Search-Based Software Engineering

Automatic Vulnerability Injection using Genetic Improvement and Static Code Analysers

This thesis explores the idea of applying genetic improvement in the aim of injecting vulnerabilities into programs. Generating vulnerabilities automatically in this manner would allow creating datasets of vulnerable programs. This would, in turn, help training machine-learning models to detect vulnerabilities more efficiently.

Leveraging Large Language Models to Automatically Infer RESTful API Specifications

Application Programming Interfaces, known as APIs, are increasingly popular in modern web applications. With APIs, users around the world are able to access a plethora of data contained in numerous server databases.

Xavier Devroey, SSBSE 2021 program co-chair

Version française : https://nouvelles.unamur.be/upnews.2021-10-18.2189995459/view. Last Monday and Tuesday 11 and 12 October 2021 took place the 13th edition of the Symposium on Search-Based Software Engineering (SSBSE ’21). This symposium is held every year and brings together specialists in evolutionary computation applied to software engineering (SBSE).