
Jeremy Bradbury
PhD
Associate Professor
Computer ScienceFaculty of Science
Enhancing software quality assurance through the application of machine learning to software testing and analysis.
jeremy.bradbury@ontariotechu.ca
905.721.8668 ext. 3685
Areas of expertise
- Artificial intelligence
- Computer science education
- Computer software
- Machine learning
- Multi-core and many-core software, concurrent software
- Open-source software development
- Serious games/gaming
- Software engineering
- Software quality assurance
- Teaching strategies for programming and software development
- PhD in Computer Science Queen's University 2007
- MSc in Computing and Information Science Queen's University 2002
- BSc in Computer Science and Mathematics, First Class Honours with Distinction Mount Allison University 2000
Educational Games for K-12 Computer Science
Toronto, Ontario February 22, 202020th Annual Conference of the Association for Computer Studies Education (ACSE 2020)
Can Commit History Predict Future Code Changes in GitHub Projects
Universidade Nova de Lisboa, Portugal June 12, 2018Invited NOVA LINCS Seminar.
Automating Software Development Using Artificial Intelligence (AI)
Mount Allison University, Sackville, New Brunswick March 21, 2018Invited Computer Science Seminar.
Automating Software Development Using Artificial Intelligence (AI)
Dalhousie University, Halifax, Nova Scotia March 20, 2018Invited Computer Science Seminar.
Automatically Repairing Concurrency Bugs with ARC
Saint Petersburg, Russia August 19, 20131st International Conference on Multicore Software Engineering, Performance, and Tools
Effectively Using Search-Based Software Engineering Techniques Within Model Checking and its Applications
San Francisco, California May 30, 20132013 1st International Workshop on Combining Modelling and Search-Based Software Engineering
Using Combinatorial Benchmark Construction to Improve the Assessment of Concurrency Bug Detection Tools
Minneapolis, Minnesota July 15, 2012International Symposium on Software Testing and Analysis
Predicting Mutation Score Using Source Code and Test Suite Metrics
Zurich, Switzerland June 5, 20122012 First International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering
Automatically Predicting Bug Severity Early in the Development Process
Published in Proc. of the 42nd International Conference on Software Engineering (ICSE 2020) The New Ideas and Emerging Results (NIER) track, Seoul, South Korea, Oct. 2020. (to appear)Jude Arokiam, Jeremy S. Bradbury
View more - Automatically Predicting Bug Severity Early in the Development Process
GidgetML: An Adaptive Serious Game for Enhancing First Year Programming Labs
Published in Proc. of the 42nd International Conference on Software Engineering (ICSE 2020) The Software Engineering Education and Training (SEET) track, Seoul, South Korea, Oct. 2020. (to appear)Michael A. Miljanovic, Jeremy S. Bradbury
View more - GidgetML: An Adaptive Serious Game for Enhancing First Year Programming Labs
A Review of Serious Games for Programming
Published in Proc. of the 4th Joint Conference on Serious Games (JCSG 2018) pages 204-216, Darmstadt, Germany, Nov. 7-8, 2018.Michael A. Miljanovic, Jeremy S. Bradbury
Making Serious Programming Games Adaptive
Published in Proc. of the 4th Joint Conference on Serious Games (JCSG 2018) pages 253-259, Darmstadt, Germany, Nov. 7-8, 2018.Michael A. Miljanovic, Jeremy S. Bradbury
RoboBUG: A Serious Game for Learning Debugging
Published in Proc. of the 13th Annual ACM International Computing Education Research Conference (ICER 2017) pages 93-100, Tacoma, WA, USA, Aug. 2017Michael A. Miljanovic, Jeremy S. Bradbury
Assessment of Software Modelling Techniques for Wireless Sensor Networks: A Survey
Published in Sensors & Transducers Journal March 12, 2012Wireless Sensor Networks (WSNs) monitor environment phenomena and in some cases react in response to the observed phenomena. The distributed nature of WSNs and the interaction between software and hardware components makes it difficult to correctly design and develop WSN systems. One solution to the WSN design challenges is system modeling. In this paper, we present a survey of nine WSN modeling techniques and show how each technique models different parts of the system such as sensor behaviour, sensor data and hardware. Furthermore, we consider how each modeling technique represents the network behaviour and network topology. We also consider the available supporting tools for each of the modeling techniques. Based on the survey, we classify the modeling techniques and derive examples of the surveyed modeling techniques by using SensIV system.
