5 papers · 1 filter
Grounding Deep Learning Framework Testing in Data Flow
Jiatao Ge, Yanzhou Mu, Yinglong Zou +3
Data flow underlies deep learning (DL) framework execution, including automatic differentiation and operator-fusion optimization. Bugs involving data flow can cause incorrect resul…
Scalpel: Automotive Deep Learning Framework Testing via Assembling Model Components
Yinglong Zou, Juan Zhai, Chunrong Fang +3
Deep learning (DL) plays a key role in autonomous driving systems. DL models support perception modules, equipped with tasks such as object detection and sensor fusion. These DL mo…
DevMuT: Testing Deep Learning Framework via Developer Expertise-Based Mutation
Yanzhou Mu, Juan Zhai, Chunrong Fang +6
Deep learning (DL) frameworks are the fundamental infrastructure for various DL applications. Framework defects can profoundly cause disastrous accidents, thus requiring sufficient…
Deep Learning Framework Testing via Heuristic Guidance Based on Multiple Model Measurements
Yinglong Zou, Juan Zhai, Chunrong Fang +3
Deep learning frameworks serve as the foundation for developing and deploying deep learning applications. To enhance the quality of deep learning frameworks, researchers have propo…
Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment
Yinglong Zou, Juan Zhai, Chunrong Fang +3
In recent years, Deep Learning (DL) applications in JavaScript environment have become increasingly popular. As the infrastructure for DL applications, JavaScript DL frameworks pla…