Empirical studies on the impact of filter‐based ranking feature selection on security vulnerability prediction
Abstract Security vulnerability prediction (SVP) can construct models to identify potentially vulnerable program modules via machine learning. Two kinds of features from different points of view are used to measure the extracted modules in previous studies. One kind considers traditional software me...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | IET Software |
| Online Access: | https://doi.org/10.1049/sfw2.12006 |