Abstract: The SynTest-Framework is designed as a user-friendly, flexible, and highly customizable platform that supports fuzzing and automated test case generation. It serves as a base for developing testing tools tailored to various programming languages. Additionally, the framework contains a collection of language-independent search algorithms that are optimized for automatic test case generation and fuzzing. Our primary objective with this framework is to streamline the process for researchers to devise and implement novel methods for automatic test case generation. Additionally, we hope that the framework will make it easier for practitioners to adopt automatic test case generation in their projects.

In this tutorial session, we will show how to use the framework to implement a new automatic test case generation approach. The tutorial will be hands-on and will consist of a series of practical scenarios. These scenarios will be based on the TypeScript programming language. Join us in this fun and interactive tutorial session and equip yourself with the skills to demonstrate your approach to software testing and validation.

Biography (Annibale Panichella): Annibale is an associate professor in the Software Engineering Research Group (SERG) at Delft University of Technology (TU Delft) in the Netherlands. He is the head of the Computation Intelligence for Software Engineering Lab (CISELab) within SERG. His research interests include security testing, software testing, search-based software engineering, testing for AI, empirical software engineering. He served and has served as a program committee member of various international conferences (e.g., ICSE, ESEC/FSE, ISSTA, GECCO, ICST) and as a reviewer for various international journals (e.g., TSE, TOSEM, TEVC, EMSE, STVR) in the fields of software engineering and evolutionary computation.

Biography (Mitchell Olsthoorn): Mitchell is a postdoctoral researcher in the Software Engineering Research Group (SERG) at the Delft University of Technology. He is also a member of the Computational Intelligence for Software Engineering lab (CISELab) and the Delft Blockchain Lab (DBL). His interests include network security, computational intelligence, and pen-testing. Currently, he is working on combining search-based approaches with Large Language Models (LLMs).