7. The method of claim 1 , wherein the training codebase comprises a first set of applications and wherein the known vulnerability distribution is based on a manual analysis of a second set of applications.
1. A method for training a classifier, comprising: running an initial security analysis on a training codebase to generate a set of vulnerabilities associated with the training codebase; analyzing a program with a feature set that limits a number of detected vulnerabilities to generate a limited set of vulnerabilities associated with the feature set; comparing the limited set of vulnerabilities to a known vulnerability distribution to generate an accuracy score using a processor; and iterating said steps of analyzing and comparing using different feature sets to find a feature set having a highest accuracy score.