Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable
insights in specific phases. The rise of continuous practices in software projects emphasizes …

Continuous Integration (CI) has become a well-established software development practice
for automatically and continuously integrating code changes during software development …

We propose a method for scenario-based testing of maritime collision avoidance systems.
The goal is to test an autonomous agent in scenarios that can lead to an unacceptable risk …

In this paper we present a novel algorithm for automatic performance testing that uses an
online variant of the Generative Adversarial Network (GAN) to optimize the test generation …

This research conducted a systematic review of the literature on machine learning (ML)-
based methods in the context of Continuous Integration (CI) over the past 22 years. The …

Performance is arguably the most crucial attribute that reflects the behavior of a configurable
software system. However, given the increasing scale and complexity of modern software …

Generating tests that can reveal performance issues in large and complex software systems
within a reasonable amount of time is a challenging task. On one hand, there are numerous …

Background: Machine Learning (ML) methods are being increasingly used for automating
different activities, eg, Test Case Prioritization (TCP), of Continuous Integration (CI) …

Internet of Things (IoT) devices are increasingly present in people's daily lives. Thus has
increased research interest in investigating strategies that can ensure that these …

Due to the importance of web application testing techniques for detecting faults and
assessing quality attributes, many research papers were published in this field. For this …