47 citations · 94 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
Has Your FaaS Application Been Decommissioned Yet? -- A Case Study on the Idle Timeout in Function as a Service Infrastructure
Kim Long Ngo, Joydeep Mukherjee, Zhen Ming Jiang +1
Function as a Service (FaaS) is a new cloud technology with automated resource management. Different from traditional cloud computing, each FaaS cloud function can only run a fixed…
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…
Towards Training Reproducible Deep Learning Models
Boyuan Chen, Mingzhi Wen, Yong Shi +4
Reproducibility is an increasing concern in Artificial Intelligence (AI), particularly in the area of Deep Learning (DL). Being able to reproduce DL models is crucial for AI-based…
Towards a consistent interpretation of AIOps models
Yingzhe Lyu, Gopi Krishnan Rajbahadur, Dayi Lin +3
Artificial Intelligence for IT Operations (AIOps) has been adopted in organizations in various tasks, including interpreting models to identify indicators of service failures. To a…