91 citations · 223 across the 8 of their papers we have counts for
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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…
TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks
Amin Abbasishahkoo, Mahboubeh Dadkhah, Lionel Briand +1
Successful deployment of Deep Neural Networks (DNNs) requires their validation with an adequate test set to ensure a sufficient degree of confidence in test outcomes. Although well…
An Empirical Study of the Characteristics of Popular Minecraft Mods
Daniel Lee, Gopi Krishnan Rajbahadur, Dayi Lin +3
It is becoming increasingly difficult for game developers to manage the cost of developing a game, while meeting the high expectations of gamers. One way to balance the increasing…
Building the perfect game -- an empirical study of game modifications
Daniel Lee, Dayi Lin, Cor-Paul Bezemer +1
Game developers cannot always meet the growing and changing needs of the gaming community, due to the often already overloaded schedules of developers. So-called modders can potent…