Article

WitchDoctor: IDE support for real-time auto-completion of refactorings

Authors:

Stephen R. Foster,

William G. Griswold,

Sorin LernerAuthors Info & Claims

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

Pages 222 - 232

Published: 02 June 2012 Publication History

Abstract

Integrated Development Environments (IDEs) have come to perform a wide variety of tasks on behalf of the programmer, refactoring being a classic example. These operations have undeniable benefits, yet their large (and growing) number poses a cognitive scalability problem. Our main contribution is WitchDoctor -- a system that can detect, on the fly, when a programmer is hand-coding a refactoring. The system can then complete the refactoring in the background and propose it to the user long before the user can complete it. This implies a number of technical challenges. The algorithm must be 1) highly efficient, 2) handle unparseable programs, 3) tolerate the variety of ways programmers may perform a given refactoring, 4) use the IDE's proven and familiar refactoring engine to perform the refactoring, even though the the refactoring has already begun, and 5) support the wide range of refactorings present in modern IDEs. Our techniques for overcoming these challenges are the technical contributions of this paper. We evaluate WitchDoctor's design and implementation by simulating over 5,000 refactoring operations across three open-source projects. The simulated user is faster and more efficient than an average human user, yet WitchDoctor can detect more than 90% of refactoring operations as they are being performed -- and can complete over a third of refactorings before the simulated user does. All the while, WitchDoctor remains robust in the face of non-parseable programs and unpredictable refactoring scenarios. We also show that WitchDoctor is efficient enough to perform computation on a keystroke-by-keystroke basis, adding an average overhead of only 15 milliseconds per keystroke.

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Cited By

Shi CZhu TZhang TPang JPan M(2023)Structural-semantics Guided Program Simplification for Understanding Neural Code Intelligence ModelsProceedings of the 14th Asia-Pacific Symposium on Internetware10.1145/3609437.3609438(1-11)Online publication date: 4-Aug-2023
https://dl.acm.org/doi/10.1145/3609437.3609438
Popoola SGray JGarcia-Dominguez AKolovos DKühn TSousa V(2022)Analyzing model changes with LoupeProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings10.1145/3550356.3561564(519-528)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550356.3561564
Chen LHayashi SRastogi ATufano RBavota GArnaoudova VHaiduc S(2022)Impact of change granularity in refactoring detectionProceedings of the 30th IEEE/ACM International Conference on Program Comprehension10.1145/3524610.3528386(565-569)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3524610.3528386
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Published In

cover image ACM Conferences

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

June 2012

1657 pages

ISBN:9781467310673

General Chair:
Martin Glinz,
Program Chairs:
Gail Murphy,
Mauro Pezzè

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

IEEE Press

Publication History

Published: 02 June 2012

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ICSE '12

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SIGSOFT

ICSE '12: 34th International Conference on Software Engineering

June 2 - 9, 2012

Zurich, Switzerland

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Shi CZhu TZhang TPang JPan M(2023)Structural-semantics Guided Program Simplification for Understanding Neural Code Intelligence ModelsProceedings of the 14th Asia-Pacific Symposium on Internetware10.1145/3609437.3609438(1-11)Online publication date: 4-Aug-2023
https://dl.acm.org/doi/10.1145/3609437.3609438
Popoola SGray JGarcia-Dominguez AKolovos DKühn TSousa V(2022)Analyzing model changes with LoupeProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings10.1145/3550356.3561564(519-528)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550356.3561564
Chen LHayashi SRastogi ATufano RBavota GArnaoudova VHaiduc S(2022)Impact of change granularity in refactoring detectionProceedings of the 30th IEEE/ACM International Conference on Program Comprehension10.1145/3524610.3528386(565-569)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3524610.3528386
Georgiou SKechagia MSharma TSarro FZou YDwyer MDamian DZeller A(2022)Green AIProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510221(1082-1094)Online publication date: 21-May-2022
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Efstathiou VSpinellis DStorey MAdams BHaiduc S(2019)Semantic source code models using identifier embeddingsProceedings of the 16th International Conference on Mining Software Repositories10.1109/MSR.2019.00015(29-33)Online publication date: 26-May-2019
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Tenorio DBibiano AGarcia ATsantalis NCai YDemeyer S(2019)On the customization of batch refactoringProceedings of the 3rd International Workshop on Refactoring10.1109/IWoR.2019.00010(13-16)Online publication date: 28-May-2019
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