Causality for Software Engineering Application

PhD Qualifying Examination


Title: "Causality for Software Engineering Application"

by

Mr. Zhenlan JI


Abstract:

Causality analysis has gained significant attention in software engineering due
to its potential to unravel complex relationships in intricate systems,
identify root causes of performance bugs, and provide insights into underlying
mechanisms. As a fundamental concept in various fields of science and
engineering, such as epidemiology, economics, and social sciences, causality
analysis provides a principal way to answer questions like "what causes what"
and "what would happen if", which are essential for science and engineering
research. In software engineering, causality analysis methods have been
effectively applied in software engineering research areas like statistical
fault localization, root cause analysis, machine learning fairness, and deep
neural network testing.

This survey aims to provide a comprehensive overview of causality analysis
methods in software engineering, demonstrating their effectiveness in software
engineering and motivate further research in this area. Specifically, this
survey reviews 25 papers that apply causality analysis in software engineering,
categorizing them into different groups based on the research topics and the
causality analysis methods used. Then, for each group, we provide a detailed
discussion of the causality analysis methods used in the papers, and discussing
their advantages and disadvantages. Additionally, the survey also presents a
systematic and accessible introduction to these methods, with the goal of
facilitating further research and enabling researchers to better understand and
improve existing research in this area. Furthermore, the survey concludes the
current trend and future research directions in causality analysis in software
engineering. With this survey, we hope to inspire researchers to further
explore the potential of causality analysis in software engineering.


Date:                   Tuesday, 20 February 2024

Time:                   1:30pm - 3:30pm

Venue:                  Room 5501
                        Lifts 25/26

Committee Members:      Dr. Shuai Wang (Supervisor)
                        Dr. Lionel Parreaux (Chairperson)
                        Dr. Wei Wang
                        Dr. Dan Xu