In this paper, our aim is to propose a model for code abstraction, based on abstract interpretation, allowing us to improve the precision of a recently proposed static analysis by abstract interpretation of dynamic languages. The problem we tackle here is that the analysis may add some spurious code to the string-to-execute abstract value and this code may need some abstract representations in order to make it analyzable. This is precisely what we propose here, where we drive the code abstraction by the analysis we have to perform.

Improving dynamic code analysis by code abstraction / Mastroeni, I.; Arceri, V.. - 341:(2021), pp. 17-32. ((Intervento presentato al convegno 9th International Workshop on Verification and Program Transformation, VPT 2021 tenutosi a lux nel 2021 [10.4204/EPTCS.341.2].

Improving dynamic code analysis by code abstraction

Arceri V.
2021

Abstract

In this paper, our aim is to propose a model for code abstraction, based on abstract interpretation, allowing us to improve the precision of a recently proposed static analysis by abstract interpretation of dynamic languages. The problem we tackle here is that the analysis may add some spurious code to the string-to-execute abstract value and this code may need some abstract representations in order to make it analyzable. This is precisely what we propose here, where we drive the code abstraction by the analysis we have to perform.
Improving dynamic code analysis by code abstraction / Mastroeni, I.; Arceri, V.. - 341:(2021), pp. 17-32. ((Intervento presentato al convegno 9th International Workshop on Verification and Program Transformation, VPT 2021 tenutosi a lux nel 2021 [10.4204/EPTCS.341.2].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2899278
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