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 …

Test smells are defined as sub-optimal design choices developers make when
implementing test cases. Hence, similar to code smells, the research community has …

Defect prediction is proposed to assist practitioners effectively prioritize limited Software
Quality Assurance (SQA) resources on the most risky files that are likely to have post-release …

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 …

Flaky tests are software tests that exhibit a seemingly random outcome (pass or fail) despite
exercising unchanged code. In this work, we examine the perceptions of software …

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 …

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 …

The impact of bad programming practices, such as code smells, in production code has
been the focus of numerous studies in software engineering. Like production code, unit tests …

In recent years, researchers and practitioners have been studying the impact of test smells
on test maintenance. However, there is still limited empirical evidence on why developers …

One of the main challenges that developers face when testing their systems lies in
engineering test cases that are good enough to reveal bugs. And while our body of …