RelationalAI is named a Cool Vendor in the May 2022 Gartner Cool Vendors in Augmented Data Management report.

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.

Related Posts

Get Early Access

Join our community, keep up to date with the latest developments in our monthly newsletter, and get early access to RelationalAI.