View more - Assessment of Software Modelling Techniques for Wireless Sensor Networks: A Survey
Tim McTiernan Student Mentorship Award
Ontario Tech University2018-2019
Teaching Representative, Ontario Tech University Board of Governors
September 1, 2015Dr. Bradbury was elected as a Teaching Representative on Ontario Tech University's Board of Governors for a three-year term from 2015-18.
Canada Foundation for Innovation Leaders Opportunity Fund - Laboratory for Human-Centred Computer Science Research
January 1, 2012Dr. Bradbury is the principal investigator of this research in Ontario Tech University's Human-Centred Control (HCC) Lab, which was designed for conducting controlled experiments that allow researchers to better understand and evaluate how people interact with leading-edge computer technology. Research in this lab falls under three main themes: information visualization, software engineering and computer security. In all three themes, a novel research approach focuses on the usability perspective of innovative prototypes and tools in new and emerging environments (e.g., mobile devices, large touch displays).
RAISE 2012 Best Paper Award
January 1, 2012Dr. Bradbury received the award for his paper Predicting Mutation Score Using Source Code and Test Suite Metrics, at the Workshop on Realizing Artificial Intelligence Synergies in Software Engineering.
Consortium for Software Enginnering Research (CSER) 2011 Best Poster Award
October 1, 2011Awarded one of three Best Poster Awards at the 2011 CSER Fall Meeting for his work Eclipticon: Eclipse Plugin for Concurrency Testing.
SoftVis’10 Best Poster Award
October 25, 2010Dr. Bradbury received this award for his poster An Interactive Visualization of Thread Interleavings at the 5th ACM Symposium on Software Visualization (SoftVis'10).
School of Computing Award for Excellence in Teaching Assistance
June 1, 2003Dr. Bradbury received this award for his contributions to teaching at Queen's University from 2002-03.
Ian A. Macleod Award
June 1, 2003Given to the graduate student who has made the greatest contribution to the intellectual and social spirit of the School of Computing, Queen's University, 2002-03
eXcellence In Variant Testing (XIVT)
ITEA 3 Call 4 Pan-European Project (2018)[locally funded through a contract with QA Consultants]
Utilizing Artificial Intelligence to Improve the Testing and Debugging of Concurrent Software
NSERC Discovery Grant (2018)Testing and Analysis of Concurrent and Heterogeneous Computing Software ($75,000)
NSERC Discovery Grant April 1, 2013This collaborative five-year research grant expands upon previous research in software testing and analysis in several key areas. This project aims to improve the quality of concurrent and heterogeneous (multicore + manycore) software, and develop better tools to improve the speed and accuracy of assessing this software through automatic testing and analysis techniques. Another key area of this project builds on creating enhanced algorithms for automatic bug detection and repair, as well as automatic debugging in which an algorithm can automatically locate code with the highest probability for a bug to exist.
Laboratory for Human-Centred Computer Science Research ($21,152)
Canada Foundation for Innovation Leaders Opportunity Fund January 1, 2012Dr. Bradbury is the principal investigator of this research in Ontario Tech University's Human-Centred Control (HCC) Lab, which was designed for conducting controlled experiments that allow researchers to better understand and evaluate how people interact with leading-edge computer technology. Research in this lab falls under three main themes: information visualization, software engineering and computer security. In all three themes, a novel research approach focuses on the usability perspective of innovative prototypes and tools in new and emerging environments (e.g., mobile devices, large touch displays).
Empirical Assessment and Improvement of Fault Detection Techniques for Concurrent Software
NSERC Discovery Grant (2008)ACM Special Interest Group on Software Engineering (SIGSOFT)
ACM Special Interest Group on Computer Science Education (SIGCSE)
Association of Computing Machinery (ACM)
Consortium of Software Engineering Research (CSER)
IEEE Computer Society
Institute of Electrical & Electronics Engineers (IEEE)
- Programming Workshop (CSCI 1060U)
- Software Quality Assurance (CSCI 3060U)
- Development of Concurrent Software (CSCI 5100G)