Machine learning testing: Survey, landscapes and horizons
This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …
Software engineering for AI-based systems: a survey
AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
Taxonomy of real faults in deep learning systems
The growing application of deep neural networks in safety-critical domains makes the
analysis of faults that occur in such systems of enormous importance. In this paper we …
analysis of faults that occur in such systems of enormous importance. In this paper we …
An empirical study on tensorflow program bugs
Y Zhang, Y Chen, SC Cheung, Y ** deep learning applications
Recent advances in deep learning promote the innovation of many intelligent systems and
applications such as autonomous driving and image recognition. Despite enormous efforts …
applications such as autonomous driving and image recognition. Despite enormous efforts …
A comprehensive study of autonomous vehicle bugs
Self-driving cars, or Autonomous Vehicles (AVs), are increasingly becoming an integral part
of our daily life. About 50 corporations are actively working on AVs, including large …
of our daily life. About 50 corporations are actively working on AVs, including large …
Automatic Static Vulnerability Detection for Machine Learning Libraries: Are We There Yet?
Automatic detection of software security vulnerabilities is critical in software quality
assurance. Many static analysis tools that can help detect security vulnerabilities have been …
assurance. Many static analysis tools that can help detect security vulnerabilities have been …