Can RVEA with DynaMOSA features perform well at generating test cases?

Can RVEA with DynaMOSA features perform well at generating test cases?

Datskiv, Sergey (TU Delft Electrical Engineering, Mathematics and Computer Science)

Panichella, A. (mentor)
Olsthoorn, Mitchell (mentor)
Stallenberg, D.M. (mentor)
Verwer, S.E. (graduation committee)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2023-06-28

On the intuitive level, software testing is important because it assures the quality of the software used by humans. However, ensuring this quality is not an easy task because as the complexity of the software increases, so do the efforts to test it. Search-based software testing is an active research field that develops and explores tools for automatic test case generation. Their work involves using meta-heuristic search optimisation approaches such as evolutionary algorithms
from the evolutionary computation community and applying them to test case generation. The crossover between the evolutionary computation domain and the test case generation one produced DynaMOSA, a state-of-the-art evolutionary algorithm for generating test cases. In an attempt to
produce another well-performing algorithm, this paper performs another crossover between the two communities and creates DynaMOSARVEA - a product of a Reference Vector Guided Evolutionary Algorithm (RVEA) and DynaMOSA.
The conducted empirical study showed that although DynaMOSARVEA does not outperform DynaMOSA, it did outperform RVEA, thus demonstrating the value brought by domain-specific knowledge.

Fuzzing
Evolutionary Intelligence
Javascript
Software Testing
Bug Hunting
RVEA
DynaMOSA
MOSA

http://resolver.tudelft.nl/uuid:49bfac14-ba1a-43f9-97cd-e25084511165

Student theses

bachelor thesis

© 2023 Sergey Datskiv