Work

Probabilistic Output Analysis by Program Manipulation

Year: 2015

Type: article

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.

Source: Electronic Proceedings in Theoretical Computer Science

DOI: 10.4204/eptcs.194.8

Authors: Mads Rosendahl, Maja H. Kirkeby

Institution: Roskilde University

Language: English

Topic: Logic, programming, and type systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: European Commission

Awards: G3207356259, G393177772, G5702163051, Whole-Systems Energy Transparency