In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

With the growth of software systems, logs have become an important data to aid system
maintenance. Log-based anomaly detection is one of the most important methods for such …

Incident management for cloud services is a complex process involving several steps and
has a huge impact on both service health and developer productivity. On-call engineers …

Deep learning (DL) techniques are rapidly developed and have been widely adopted in
practice. However, similar to traditional software systems, DL systems also contain bugs …

Deep Neural Network (DNN) testing is one of the most widely-used ways to guarantee the
quality of DNNs. However, labeling test inputs to check the correctness of DNN prediction is …

Root Cause Analysis (RCA) plays a pivotal role in the incident diagnosis process for cloud
services, requiring on-call engineers to identify the primary issues and implement corrective …

The management of cloud service incidents (unplanned interruptions or outages of a
service/product) greatly affects customer satisfaction and business revenue. After years of …

Deep learning (DL) techniques are proven effective in many challenging tasks, and become
widely-adopted in practice. However, previous work has shown that DL libraries, the basis of …

In large-scale cloud service systems, monitoring metric data and conducting anomaly
detection is an important way to maintain reliability and stability. However, great disparity …

Cloud systems have become increasingly popular in recent years due to their flexibility and
scalability. Each time cloud computing applications and services hosted on the cloud are …