7 citations · 20 across the 10 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.SE2021★ 3 cited
Measuring Discrimination to Boost Comparative Testing for Multiple Deep Learning Models
Linghan Meng, Yanhui Li, Lin Chen +4
The boom of DL technology leads to massive DL models built and shared, which facilitates the acquisition and reuse of DL models. For a given task, we encounter multiple DL models a…
cs.SE2021
Mutant reduction evaluation: what is there and what is missing?
Peng Zhang, Yang Wang, Xutong Liu +6
Background. Many mutation reduction strategies, which aim to reduce the number of mutants, have been proposed. Problem. It is important to measure the ability of a mutation reducti…
cs.SE2021★ 2 cited
An extensive empirical study of inconsistent labels in multi-version-project defect data sets
Shiran Liu, Zhaoqiang Guo, Yanhui Li +4
The label quality of defect data sets has a direct influence on the reliability of defect prediction models. In this study, for multi-version-project defect data sets, we propose a…