40 citations · 70 across the 7 of their papers we have counts for
12 papers · 1 filter
On Using Information Retrieval to Recommend Machine Learning Good Practices for Software Engineers
Laura Cabra-Acela, Anamaria Mojica-Hanke, Mario Linares-Vásquez +1
Machine learning (ML) is nowadays widely used for different purposes and in several disciplines. From self-driving cars to automated medical diagnosis, machine learning models exte…
Predicting Issue Types with seBERT
Alexander Trautsch, Steffen Herbold
Pre-trained transformer models are the current state-of-the-art for natural language models processing. seBERT is such a model, that was developed based on the BERT architecture, b…
Broccoli: Bug localization with the help of text search engines
Benjamin Ledel, Steffen Herbold
Bug localization is a tedious activity in the bug fixing process in which a software developer tries to locate bugs in the source code described in a bug report. Since this process…
MSR Mining Challenge: The SmartSHARK Repository Mining Data
Alexander Trautsch, Fabian Trautsch, Steffen Herbold
The SmartSHARK repository mining data is a collection of rich and detailed information about the evolution of software projects. The data is unique in its diversity and contains de…
A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits
Steffen Herbold, Alexander Trautsch, Benjamin Ledel +45
Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only…
The SmartSHARK Ecosystem for Software Repository Mining
Alexander Trautsch, Fabian Trautsch, Steffen Herbold +2
Software repository mining is the foundation for many empirical software engineering studies. The collection and analysis of detailed data can be challenging, especially if data sh…