e-Informatica Software Engineering Journal (EISEJ)
An international, open access, no authorship fees, blind peer-reviewed journal (indexed by Web of Science ESCI, Scopus, DBLP etc.) that concerns theoretical and practical issues pertaining development of software systems.
Our aim is to focus on experimentation and machine learning in software engineering.
Since Volume 11/2017 all papers are published under Creative Commons CC-BY 4.0 license.
Early bird access to Volume 16/2022:
- Issue 1
- Amal Ahmed Anda, Daniel Amyot, “Self-Adaptation Driven by SysML and Goal Models – A Literature Review“
- Rajdeep Kaur, Kuljit Kaur Chahal, Munish Saini , “Analysis of Factors Influencing Developers’ Sentiments in Commit Logs: Insights from Applying Sentiment Analysis“
- Huynh Khanh Vi Tran, Jürgen Börstler, Nauman bin Ali, Michael Unterkalmsteiner, “How good are my search strings? Reflections on using an existing review as a quasi-gold standard“
- Pooja Sharma, Amrit Lal Sangal, “Examining the Predictive Capability of Advanced Software Fault Prediction Models – An Experimental Investigation Using Combination Metrics“
- Megha Khanna, “A Systematic Review of Ensemble Techniques for Software Defect and Change Prediction“
- Nauman bin Ali, Binish Tanveer, “A Comparison of Citation Sources for Reference and Citation-Based Search in Systematic Literature Reviews“
- Sebastian Ştefan, Virginia Niculescu, “Microservice-Oriented Workload Prediction Using Deep Learning“
- Einav Peretz-Andersson, Richard Torkar , “Empirical AI Transformation Research: A Systematic Mapping Study and Future Agenda” (Preview)
- Deepika Badampudi, Farnaz Fotrousi, Bruno Cartaxo, Muhammad Usman , “Reporting Consent, Anonymity and Confidentiality Procedures Adopted in Empirical Studies Using Human Participants” (Preview)