Defect prediction is commonly used to reduce the effort from the testing phase of software
development. A promising strategy is to use machine learning techniques to predict which …

Defect prediction is a technique introduced to optimize the testing phase of the software
development pipeline by predicting which components in the software may contain defects …

Software defect and code smell prediction help developers identify problems in the code
and fix them before they degrade the quality or the user experience. The prediction of …

The challenge of effective refactoring in the software development cycle brought forward the
need to develop automated defect prediction models. Among many existing indicators of …

Code smell is a software characteristic that indicates bad symptoms in code design which
causes problems related to software quality. The severity of code smells must be measured …

Accepted: 12/May/2019, Published: 31/May/2019 Abstract—Code smells identified by
Fowler [1] is as symptoms of possible code or design problems. Code smells have adverse …

Code smells are poor implementation choices applied during software evolution that can
affect source code maintainability. While several heuristic-based approaches have been …

Several code smells detection tools have been developed providing different results,
because smells can be subjectively interpreted and hence detected in different ways …

Code smell detection is essential to improve software quality, enhancing software
maintainability, and decrease the risk of faults and failures in the software system. In this …

Code smells are generally not considered as bugs; instead, they point out certain
shortcomings in the software design or code. Identification of code smell is a necessary step …