papers

Publications (5)

cs.SE2020

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…

cs.SE2021

Problems with SZZ and Features: An empirical study of the state of practice of defect prediction data collection

Steffen Herbold, Alexander Trautsch, Fabian Trautsch +1

Context: The SZZ algorithm is the de facto standard for labeling bug fixing commits and finding inducing changes for defect prediction data. Recent research uncovered potential pro…

cs.SE2021

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…

cs.SE2022

Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP

Benjamin Ledel, Steffen Herbold

Context: The identification of bugs within the reported issues in an issue tracker is crucial for the triage of issues. Machine learning models have shown promising results regardi…

cs.SE2021

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…