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Found 4 papers, 1 papers with code
Importance-Driven Deep Learning System Testing
Deep Learning (DL) systems are key enablers for engineering intelligent applications due to their ability to solve complex tasks such as image recognition and machine translation.
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning
Among those, CGF aims to produce new test inputs by fuzzing existing ones to achieve high coverage on a test adequacy criterion (i. e. coverage criterion).
Reinforcement Learning-Driven Test Generation for Android GUI Applications using Formal Specifications
By dynamically executing the Application Under Test (AUT), it learns how to generate a test that satisfies the LTL formula using Reinforcement Learning (RL).
DeepFault: Fault Localization for Deep Neural Networks
Deep Neural Networks (DNNs) are increasingly deployed in safety-critical applications including autonomous vehicles and medical diagnostics.
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