The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, the …

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 …

Code smells detection helps in improving understandability and maintainability of software
while reducing the chances of system failure. In this study, six machine learning algorithms …

Code smells are the result of not following software engineering principles during software
development, especially in the design and coding phase. It leads to low maintainability. To …

Context Code smells are patterns in source code associated with an increased defect rate
and a higher maintenance effort than usual, but without a clear definition. Code smells are …

Code smells are poor code design or implementation that affect the code maintenance
process and reduce the software quality. Therefore, code smell detection is important in …

Code smell is the structural design defect that makes programs difficult to understand,
maintain, and evolve. Existing works of code smell detection mainly focus on prevalent code …

Detecting code smells may be highly helpful for reducing maintenance costs and raising
source code quality. Code smells facilitate developers or researchers to understand several …

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 …

The violation of the semantic and structural software principles, such as low connection, high
coherence, high understanding, and others, are called anti-patterns, which is one of the …