47 citations · 94 across the 8 of their papers we have counts for
5 papers · 1 filter
An empirical study of testing machine learning in the wild
Moses Openja, Foutse Khomh, Armstrong Foundjem +4
Recently, machine and deep learning (ML/DL) algorithms have been increasingly adopted in many software systems. Due to their inductive nature, ensuring the quality of these systems…
Bugs in Machine Learning-based Systems: A Faultload Benchmark
Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh +2
The rapid escalation of applying Machine Learning (ML) in various domains has led to paying more attention to the quality of ML components. There is then a growth of techniques and…
Towards a Change Taxonomy for Machine Learning Systems
Aaditya Bhatia, Ellis E. Eghan, Manel Grichi +4
Machine Learning (ML) research publications commonly provide open-source implementations on GitHub, allowing their audience to replicate, validate, or even extend machine learning…
Towards Build Verifiability for Java-based Systems
Jiawen Xiong, Yong Shi, Boyuan Chen +3
Build verifiability refers to the property that the build of a software system can be verified by independent third parties and it is crucial for the trustworthiness of a software…
An Exploratory Study on Machine Learning Model Stores
Minke Xiu, Zhen Ming, Jiang +1
Recent advances in Artificial Intelligence, especially in Machine Learning (ML), have brought applications previously considered as science fiction (e.g., virtual personal assistan…