Background: Code smells indicate suboptimal design or implementation choices in the
source code that often lead it to be more change-and fault-prone. Researchers defined …

Code smells are symptoms of poor design and implementation choices weighing heavily on
the quality of produced source code. During the last decades several code smell detection …

The test code, just like production source code, is subject to bad design and programming
practices, also known as smells. The presence of test smells in a software project may affect …

Prior works have developed transformer-based language learning models to automatically
generate source code for a task without compilation errors. The datasets used to train these …

Code smells are structures in the source code that suggest the possibility of refactorings.
Consequently, developers may identify refactoring opportunities by detecting code smells …

Test smells are sub-optimal design choices in the implementation of test code. As reported
by recent studies, their presence might not only negatively affect the comprehension of test …

Defect prediction models focus on identifying defect-prone code elements, for example to
allow practitioners to allocate testing resources on specific subsystems and to provide …

Infrastructure-as-code (IaC) is the DevOps tactic of managing and provisioning infrastructure
through machine-readable definition files, rather than physical hardware configuration or …

Code smells are poor implementation choices applied by developers during software
evolution that often lead to critical flaws or failure. Much in the same way, community smells …

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