TF-DM: Tool for Studying ML Model Resilience to Data Faults
2021 IEEE/ACM Third International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest)(2021)
Abstract
Machine learning (ML) is widely deployed in safety-critical systems (e.g. self-driving cars). Failures can have disastrous consequences in these systems, and hence ensuring the reliability of its operations is important. Mutation testing is a popular method for assessing the dependability of applications and tools have recently been developed for ML frameworks. However, the focus has been on impro...
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Key words
Data Mutation,Machine Learning,TensorFlow,Error Resilience
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