Defensive Points-To Analysis: Effective Soundness via Laziness
RelationalAI
01 January 2018
less than a minute read
Defensive Points-To Analysis: Effective Soundness via Laziness
We present a defensive may-point-to analysis approach, which offers soundness even in the presence of arbitrary opaque code.
Authors: Yannis Smaragdakis, George Kastrinis´. 2018.
In Proceedings of the 32nd European Conference on Object-Oriented Programming (ECOOP ‘18).
We present a defensive may-point-to analysis approach, which offers soundness even in the presence of arbitrary opaque code: all non-empty points-to sets computed are guaranteed to be over-approximations of the sets of values arising at run time. A key design tenet of the analysis is laziness: the analysis computes points-to relationships only for variables or objects that are guaranteed to never escape into opaque code.
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