163 citations · 233 across the 8 of their papers we have counts for
8 papers
An Exploratory Study on Code Attention in BERT
Rishab Sharma, Fuxiang Chen, Fatemeh Fard +1
Many recent models in software engineering introduced deep neural models based on the Transformer architecture or use transformer-based Pre-trained Language Models (PLM) trained on…
On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages
Fuxiang Chen, Fatemeh Fard, David Lo +1
A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves high…
On the Effectiveness of Pretrained Models for API Learning
Mohammad Abdul Hadi, Imam Nur Bani Yusuf, Ferdian Thung +4
Developers frequently use APIs to implement certain functionalities, such as parsing Excel Files, reading and writing text files line by line, etc. Developers can greatly benefit f…
Efficient Search of Live-Coding Screencasts from Online Videos
Chengran Yang, Ferdian Thung, David Lo
Programming videos on the Internet are valuable resources for learning programming skills. To find relevant videos, developers typically search online video platforms (e.g., YouTub…
Code Smells in Machine Learning Systems
Jiri Gesi, Siqi Liu, Jiawei Li +6
As Deep learning (DL) systems continuously evolve and grow, assuring their quality becomes an important yet challenging task. Compared to non-DL systems, DL systems have more compl…
PTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained Models
Junda He, Bowen Xu, Zhou Yang +3
Stack Overflow is often viewed as the most influential Software Question Answer (SQA) website with millions of programming-related questions and answers. Tags play a critical role…