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Metafor: visualizing stories as code

Published: 10 January 2005 Publication History

Abstract

Every program tells a story. Programming, then, is the art of constructing a story about the objects in the program and what they do in various situations. So-called programming languages, while easy for the computer to accurately convert into code, are, unfortunately, difficult for people to write and understand.We explore the idea of using descriptions in a natural language as a representation for programs. While we cannot yet convert arbitrary English to fully specified code, we can use a reasonably expressive subset of English as a visualization tool. Simple descriptions of program objects and their behavior generate scaffolding (underspecified) code fragments, that can be used as feedback for the designer. Roughly speaking, noun phrases can be interpreted as program objects; verbs can be functions, adjectives can be properties. A surprising amount of what we call programmatic semantics can be inferred from linguistic structure. We present a program editor, Metafor, that dynamically converts a user's stories into program code, and in a user study, participants found it useful as a brainstorming tool.

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Amy Bruckman: 1997, MOOSE Crossing. PhD Thesis, MIT.
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Henry Lieberman and Hugo Liu: 2004a, Feasibility Studies for Programming in Natural Language. In Lieberman, Paterno & Wulf (Eds.) End-User Development. Kluwer.
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Hugo Liu: 2004a, MontyLingua v2.1 Free Natural Language Understanding Toolkit and API available at: http://web.media.mit.edu/~hugo/montylingua/
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Hugo Liu and Henry Lieberman: 2004b, Toward a Programmatic Semantics of Natural Language. Proceedings of the 20th IEEE Symposium on Visual Languages and Human-Centric Computing. IEEE Computer Society Press.
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Hugo Liu and Push Singh: 2004b, ConceptNet: A Practical Commonsense Reasoning Toolkit. BT Technology Journal 22(4). Kluwer.
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J.F. Pane, C.A. Ratanamahatana, & B.A. Myers: 2001, Studying the Language and Structure in Non-Programmers' Solutions to Programming Problems. International Journal of Human-Computer Studies, 54(2), 237--264.
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  • (2021)Breaking Down High-Level Robot Path-Finding Abstractions in Natural Language ProgrammingAIxIA 2020 – Advances in Artificial Intelligence10.1007/978-3-030-77091-4_18(280-297)Online publication date: 22-May-2021
  • (2020)Towards Programming in Natural Language: Learning New Functions from Spoken UtterancesInternational Journal of Semantic Computing10.1142/S1793351X2040009714:02(249-272)Online publication date: 23-Sep-2020
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Published In

cover image ACM Conferences
IUI '05: Proceedings of the 10th international conference on Intelligent user interfaces
January 2005
344 pages
ISBN:1581138946
DOI:10.1145/1040830
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2005

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Author Tags

  1. case tools
  2. natural language programming
  3. storytelling

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IUI05
IUI05: Tenth International Conference on Intelligent User Interfaces
January 10 - 13, 2005
California, San Diego, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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  • (2024)DOĞAL DİL METİNLERİNDEN PROGRAMLAMA DİLİ KODU OLUŞTURMA ÇALIŞMALARI: BİR DERLEME ÇALIŞMASIİstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi10.55071/ticaretfbd.1354040Online publication date: 21-Mar-2024
  • (2021)Breaking Down High-Level Robot Path-Finding Abstractions in Natural Language ProgrammingAIxIA 2020 – Advances in Artificial Intelligence10.1007/978-3-030-77091-4_18(280-297)Online publication date: 22-May-2021
  • (2020)Towards Programming in Natural Language: Learning New Functions from Spoken UtterancesInternational Journal of Semantic Computing10.1142/S1793351X2040009714:02(249-272)Online publication date: 23-Sep-2020
  • (2020)Context Classification in Dialog-Based Interaction2020 IEEE 14th International Conference on Semantic Computing (ICSC)10.1109/ICSC.2020.00038(185-189)Online publication date: Feb-2020
  • (2020)Roger that! Learning How Laypersons Teach New Functions to Intelligent Systems2020 IEEE 14th International Conference on Semantic Computing (ICSC)10.1109/ICSC.2020.00020(93-100)Online publication date: Feb-2020
  • (2020)Evolution of Naturalistic Programming: A NeedNew Perspectives in Software Engineering10.1007/978-3-030-63329-5_13(185-198)Online publication date: 7-Nov-2020
  • (2019)ParlAmI: A Multimodal Approach for Programming Intelligent EnvironmentsTechnologies10.3390/technologies70100117:1(11)Online publication date: 11-Jan-2019
  • (2019)A Model for Naturalistic Programming with ImplementationApplied Sciences10.3390/app91839369:18(3936)Online publication date: 19-Sep-2019
  • (2019)VajraProceedings of the 24th International Conference on Intelligent User Interfaces10.1145/3301275.3302267(30-39)Online publication date: 17-Mar-2019
  • (2019)Dialog-Based Meaning Derivation Service for Technical Language Domains2019 IEEE 13th International Conference on Semantic Computing (ICSC)10.1109/ICOSC.2019.8665513(375-380)Online publication date: Jan-2019
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