Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/138842
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Type: Journal article
Title: NCQ: Code Reuse Support for Node.js Developers
Author: Reid, B.
Amorim, M.D.
Wagner, M.
Treude, C.
Citation: IEEE Transactions on Software Engineering, 2023; 49(5):1-21
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2023
ISSN: 0098-5589
1939-3520
Statement of
Responsibility: 
Brittany Reid, Marcelo d, Amorim, Markus Wagner, and Christoph Treude
Abstract: Code reuse is an important part of software development. The adoption of code reuse practices is especially common among Node.js developers. The Node.js package manager, NPM, indexes over 1Million packages and developers often seek out packages to solve programming tasks. Due to the vast number of packages, selecting the right package is difficult and time consuming. With the goal of improving productivity of developers that heavily reuse code through third-party packages, we present Node Code Query (NCQ), a Read-Eval-Print-Loop environment that allows developers to 1) search for NPM packages using natural language queries, 2) search for code snippets related to those packages, 3) automatically correct errors in these code snippets, 4) quickly setup new environments for testing those snippets, and 5) transition between search and editing modes. In two user studies with a total of 20 participants, we find that participants begin programming faster and conclude tasks faster with NCQ than with baseline approaches, and that they like, among other features, the search for code snippets and packages. Our results suggest that NCQ makes Node.js developers more efficient in reusing code.
Keywords: Code reuse; code search; library selection
Rights: © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
DOI: 10.1109/tse.2023.3248113
Grant ID: http://purl.org/au-research/grants/arc/DP200102364
http://purl.org/au-research/grants/arc/DP210102670
Published version: http://dx.doi.org/10.1109/tse.2023.3248113
Appears in Collections:Computer Science publications

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