The 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025) took place in Ottawa, ON, Canada from April 27-May 3, 2025. SEER Lab members Prof. Jeremy Bradbury and Prof. Michael Miljanovic were present along with Ontario Tech colleague Prof. Cristiano Politowski.
Congratulations to Ashar Izhar, Daniel Hinbest, Dev Thaker, and Mirisan Ravindran who all successfully presented their Computer Science honours theses last Thursday! 🎓 A further congratulations to Ashar who’s thesis was nominated for the Ontario Tech Computer Science Outstanding Thesis Award.
Continue reading “SEER Lab BSc (Hons.) Students Successfully Present Theses”Last Friday, Stacey Koornneef presented at the 2025 Digital Innovation in Education Conference on “Lessons Learned: How to Design & Evaluate Cost-Accessible Coding Games for Children.”
SEER Lab’s Prof. Jeremy Bradbury and Riddhi More are at the 18th IEEE International Conference on Software Testing, Verification and Validation (ICST 2025) this week in Naples, Italy.
Riddhi will be presented their paper “An Analysis of LLM Fine-Tuning and Few-Shot Learning for Flaky Test Detection and Classification” and Prof. Jeremy Bradbury will be presenting their paper “Addressing Data Leakage in HumanEval Using Combinatorial Test Design.”
Prof. Bradbury will also be a panel member at the ICST 2025 Doctoral Symposium.
MSc student Riddhi More presented the latest lab research paper, “Assessing Data Augmentation-Induced Bias in Training and Testing of Machine Learning Models,” (co-authored with Prof. Jeremy Bradbury at the 1st International Workshop on Fairness in Software Systems (FAIRNESS 2025).
Data augmentation has become a standard practice in software engineering to address limited or imbalanced data sets, particularly in specialized domains like test classification and bug detection where data can be scarce. Although techniques such as SMOTE and mutation-based augmentation are widely used in software testing and debugging applications, a rigorous understanding of how augmented training data impacts model bias is lacking. It is especially critical to consider bias in scenarios where augmented data sets are used not just in training but also in testing models. Through a comprehensive case study of flaky test classification, we demonstrate how to test for bias and understand the impact that the inclusion of augmented samples in testing sets can have on model evaluation.
MSc student Riddhi More and Prof. Jeremy Bradbury are in Montreal, PQ this week attending the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025) and the 1st International Workshop on Fairness in Software Systems (FAIRNESS 2025). Riddhi will also be presenting their paper “Assessing Data Augmentation-Induced Bias in Training and Testing of Machine Learning Models” at the FAIRNESS workshop.
Today Prof. Michael Miljanovic presented the latest SEER Lab paper at the SIGCSE Technical Symposium on Computer Science Education (SIGCSE 2025). The paper titled “How Effective and Efficient Are Student-Written Software Tests?”, is co-authored by Amanda Showler, Michael Miljanovic, and Jeremy Bradbury.
This paper aims to better understand gaps in students’ testing skills and knowledge. We analyzed 1014 software tests written by 12 groups in an undergraduate Software Quality Assurance (SQA) course project. In the project the student groups were provided a requirements document and were instructed to follow Test Driven Development (TDD) practices using black-box tests. To understand how the groups applied black-box testing in their project, we created an automatic tool to sort the tests into categories or “test buckets.” By analyzing the test bucket data, we were able to assess the effectiveness and efficiency of student-written tests. We observed that the student groups were significantly more likely to test for explicit requirements than implicit requirements and significantly more likely to test happy paths than invalid inputs. Furthermore, students inefficiently tested happy paths, invalid inputs and explicit requirements resulting in a higher proportion of software tests with duplicate intent. Based on these results we provide insights into how black-box test education can be improved.
SEER Lab’s Stacey Koornneef and Prof. Michael Miljanovic are in Pittsburgh, PA this week attending the SIGCSE Technical Symposium on Computer Science Education (SIGCSE 2025). Michael Miljanovic will be presenting the latest lab paper titled “How Effective and Efficient Are Student-Written Software Tests?” (co-authored by Amanda Showler, Michael Miljanovic, and Jeremy Bradbury). Stacey Koornneef will also be presenting two posters in collaboration with Prof. Annie Lee at the conference.
SEER Lab PhD student Stacey Koornneef presenting her talk titled “Designing and Evaluating a Cost-Accessible Computational Thinking Educational Game for K-5 Students” at the Canadian Women in Computing Conference (CAN-CWIC 2024)!
SEER Lab members Bridget Green, Riddhi More, Rosie Khurmi, Stacey Koornneef and Syeda Bisha Fatima are attending the Canadian Women in Computing Conference (CAN-CWIC 2024) this weekend! Thank you to OntarioTech Computer Science and the Faculty of Science for sponsoring them.
