76 citations · 129 across the 23 of their papers we have counts for
9 papers · 1 filter
Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes
Cedric Richter, Heike Wehrheim
Real bug fixes found in open source repositories seem to be the perfect source for learning to localize and repair real bugs. However, the absence of large scale bug fix collection…
TSSB-3M: Mining single statement bugs at massive scale
Cedric Richter, Heike Wehrheim
Single statement bugs are one of the most important ingredients in the evaluation of modern bug detection and automatic program repair methods. By affecting only a single statement…
DeepMutants: Training neural bug detectors with contextual mutations
Cedric Richter, Heike Wehrheim
Learning-based bug detectors promise to find bugs in large code bases by exploiting natural hints such as names of variables and functions or comments. Still, existing techniques t…
MLCheck- Property-Driven Testing of Machine Learning Models
Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo +1
In recent years, we observe an increasing amount of software with machine learning components being deployed. This poses the question of quality assurance for such components: how…
Cooperative Verification via Collective Invariant Generation
Jan Haltermann, Heike Wehrheim
Software verification has recently made enormous progress due to the development of novel verification methods and the speed-up of supporting technologies like SMT solving. To keep…
Verification Artifacts in Cooperative Verification: Survey and Unifying Component Framework
Dirk Beyer, Heike Wehrheim
The goal of cooperative verification is to combine verification approaches in such a way that they work together to verify a system model. In particular, cooperative verifiers prov…