Uncertain〈T〉: A first-order type for Uncertain data

James Bornholt, Todd Mytkowicz, Kathryn S. McKinley

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    80 Citations (Scopus)

    Abstract

    Emerging applications increasingly use estimates such as sensor data (GPS), probabilistic models, machine learning, big data, and human data. Unfortunately, representing this uncertain data with discrete types (floats, integers, and booleans) encourages developers to pretend it is not probabilistic, which causes three types of uncertainty bugs. (1) Using estimates as facts ignores random error in estimates. (2) Computation compounds that error. (3) Boolean questions on probabilistic data induce false positives and negatives. This paper introduces Uncertain〈T〉, a new programming language abstraction for uncertain data. We implement a Bayesian network semantics for computation and conditionals that improves program correctness. The runtime uses sampling and hypothesis tests to evaluate computation and conditionals lazily and efficiently. We illustrate with sensor and machine learning applications that Uncertain〈T〉 improves expressiveness and accuracy. Whereas previous probabilistic programming languages focus on experts, Uncertain〈T〉 serves a wide range of developers. Experts still identify error distributions. However, both experts and application writers compute with distributions, improve estimates with domain knowledge, and ask questions with conditionals. The Uncertain〈T〉 type system and operators encourage developers to expose and reason about uncertainty explicitly, controlling false positives and false negatives. These benefits make Uncertain〈T〉 a compelling programming model for modern applications facing the challenge of uncertainty.

    Original languageEnglish
    Title of host publicationASPLOS 2014 - 19th International Conference on Architectural Support for Programming Languages and Operating Systems
    Pages51-65
    Number of pages15
    DOIs
    Publication statusPublished - 2014
    Event19th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2014 - Salt Lake City, UT, United States
    Duration: 1 Mar 20145 Mar 2014

    Publication series

    NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS

    Conference

    Conference19th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2014
    Country/TerritoryUnited States
    CitySalt Lake City, UT
    Period1/03/145/03/14

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