Search Results for author:
Found 7 papers, 3 papers with code
Is ChatGPT the Ultimate Programming Assistant -- How far is it?
To assess the feasibility of using an LLM as a useful assistant bot for programmers, we must assess its realistic capabilities on unseen problems as well as its capabilities on various tasks.
COMET: Coverage-guided Model Generation For Deep Learning Library Testing
Techniques have been proposed to generate various DL models and apply them to test these libraries.
DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs
Besides, for fault localization, DeepFD also outperforms the existing works, correctly locating 42% faulty programs, which almost doubles the best result (23%) achieved by the existing works.
Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications
To this end, we propose DFLARE, a novel, search-based, black-box testing technique to automatically find triggering inputs that result in deviated behaviors in image classification tasks.
Hero: On the Chaos When PATH Meets Modules
The results showed that \textsc{Hero} achieved a high detection rate of 98. 5\% on a DM issue benchmark and found 2, 422 new DM issues in 2, 356 popular Golang projects.
Software Engineering
SemMT: A Semantic-based Testing Approach for Machine Translation Systems
SemMT applies round-trip translation and measures the semantic similarity between the original and translated sentences.
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations
The corresponding rate for the object detection models is over 8. 5%.
