In the past five years there has been a dramatic increase in work on Search-Based Software
Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based …

Genetic improvement (GI) uses automated search to find improved versions of existing
software. We present a comprehensive survey of this nascent field of research with a focus …

This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …

The test case generation is intrinsically a multi-objective problem, since the goal is covering
multiple test targets (eg, branches). Existing search-based approaches either consider one …

Test case generation is among the most labour-intensive tasks in software testing. It also has
a strong impact on the effectiveness and efficiency of software testing. For these reasons, it …

With the increasing adoption of Deep Learning (DL) for critical tasks, such as autonomous
driving, the evaluation of the quality of systems that rely on DL has become crucial. Once …

Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …

Search Based Software Testing (SBST) formulates testing as an optimisation problem, which
can be attacked using computational search techniques from the field of Search Based …

Metaheuristic search techniques have been extensively used to automate the process of
generating test cases, and thus providing solutions for a more cost-effective testing process …

Search-Based Software Testing is the use of a meta-heuristic optimizing search technique,
such as a Genetic Algorithm, to automate or partially automate a testing task, for example the …