research-article

Emergent, crowd-scale programming practice in the IDE

Authors:

Daniel Steffee,

Joel R. Brandt,

Michael S. BernsteinAuthors Info & Claims

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 2491 - 2500

https://doi.org/10.1145/2556288.2556998

Published: 26 April 2014 Publication History

Abstract

While emergent behaviors are uncodified across many domains such as programming and writing, interfaces need explicit rules to support users. We hypothesize that by codifying emergent programming behavior, software engineering interfaces can support a far broader set of developer needs. To explore this idea, we built Codex, a knowledge base that records common practice for the Ruby programming language by indexing over three million lines of popular code. Codex enables new data-driven interfaces for programming systems: statistical linting, identifying code that is unlikely to occur in practice and may constitute a bug; pattern annotation, automatically discovering common programming idioms and annotating them with metadata using expert crowdsourcing; and library generation, constructing a utility package that encapsulates and reflects emergent software practice. We evaluate these applications to find Codex captures a broad swatch of programming practice, statistical linting detects problematic code snippets, and pattern annotation discovers nontrivial idioms such as basic HTTP authentication and database migration templates. Our work suggests that operationalizing practice-driven knowledge in structured domains such as programming can enable a new class of user interfaces.

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Cited By

Ahmed ASalah AKhoriba GArafa T(2023)Localizing Non-functional Code Bugs in User Interfaces Using Deep Learning TechniquesModel and Data Engineering10.1007/978-3-031-49333-1_27(381-394)Online publication date: 22-Dec-2023
https://doi.org/10.1007/978-3-031-49333-1_27
Kotenko IIzrailov KBuinevich M(2022)Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning ApproachesSensors10.3390/s2204133522:4(1335)Online publication date: 10-Feb-2022
https://doi.org/10.3390/s22041335
Soui MHaddad ZTrabelsi RSrinivasan K(2022)Deep features extraction to assess mobile user interfacesMultimedia Tools and Applications10.1007/s11042-022-11978-181:9(12945-12960)Online publication date: 22-Feb-2022
https://doi.org/10.1007/s11042-022-11978-1
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Index Terms

Emergent, crowd-scale programming practice in the IDE
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2014

4206 pages

ISBN:9781450324731

DOI:10.1145/2556288

General Chairs:
Matt Jones
Swansea University, Wales, UK
,
Philippe Palanque
Université Paul Sabatier, France
,
Program Chairs:
Albrecht Schmidt
University of Stuttgart, Germany
,
Tovi Grossman
Autodesk Research, Canada

Copyright © 2014 ACM.

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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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

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Published: 26 April 2014

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CHI '14: CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2014

Ontario, Toronto, Canada

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CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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https://doi.org/10.1007/978-3-031-49333-1_27
Kotenko IIzrailov KBuinevich M(2022)Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning ApproachesSensors10.3390/s2204133522:4(1335)Online publication date: 10-Feb-2022
https://doi.org/10.3390/s22041335
Soui MHaddad ZTrabelsi RSrinivasan K(2022)Deep features extraction to assess mobile user interfacesMultimedia Tools and Applications10.1007/s11042-022-11978-181:9(12945-12960)Online publication date: 22-Feb-2022
https://doi.org/10.1007/s11042-022-11978-1
Henley ABall JKlein BRutter ALee DErdogmus HMoreno A(2021)An inquisitive code editor for addressing novice programmers' misconceptions of program behaviorProceedings of the 43rd International Conference on Software Engineering: Joint Track on Software Engineering Education and Training10.1109/ICSE-SEET52601.2021.00026(165-170)Online publication date: 25-May-2021
https://dl.acm.org/doi/10.1109/ICSE-SEET52601.2021.00026
Schröder MCito J(2021)An empirical investigation of command-line customizationEmpirical Software Engineering10.1007/s10664-021-10036-y27:2Online publication date: 14-Dec-2021
https://doi.org/10.1007/s10664-021-10036-y
Krishna RGordon MFei-Fei LBernstein M(2021)Visual Intelligence through Human InteractionArtificial Intelligence for Human Computer Interaction: A Modern Approach10.1007/978-3-030-82681-9_9(257-314)Online publication date: 5-Nov-2021
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Zhao YFeng YWang YHao RFang CChen Z(2020)Quality assessment of crowdsourced test casesScience China Information Sciences10.1007/s11432-019-2859-863:9Online publication date: 10-Aug-2020
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Anderson CHübener ISeipp AOhly SDavid KPejovic V(2018)A Survey of Attention Management Systems in Ubiquitous Computing EnvironmentsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142612:2(1-27)Online publication date: 5-Jul-2018
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Allamanis MBarr EDevanbu PSutton C(2018)A Survey of Machine Learning for Big Code and NaturalnessACM Computing Surveys10.1145/321269551:4(1-37)Online publication date: 31-Jul-2018
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Ichinco MKelleher CGiannakos MJaccheri LDivitini M(2018)Semi-automatic suggestion generation for young novice programmers in an open-ended contextProceedings of the 17th ACM Conference on Interaction Design and Children10.1145/3202185.3202762(405-412)Online publication date: 19-Jun-2018
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