{"paper":{"title":"Probabilistic Output Analysis by Program Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Denmark), Mads Rosendahl (Roskilde University, Maja H. Kirkeby (Roskilde University","submitted_at":"2015-09-29T02:11:11Z","abstract_excerpt":"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 t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.08566","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}