57 citations · 254 across the 24 of their papers we have counts for
5 papers · 1 filter
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…
Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects
Steffen Herbold, Tobias Haar
Machine learning is nowadays a standard technique for data analysis within software applications. Software engineers need quality assurance techniques that are suitable for these n…
On the feasibility of automated prediction of bug and non-bug issues
Steffen Herbold, Alexander Trautsch, Fabian Trautsch
Context: Issue tracking systems are used to track and describe tasks in the development process, e.g., requested feature improvements or reported bugs. However, past research has s…
With Registered Reports Towards Large Scale Data Curation
Steffen Herbold
The scale of manually validated data is currently limited by the effort that small groups of researchers can invest for the curation of such data. Within this paper, we propose the…
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…