### Abstract

Language | English |
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Title of host publication | Electronic Proceedings in Theoretical Computer Science |

Volume | 194 |

Date | 29 Sep 2015 |

Pages | 110-124 |

DOIs | |

Publication status | Published - 29 Sep 2015 |

Event | Quantitative Aspects of Programming Languages and Systems - Queen Mary Unversity of London, London, United Kingdom Duration: 11 Apr 2015 → 12 Apr 2015 http://qapl15.inria.fr/ |

### Conference

Conference | Quantitative Aspects of Programming Languages and Systems |
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Location | Queen Mary Unversity of London |

Country | United Kingdom |

City | London |

Period | 11/04/2015 → 12/04/2015 |

Internet address |

Series | Electronic Proceedings in Theoretical Computer Science |
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Number | 194 |

ISSN | 2075-2180 |

### Cite this

*Electronic Proceedings in Theoretical Computer Science*(Vol. 194, pp. 110-124). Electronic Proceedings in Theoretical Computer Science, No. 194 https://doi.org/10.4204/EPTCS.194.8

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*Electronic Proceedings in Theoretical Computer Science.*vol. 194, Electronic Proceedings in Theoretical Computer Science, no. 194, pp. 110-124, London, United Kingdom, 11/04/2015. https://doi.org/10.4204/EPTCS.194.8

**Probabilistic Output Analysis by Program Manipulation.** / Rosendahl, Mads; Kirkeby, Maja Hanne.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Probabilistic Output Analysis by Program Manipulation

AU - Rosendahl, Mads

AU - Kirkeby, Maja Hanne

PY - 2015/9/29

Y1 - 2015/9/29

N2 - 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.

AB - 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.

UR - http://eptcs.web.cse.unsw.edu.au/paper.cgi?QAPL2015.8

U2 - 10.4204/EPTCS.194.8

DO - 10.4204/EPTCS.194.8

M3 - Article in proceedings

VL - 194

SP - 110

EP - 124

BT - Electronic Proceedings in Theoretical Computer Science

ER -