou;Stephen MacDonell;Efstathios Stamatatos;Stefanos Gritzalis

  • Technical debt and agile software development practices and processes: An industry practitioner survey

    Johannes Holvitie;Johannes Holvitie;Sherlock A. Licorish;Rodrigo O. Spínola;Sami Hyrynsalmi

  • Source code authorship analysis for supporting the cybercrime investigation process

    Georgia Frantzeskou;Stefanos Gritzalis;Stephen G. MacDonell

  • What accuracy statistics really measure

    Barbara Ann Kitchenham;Stephen G. MacDonell;Lesley M. Pickard;Martin J. Shepperd

Frequent Co-Authors

Martin Shepperd
Martin Shepperd Brunel University London
José Carlos Maldonado
José Carlos Maldonado Universidade de São Paulo
Nikola Kasabov
Nikola Kasabov Auckland University of Technology
Emilia Mendes
Emilia Mendes Aarhus University
Jürgen Münch
Jürgen Münch Reutlingen University
Jacky Keung
Jacky Keung City University of Hong Kong
Stefanos Gritzalis
Stefanos Gritzalis University of Piraeus
Barbara Kitchenham
Barbara Kitchenham Keele University
Efstathios Stamatatos
Efstathios Stamatatos University of the Aegean
Steve Counsell
Steve Counsell Brunel University London

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