Natural Language Processing for Requirements Engineering (NLP4RE) is an area of
research and development that seeks to apply natural language processing (NLP) …

With the rise of big data, the quality of datasets has become a crucial factor affecting the
performance of machine learning models. High-quality datasets are essential for the …

Abstract Context: Quality Assessment (QA) of reviewed literature is paramount to a
Systematic Literature Review (SLR) as the quality of conclusions completely depends on the …

Validation of software requirements is a primary phase in requirements engineering that
ensures requirements match the target system with the intended needs of the acquirer. It …

Code smells are sub-optimal implementation choices applied by developers that have the
effect of negatively impacting, among others, the change-proneness of the affected classes …

This study addresses the challenge of requirements-to-code traceability by proposing a
novel model, Genetic Algorithm-XGBoost With Code Dependency (GA-XWCoDe), which …

With the increasing popularity of open-source software development, there is a tremendous
growth of software artifacts that provide insight into how people build software. Researchers …

Requirements-to-code traceability link recovery (RC-TLR) can establish connections
between requirements and target code artifacts, which is critical for the maintenance and …

Today's software systems tend to be long-living and often process security-critical data, so
keeping up with ever-changing security measures, attacks, and mitigations is critical to …

Relations between requirements are part of nearly every requirements engineering
approach. Yet, relations of views, such as requirements documents, are scarcely …