Prior works have developed transformer-based language learning models to automatically
generate source code for a task without compilation errors. The datasets used to train these …

Context: Architecture of a software system represents the key design decisions and therefore
its quality plays an important role to keep the software maintainable. Code smells are …

The current era demands high quality software in a limited time period to achieve new goals
and heights. To meet user requirements, the source codes undergo frequent modifications …

In recent years, the evolution of software ecosystems and the detection of technical debt
received significant attention by researchers from both industry and academia. While a few …

Code smells are symptoms of poor design and implementation choices, which might hinder
comprehension, increase code complexity and fault-proneness and decrease …

Abstract Context: Code Smells—a concept not fully understood among programmers, crucial
to the code quality, and yet unstandardized in the scientific literature. Objective: Goal (# 1) …

Purpose Code smells indicate deep software issues. They have been studied by
researchers with different perspectives. The need to study code smells was felt from the …

Researchers apply machine-learning techniques for code smell detection to counter the
subjectivity of many code smells. Such approaches need a large, manually annotated …

Code Smells have been detected, predicted and studied by researchers from several
perspectives. This literature review is conducted to understand tools and algorithms used to …

Background: Software smells reflect the sub-optimal patterns in the software. In a similar
way, community smells consider the sub-optimal patterns in the organizational and social …