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Code completion of multiple keywords from abbreviated input

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Abstract

Abbreviation Completion is a novel technique to improve the efficiency of code-writing by supporting code completion of multiple keywords based on non-predefined abbreviated input—a different approach from conventional code completion that finds one keyword at a time based on an exact character match. Abbreviated input consisting of abbreviated keywords and non-alphanumeric characters between each abbreviated keyword (e.g. pb st nm) is expanded into a full expression (e.g. public String name) by a Hidden Markov Model learned from a corpus of existing code and abbreviation examples. The technique does not require the user to memorize abbreviations and provides incremental feedback of the most likely completions.

In addition to code completion by disabbreviation of multiple keywords, abbreviation completion supports prediction of the next keywords and non-alphanumeric characters of a code completion candidate, a technique called code completion by extrapolation. The system finds the most likely next keywords and non-alphanumeric characters using an n-gram model of programming language. This enables a code completion scenario in which a user first types a short abbreviated expression to complete the beginning part of a desired full expression and then uses the extrapolation feature to complete the remaining part without further typing.

This paper presents the algorithm for abbreviation completion, integrated with a new user interface for multiple-keyword code completion. We tested the system by sampling 4919 code lines from open source projects and found that more than 99% of the code lines could be resolved from acronym-like abbreviations. The system could also extrapolate code completion candidates to complete the next one or two keywords with the accuracy of 96% and 82%, respectively. A user study of code completion by disabbreviation found 30% reduction in time usage and 41% reduction of keystrokes over conventional code completion.

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Authors and Affiliations

  1. MIT, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA

    Sangmok Han, David R. Wallace & Robert C. Miller

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  1. Sangmok Han
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  2. David R. Wallace
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  3. Robert C. Miller
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Correspondence to Sangmok Han.

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This research was supported by Samsung Scholarship Foundation.

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Han, S., Wallace, D.R. & Miller, R.C. Code completion of multiple keywords from abbreviated input. Autom Softw Eng 18, 363–398 (2011). https://doi.org/10.1007/s10515-011-0083-2

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