Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …

Context: Code smell detection is the process of identifying code pieces that are poorly
designed and implemented. Recently more research has been directed towards machine …

Code smells are an indicator of poor design in software systems. Artificial intelligence
techniques have been applied in several ways to improve soft-ware quality in code smells …

Abstract Design smell detection has proven to be an efficient strategy to improve software
quality and consequently decrease maintainability expenses. This work explores the …

Software maintenance is an essential part of any software that finds its use in the day-to-day
activities of any organization. During the maintenance phase bugs detected must be …

Software evolution, an integral part of the software development process, encompasses
frequent and numerous changes and updates that may lead to complex and poor-quality …

Code smells detection primarily adopts heuristic-based, machine learning, and deep
learning approaches, However, to enhance accuracy, most studies employ deep learning …

Bad-smell prediction significantly impacts on software quality. It is beneficial if bad-smell
prediction can be performed as early as possible in the development life cycle. We present …

Background: Defining code smell is not a trivial task. Their recognition tends to be highly
subjective. Nevertheless some code smells detection tools have been proposed. Other …

Code smells refer to poor design and implementation choices by software engineers that
might affect the overall software quality. Code smells detection using machine learning …