  Test smells, similar to code smells, can negatively impact both the test code
and the production code being tested. Despite extensive research on test smells
in languages like Java, Scala, and Python, automated tools for detecting test
smells in C# are lacking. This paper aims to bridge this gap by extending the
study of test smells to C#, and developing a tool (xNose) to identify test
smells in this language and analyze their distribution across projects. We
identified 16 test smells from prior studies that were language-independent and
had equivalent features in C# and evaluated xNose, achieving a precision score
of 96.97% and a recall score of 96.03%. In addition, we conducted an empirical
study to determine the prevalence of test smells in xUnit-based C# projects.
This analysis sheds light on the frequency and distribution of test smells,
deepening our understanding of their impact on C# projects and test suites. The
development of xNose and our analysis of test smells in C# code aim to assist
developers in maintaining code quality by addressing potential issues early in
the development process.
