Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Validating a deep learning framework by metamorphic testing
Metamorphic Testing: A New Approach for Generating Next Test Cases
Machine Learning-based Software Testing: Towards a Classification Framework
DeepFlow: a deep learning framework for software-defined measurement
XEMU: an efficient QEMU based binary mutation testing framework for embedded software
An Analysis and Survey of the Development of Mutation Testing
A framework for practical, automated black-box testing of component-based software
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing
Comparative Study of Deep Learning Software Frameworks
An automated framework for software test oracle
SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities
DeepTest: automated testing of deep-neural-network-driven autonomous cars
Pallas: Semantic-Aware Checking for Finding Deep Bugs in Fast Path
Automatic Mutation Test Case Generation via Dynamic Symbolic Execution
Using Machine Learning to Refine Black-Box Test Specifications and Test Suites
Simulated penetration testing: from Dijkstra to Turing Test++
DeepRoad: GAN-based Metamorphic Autonomous Driving System Testing
Combining unit-level symbolic execution and system-level concrete execution for testing nasa software
Machine Learning and Evolutionary Computing for GUI-based Regression Testing
Evaluating Symbolic Execution-Based Test Tools
A survey of deep-learning frameworks
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks
Openfst: a general and efficient weighted finite-state transducer library
An implementation of optimized framework for action classification using multilayers neural network on selected fused features
Revisiting the biology of infant t(4;11)/MLL-AF4+ B-cell acute lymphoblastic leukemia