6 papers
On the Effectiveness of Code Representation in Deep Learning-Based Automated Patch Correctness Assessment
Quanjun Zhang, Haichuan Hu, Chunrong Fang +5
Automated program repair (APR) attempts to generate correct patches and has drawn wide attention from both academia and industry in the past decades. However, APR is continuously s…
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…
Improving Retrieval-Augmented Deep Assertion Generation via Joint Training
Quanjun Zhang, Chunrong Fang, Yi Zheng +7
Unit testing attempts to validate the correctness of basic units of the software system under test and has a crucial role in software development and testing. Very recent work prop…
Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models
Quanjun Zhang, Chunrong Fang, Yi Zheng +7
Unit testing validates the correctness of the units of the software system under test and serves as the cornerstone in improving software quality and reliability. To reduce manual…
Continuous Concepts Removal in Text-to-image Diffusion Models
Tingxu Han, Weisong Sun, Yanrong Hu +6
Text-to-image diffusion models have shown an impressive ability to generate high-quality images from input textual descriptions. However, concerns have been raised about the potent…
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…