Incorporating Domain-Specific Insights for Automated Test Generation

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


MPhil Thesis Defence


Title: "Incorporating Domain-Specific Insights for Automated Test Generation"

By

Miss Ka Wing Yoyo YEUNG


Abstract:

There has been growing discussion in Automated Test Generation (ATG) among both 
academia and industry due to its critical role in software development 
lifecycle aimed at enhancing the efficiency and quality of software testing. 
With the increased complexity in software systems and incessant demand for 
faster development cycles, more and more studies have been dedicated to 
purposing and improving existing techniques.

Central to our investigation is the recognition of existing ATG methodologies' 
limitations, particularly their effectiveness in real-world fault detection. 
Through an extensive review of literature and existing techniques, we identify 
a critical gap in the application of domain knowledge - specific insights 
derived from manual bug-fixing processes that are not yet leveraged in existing 
ATG approaches.

In this thesis, we introduce an approach to integrate this untapped domain 
knowledge with automated testing processes. Our approach aims to complement 
existing ATG methodologies by harnessing developers' experimental insights 
during manual debugging for test generation. The test cases generated by our 
approach are destined to be different from those generated by existing 
methodologies due to the difference in test input collection.

We evaluate our technique using subjects from Defects4J. Our evaluation 
demonstrates the potential of this integrated approach, showing an improvement 
in fault detection capabilities and test coverage. We also discuss the broader 
implications of our findings for software development practices, emphasizing 
the value of synergizing human expertise with automation for advancing software 
quality assurance.

This work contributes to the field of ATG by offering a new perspective on 
improving automated testing's effectiveness and efficiency. It opens avenues 
for future research on the integration of human-derived insights with automated 
systems, marking a step forward in the evolution of software testing 
methodologies.


Date:                   Thursday, 8 August 2024

Time:                   2:00pm - 4:00pm

Venue:                  Room 5508
                        Lifts 25/26

Chairman:               Dr. Shuai WANG

Committee Members:      Prof. Shing-Chi CHEUNG (Supervisor)
                        Dr. Desmond TSOI