Artifact for ICSE-22 submission "Striking a Balance: Pruning False-Positives from Static Call Graphs"

This artifact contains 2 compressed folders for the code and data that accompanies the paper. <strong>Code</strong> The <em>Readme</em> in the code details the dependencies as well as the instruction on how to run the train and test-phases for the tool, and reproduce the main experimental results. The <em>final-experiments</em> folder contains per-benchmark results for the paper. <strong>Data</strong> This includes the following: 1) Benchmark-set (copied from NJR-1) 2) Pre-computed call-graphs 3) Pre-trained models for the cg-pruner 4) Null-pointer classification results 5) Train and test program lists