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BinSleuth: Scalable vulnerability discovery in binaries via automated source identification and path optimization.

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Τίτλος: BinSleuth: Scalable vulnerability discovery in binaries via automated source identification and path optimization.
Συγγραφείς: Liu, Jie1 (AUTHOR) liujie_ran@bupt.edu.cn, Zou, Shun1 (AUTHOR) zous@bupt.edu.cn, Liang, Hongliang1 (AUTHOR) hliang@bupt.edu.cn
Πηγή: Journal of Systems & Software. Oct2026, Vol. 240, pN.PAG-N.PAG. 1p.
Θεματικοί όροι: *Mathematical optimization, Compilers (Computer programs), Penetration testing (Computer security)
Βάση Δεδομένων: Business Source Index
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  – Url: https://www.doi.org/10.1016/j.jss.2026.112933?
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PubType: Academic Journal
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.jss.2026.112933
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Compilers (Computer programs)
        Type: general
      – SubjectFull: Penetration testing (Computer security)
        Type: general
    Titles:
      – TitleFull: BinSleuth: Scalable vulnerability discovery in binaries via automated source identification and path optimization.
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          Name:
            NameFull: Liu, Jie
      – PersonEntity:
          Name:
            NameFull: Zou, Shun
      – PersonEntity:
          Name:
            NameFull: Liang, Hongliang
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          Dates:
            – D: 01
              M: 10
              Text: Oct2026
              Type: published
              Y: 2026
          Identifiers:
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              Value: 01641212
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            – Type: volume
              Value: 240
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            – TitleFull: Journal of Systems & Software
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