The accuracy reported for code smell-detecting tools varies depending on the dataset used
to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a …

Background: The migration from a monolithic system to microservices requires a deep
refactoring of the system. Therefore, such a migration usually has a big economic impact …

The popularity of tools for analyzing Technical Debt, and particularly the popularity of
SonarQube, is increasing rapidly. SonarQube proposes a set of coding rules, which …

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 …

Context Research on code smells accelerates and there are many studies that discuss them
in the machine learning context. However, while data sets used by researchers vary in …

Many software processes advocate that the test code should co-evolve with the production
code. Prior work usually studies such co-evolution based on production-test co-evolution …

Technical Debt (TD) is a successful metaphor in conveying the consequences of software
inefficiencies and their elimination to both technical and non-technical stakeholders …

Context: Companies frequently invest effort to remove technical issues believed to impact
software qualities, such as removing anti-patterns or coding styles violations. Objective: We …

The concept of technical debt has been explored from many perspectives but its precise
estimation is still under heavy empirical and experimental inquiry. We aim to understand …

Common software vulnerabilities can result in severe security breaches, financial losses,
and reputation deterioration and require research effort to improve software security. The …