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Analysis of Decompiled Program Code Using Abstract Syntax Trees
by
Moskvin, D. A.
, Gribkov, N. A.
, Ovasapyan, T. D.
in
Algorithms
/ Apexes
/ Binary codes
/ Cloning
/ Codes
/ Computer Science
/ Control Structures and Microprogramming
/ Fragments
/ Graphs
/ Machine learning
/ Neural networks
/ Open source software
/ Semantics
/ Software development
/ Syntax
2023
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Analysis of Decompiled Program Code Using Abstract Syntax Trees
by
Moskvin, D. A.
, Gribkov, N. A.
, Ovasapyan, T. D.
in
Algorithms
/ Apexes
/ Binary codes
/ Cloning
/ Codes
/ Computer Science
/ Control Structures and Microprogramming
/ Fragments
/ Graphs
/ Machine learning
/ Neural networks
/ Open source software
/ Semantics
/ Software development
/ Syntax
2023
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Do you wish to request the book?
Analysis of Decompiled Program Code Using Abstract Syntax Trees
by
Moskvin, D. A.
, Gribkov, N. A.
, Ovasapyan, T. D.
in
Algorithms
/ Apexes
/ Binary codes
/ Cloning
/ Codes
/ Computer Science
/ Control Structures and Microprogramming
/ Fragments
/ Graphs
/ Machine learning
/ Neural networks
/ Open source software
/ Semantics
/ Software development
/ Syntax
2023
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Analysis of Decompiled Program Code Using Abstract Syntax Trees
Journal Article
Analysis of Decompiled Program Code Using Abstract Syntax Trees
2023
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Overview
This article proposes a method for preprocessing fragments of binary program codes for subsequent detection of their similarity using machine learning methods. The method is based on the analysis of pseudocode obtained as a result of decompiling fragments of binary codes. The analysis is performed using attributed abstract syntax trees (AASTs). As part of the study, testing and comparative analysis of the effectiveness of the developed method are carried out. This method makes it possible to increase the efficiency of detecting functionally similar fragments of program code, compared to analogs, by using the semantic context of vertices in abstract syntax trees.
Publisher
Pleiades Publishing,Springer Nature B.V
Subject
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