Probabilistic Output Analysis by Program Manipulation
Abstract
The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability function as a possibly uncomputable expression in an intermediate language. This program is then analyzed, transformed, and approximated. The result is a closed form expression that computes an over approximation of the output probability distribution for the program. We focus on programs where the possible input follows a known probability distribution. Tests in programs are not assumed to satisfy the Markov property of having fixed branching probabilities independently of previous history.
Cite
@article{arxiv.1509.08566,
title = {Probabilistic Output Analysis by Program Manipulation},
author = {Mads Rosendahl and Maja H. Kirkeby},
journal= {arXiv preprint arXiv:1509.08566},
year = {2015}
}
Comments
In Proceedings QAPL 2015, arXiv:1509.08169