A code search engine for software ecosystems

Chris Pfaff; Elena Baninemeh; Siamak Farshidi; Slinger Jansen

A code search engine for software ecosystems

Chris Pfaff, Elena Baninemeh, Siamak Farshidi, Slinger Jansen

Utrecht University

Research output: Contribution to journal › Conference article › Academic › peer-review

Abstract

Searching and reusing source code play an increasingly significant role in the daily tasks of software developers. While code repositories, such as GitHub and Stackoverflow, may provide some results, a code search engine is generally considered most helpful when searching for code snippets as they typically crawl data from a wide range of code repositories. Code search engines enable software developers to search for code snippets using search terms. The accuracy of the search results can be increased if the searchers' intent can be modeled and predicted correctly. This study proposes a novel code search engine to model user intents through a dialogue system and then suggests a ranked list of code snippets that can meet user requirements.

Original language	English
Number of pages	11
Journal	CEUR Workshop Proceedings
Volume	3245
Publication status	Published - 2022
Event	21st Belgium-Netherlands Software Evolution Workshop, BENEVOL 2022 - Mons, Belgium Duration: 12 Sept 2022 → 13 Sept 2022

Bibliographical note

Publisher Copyright:
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Keywords

code search
code search engine
indexing source code
machine learning
ranking code snippets

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paper2Final published version, 1.08 MBLicence: CC BY

https://ceur-ws.org/Vol-3245/Licence: CC BY

Cite this

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title = "A code search engine for software ecosystems",

abstract = "Searching and reusing source code play an increasingly significant role in the daily tasks of software developers. While code repositories, such as GitHub and Stackoverflow, may provide some results, a code search engine is generally considered most helpful when searching for code snippets as they typically crawl data from a wide range of code repositories. Code search engines enable software developers to search for code snippets using search terms. The accuracy of the search results can be increased if the searchers' intent can be modeled and predicted correctly. This study proposes a novel code search engine to model user intents through a dialogue system and then suggests a ranked list of code snippets that can meet user requirements.",

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T1 - A code search engine for software ecosystems

AU - Pfaff, Chris

AU - Baninemeh, Elena

AU - Farshidi, Siamak

AU - Jansen, Slinger

PY - 2022

Y1 - 2022

N2 - Searching and reusing source code play an increasingly significant role in the daily tasks of software developers. While code repositories, such as GitHub and Stackoverflow, may provide some results, a code search engine is generally considered most helpful when searching for code snippets as they typically crawl data from a wide range of code repositories. Code search engines enable software developers to search for code snippets using search terms. The accuracy of the search results can be increased if the searchers' intent can be modeled and predicted correctly. This study proposes a novel code search engine to model user intents through a dialogue system and then suggests a ranked list of code snippets that can meet user requirements.

AB - Searching and reusing source code play an increasingly significant role in the daily tasks of software developers. While code repositories, such as GitHub and Stackoverflow, may provide some results, a code search engine is generally considered most helpful when searching for code snippets as they typically crawl data from a wide range of code repositories. Code search engines enable software developers to search for code snippets using search terms. The accuracy of the search results can be increased if the searchers' intent can be modeled and predicted correctly. This study proposes a novel code search engine to model user intents through a dialogue system and then suggests a ranked list of code snippets that can meet user requirements.

KW - code search

KW - code search engine

KW - indexing source code

KW - machine learning

KW - ranking code snippets

UR - http://www.scopus.com/inward/record.url?scp=85140887504&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85140887504

SN - 1613-0073

VL - 3245

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 21st Belgium-Netherlands Software Evolution Workshop, BENEVOL 2022

Y2 - 12 September 2022 through 13 September 2022

ER -

A code search engine for software ecosystems

Abstract

Bibliographical note

Keywords

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