Making More with Less: Improving Software Testing Outcomes Using a Cross-Project and Cross-Language ML Classifier Based on Cost-Sensitive Training
As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of softwar...
Main Authors: | Nascimento, Alexandre M., Shimanuki, Gabriel Kenji G., Dias, Luiz Alberto V. |
---|---|
Format: | Article |
Published: |
MDPI AG
2024
|
Online Access: | https://hdl.handle.net/1721.1/155268 |
Similar Items
-
Doing more with less: characterizing dataset downsampling for AutoML
by: Zogaj, Fatjon, et al.
Published: (2022) -
SKCV: Stratified K-fold cross-validation on ML classifiers for predicting cervical cancer
by: Sashikanta Prusty, et al.
Published: (2022-08-01) -
TinyML Gamma Radiation Classifier
by: Moez Altayeb, et al.
Published: (2023-02-01) -
Microglial APOE4: more is less and less is more
by: Ghazaleh Eskandari-Sedighi, et al.
Published: (2023-12-01) -
Resolving Voter Registration Problems: Making Registration Easier, Less Costly and More Accurate
by: Alvarez, R. Michael, et al.
Published: (2015)