Additive manufacturing (AM) is poised to bring a revolution due to its unique production
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …

Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …

The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …

When developers make changes to their code, they typically run regression tests to detect if
their recent changes (re) introduce any bugs. However, many tests are flaky, and their …

Background When you make a forex transaction, you sell one currency and buy another. If
the currency you buy increases against the currency you sell, you profit, and you do this …

Code smells represent poor implementation choices performed by developers when
enhancing source code. Their negative impact on source code maintainability and …

Background: Software vulnerabilities are weaknesses in source code that might be exploited
to cause harm or loss. Previous work has proposed a number of automated machine …

Code smells are structures in code that often harm its quality. Manually detecting code
smells is challenging, so researchers proposed many automatic detectors. Traditional code …