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Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT.

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Title: Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT.
Authors: Pujar, Saurabh1, saurabh.pujar@ibm.com, Zheng, Yunhui1, Buratti, Luca1, Lewis, Burn1, Chen, Yunchung2, Laredo, Jim1, Morari, Alessandro1, Epstein, Edward1, Lin, Tsungnan2, Yang, Bo3, Su, Zhong3
Source: Empirical Software Engineering; Apr2024, Vol. 29 Issue 2, p1-38, 38p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 175622747
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT.
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  Data: <searchLink fieldCode="JN" term="%22Empirical+Software+Engineering%22">Empirical Software Engineering</searchLink>; Apr2024, Vol. 29 Issue 2, p1-38, 38p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=175622747
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        Value: 10.1007/s10664-023-10405-9
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              Text: Apr2024
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              Y: 2024
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