Artefact for the paper "Real-World Fault Detection for C-Extended Python Projects with Automated Unit Test Generation"
Berg, Lucas; Krodinger, Lukas; Lukasczyk, Stephan; Panichella, Annibale; Fraser, Gordon; Vanhoof, Wim; Devroey, Xavier;
Artefact for the paper "Real-World Fault Detection for C-Extended Python Projects with Automated Unit Test Generation"
This artefact provides the raw experiment data, analysis scripts, and infrastructure code needed to reproduce the results presented in the paper "Real-World Fault Detection for C-Extended Python Projects with Automated Unit Test Generation".
- Delft University of Technology Netherlands
- Namur Digital Institute Belgium
- University of Passau Germany
python, c-extension, subprocess, foreign function interface, test generation, fault detection
python, c-extension, subprocess, foreign function interface, test generation, fault detection
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
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