ICST 2024
Mon 27 - Fri 31 May 2024 Canada
Tue 28 May 2024 11:22 - 11:45 at Room 1 - Session 2 (Papers 2)

Regression testing in software development is challenging due to the large number of test cases and continuous integration (CI) practices. Recently, test case prioritization (TCP) using machine learning (ML) has been shown to efficiently execute regression tests. This study introduces an automated, end-to-end, self-contained ML-based framework, TCP-Tune, tailored exclusively for TCP. The framework utilizes open-source version control system data to combine code-change-related features with the test execution results. This integration allows the automated optimization of hyperparameters across different ML models to improve TCP. The framework also effectively visualizes and utilizes multiple evaluation metrics to evaluate the performance of the model over several builds. Unlike existing implementations, which rely on various frameworks, TCP-Tune enables the effortless incorporation of features from multiple sources and fine-tuned models, thereby providing optimum test prioritization in the ever-changing field of software development. Our approach has helped provide efficient TCP through experimental assessments of a real-life, large-scale CI system

Tue 28 May

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Session 2 (Papers 2)AIST at Room 1
11:00
22m
Talk
"No Free Lunch" when using Large Language Models to Verify Self-Generated Programs
AIST
Sol Zilberman Michigan State University, Betty H.C. Cheng Michigan State University
11:22
22m
Talk
An End-to-End Test Case Prioritization Framework using Optimized Machine Learning Models
AIST
Md Asif Khan Ontario Tech University, Akramul Azim Ontario Tech University, Ramiro Liscano Ontario Tech University, Kevin Smith International Business Machines Corporation (IBM), Yee-Kang Chang International Business Machines Corporation (IBM), Qasim Tauseef International Business Machines Corporation (IBM), Gkerta Seferi International Business Machines Corporation (IBM)
11:45
22m
Talk
Iterative Optimization of Hyperparameter-based Metamorphic Transformations
AIST
Gaadha Sudheerbabu Åbo Akademi University, Tanwir Ahmad Åbo Akademi University, Dragos Truscan Åbo Akademi University, Jüri Vain Tallinn University of Technology, Estonia, Ivan Porres Åbo Akademi University
12:07
22m
Talk
Machine Learning for Cross-Vulnerability Prediction in Smart Contracts
AIST
Hajra Naeem Toronto Metropolitan University, Manar H. Alalfi