6 citations · 6 across the 2 of their papers we have counts for
5 papers
Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmap
Ahmed E. Hassan, Gustavo A. Oliva, Dayi Lin +3
The rise of AI-assisted software engineering (SE 2.0), powered by Foundation Models (FMs) and FM-powered coding assistants, has shown promise in improving developer productivity. H…
SimClone: Detecting Tabular Data Clones using Value Similarity
Xu Yang, Gopi Krishnan Rajbahadur, Dayi Lin +3
Data clones are defined as multiple copies of the same data among datasets. Presence of data clones between datasets can cause issues such as difficulties in managing data assets a…
Rethinking Software Engineering in the Foundation Model Era: From Task-Driven AI Copilots to Goal-Driven AI Pair Programmers
Ahmed E. Hassan, Gustavo A. Oliva, Dayi Lin +3
The advent of Foundation Models (FMs) and AI-powered copilots has transformed the landscape of software development, offering unprecedented code completion capabilities and enhanci…
Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting
Hao Li, Gopi Krishnan Rajbahadur, Dayi Lin +3
In software engineering, deep learning models are increasingly deployed for critical tasks such as bug detection and code review. However, overfitting remains a challenge that affe…
On the Model Update Strategies for Supervised Learning in AIOps Solutions
Yingzhe Lyu, Heng Li, Zhen Ming +2
AIOps (Artificial Intelligence for IT Operations) solutions leverage the massive data produced during the operation of large-scale systems and machine learning models to assist sof…