e-Informatica Software Engineering Journal (EISEJ)
An international, open access, no authorship fees, blind peer-reviewed journal indexed by Web of Science, 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 will be published under Creative Commons CC-BY 4.0 license.
Current Volume 11/2017:
- Issue 1
- ECLogger: Cross-Project Catch-Block Logging Prediction using Ensemble of Classifiers
- Experience Report: Introducing Kanban Into Automotive Software Project
- Systematic Literature Review on Search Based Mutation Testing
- Efficiency of Software Testing Techniques: A Controlled Experiment Replication and Network Meta-analysis
- NRFixer: Sentiment Based Model for Predicting the Fixability of Non-Reproducible Bugs
- Machine Learning or Information Retrieval Techniques for Bug Triaging: Which is better?