About the Journal
Aims and Scope. Journal of Empirical Software Engineering and Analytics provides a focused venue for research on repository mining, defect prediction, developer productivity, empirical methods, replication studies. The journal prioritizes technically substantive, internationally relevant work in which the principal novelty lies inside the stated computing scope rather than only in the application domain.
Core topics in scope include:
- repository mining
- defect prediction
- developer productivity
- empirical methods
- replication studies
- evidence synthesis in software engineering
- empirical software engineering
- software analytics
- mining repositories
- developer studies
Evidence and methodological expectations. Software and programming research should report reproducible artifacts where feasible, explicit research questions or formal claims, appropriate empirical or formal validation, realistic systems or repositories, and evidence that findings generalize beyond a single codebase or development team.
Normally outside scope. Tutorial-style implementations, CRUD applications, framework comparisons without research design, and single-project observations lacking methodological rigor or transferable software-engineering knowledge are normally outside scope.
Research integrity and reproducibility. Authors should disclose datasets, software, model or system configurations, experimental protocols, statistical procedures, ethical approvals where applicable, competing interests, funding, and any material use of generative AI. Data and code should be shared when legally and ethically possible, or the restriction must be explained.
