A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability
In the past few years, significant progress has been made on deep neural networks (DNNs)
in achieving human-level performance on several long-standing tasks. With the broader …
in achieving human-level performance on several long-standing tasks. With the broader …
[HTML][HTML] Testing machine learning based systems: a systematic mapping
Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …
one or more components that learn how to perform a task from a given data set. The …
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 …
Deephunter: a coverage-guided fuzz testing framework for deep neural networks
The past decade has seen the great potential of applying deep neural network (DNN) based
software to safety-critical scenarios, such as autonomous driving. Similar to traditional …
software to safety-critical scenarios, such as autonomous driving. Similar to traditional …
Assuring the machine learning lifecycle: Desiderata, methods, and challenges
R Ashmore, R Calinescu, C Paterson - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Machine learning has evolved into an enabling technology for a wide range of highly
successful applications. The potential for this success to continue and accelerate has placed …
successful applications. The potential for this success to continue and accelerate has placed …
Securing connected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward
Connected and autonomous vehicles (CAVs) will form the backbone of future next-
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
Deep learning library testing via effective model generation
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 …
practice. However, similar to traditional software systems, DL systems also contain bugs …
Testing deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
Deepxplore: Automated whitebox testing of deep learning systems
Deep learning (DL) systems are increasingly deployed in safety-and security-critical
domains including self-driving cars and malware detection, where the correctness and …
domains including self-driving cars and malware detection, where the correctness and …