Proj CDeepFuzz Paper Reading: Regression Fuzzing for Deep Learning Systems
Abstract
本文：DRFuzz
Task: find the regression faults between versions of a DL system
Method:
- a diversity-oriented test criterion to explore as many faulty behaviors as possible(⼀种⾯向多样性的测试标准来探索尽可能多的错误⾏为).
- 基于GAN的fidelity保证机制
实验：
数据集：四个回归场景（补充训练、对抗训练、模型修复和模型剪枝）中的四个主题(MNIST LeNet-5, CIFAR10 VGG16, Fashion-MNIST AlexNet, SVHN ResNet18)
竞争对象：DiffChaser, DeepHunter
效果：在检测到的回归错误数量⽅⾯平均提⾼了 1,177% 和 539%。