Points-To Analysis: Provenance Generation
November 2016

The usual points-to analysis does not store the justification for the presence of a tuple in the points-to result. However, this is required for many client driven queries as the provenance information provides information to the client which can be used in other contexts such as debugging. In this presentation, we describe our approach to generate provenance information using the results of a context-sensitive points-to analysis. This has been implemented using the DOOP framework and the Souffle Datalog engine. Our uses cases demand that the approach scale to large code-bases. We use four benchmarks derived from two versions of the JDK and use two realistic clients to demonstrate the effectiveness of our approach.

Authors: Stepan Sindelar, Padmanabhan Krishnan, Bernhard Scholz, Raghavendra Kagalavadi Ramesh, Yi Lu

Venue: To be presented at SAPLING


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