7 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models
Yalin Liu, Kosay Jabre, Rui Abreu +10
Predictions by machine learning (ML) and artificial intelligence (AI) models are often received skeptically unless they are paired with intelligible explanations. In the context of…
Generating and Visualizing Trace Link Explanations
Yalin Liu, Jinfeng Lin, Oghenemaro Anuyah +2
Recent breakthroughs in deep-learning (DL) approaches have resulted in the dynamic generation of trace links that are far more accurate than was previously possible. However, DL-ge…
Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models
Jinfeng Lin, Yalin Liu, Qingkai Zeng +2
Software traceability establishes and leverages associations between diverse development artifacts. Researchers have proposed the use of deep learning trace models to link natural…
Traceability Support for Multi-Lingual Software Projects
Yalin Liu, Jinfeng Lin, Jane Cleland-Huang
Software traceability establishes associations between diverse software artifacts such as requirements, design, code, and test cases. Due to the non-trivial costs of manually creat…