Automated detection of software vulnerabilities is a fundamental problem in software
security. Existing program analysis techniques either suffer from high false positives or false …

Randomized algorithms are widely used to address many types of software engineering
problems, especially in the area of software verification and validation with a strong …

This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

Search-based software testing (SBST) generates high-coverage test cases for programs
under test with a combination of test case generation and mutation. SBST's performance …

Fuzz testing has enjoyed great success at discovering security critical bugs in real software.
Recently, researchers have devoted significant effort to devising new fuzzing techniques …

This paper presents a novel end-to-end approach to program repair based on sequence-to-
sequence learning. We devise, implement, and evaluate a technique, called SequenceR, for …

Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

We introduce Sapienz, an approach to Android testing that uses multi-objective search-
based testing to automatically explore and optimise test sequences, minimising length, while …

Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …

This paper defines software fairness and discrimination and develops a testing-based
method for measuring if and how much software discriminates, focusing on causality in …