Recommending People in Developers' Collaboration Network

Many software developments involve collaborations of developers across the globe. This is true for both open-source and closed-source development efforts. Developers collaborate on different projects of various types. As with any other teamwork endeavors, finding compatibility among members in a deve...

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Main Authors: SURIAN, Didi, LIU, Nian, LO, David, Tong, Hanghang, LIM, Ee Peng, Faloutsos, Christos
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Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/1395
https://ink.library.smu.edu.sg/context/sis_research/article/2394/viewcontent/wcre11_recommend.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-23942018-04-30T06:20:31Z Recommending People in Developers' Collaboration Network SURIAN, Didi LIU, Nian LO, David Tong, Hanghang LIM, Ee Peng Faloutsos, Christos Many software developments involve collaborations of developers across the globe. This is true for both open-source and closed-source development efforts. Developers collaborate on different projects of various types. As with any other teamwork endeavors, finding compatibility among members in a development team is helpful towards the realization of the team’s goal. Compatible members tend to share similar programming style and naming strategy, communicate well with one another, etc. However, finding the right person to work with is not an easy task. In this work, we extract information available from Sourceforge.Net, the largest database of open source software, and build developer collaboration network comprising of information on developers, projects, and project properties. Based on an input developer, we then recommend a list of top developers that are most compatible based on their programming language skills, past projects and project categories they have worked on before, via a random walk with restart procedure. Our quantitative and qualitative experiments show that we are able to recommend reasonable developer candidates from snapshots of Sourceforge.Net consisting of tens of thousands of developers and projects, and hundreds of project properties. 2011-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1395 info:doi/10.1109/WCRE.2011.53 https://ink.library.smu.edu.sg/context/sis_research/article/2394/viewcontent/wcre11_recommend.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Developer Collaboration Network Randow Walk with Restart Recommendation Tool DPP Graph Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Developer Collaboration Network
Randow Walk with Restart
Recommendation Tool
DPP Graph
Software Engineering
spellingShingle Developer Collaboration Network
Randow Walk with Restart
Recommendation Tool
DPP Graph
Software Engineering
SURIAN, Didi
LIU, Nian
LO, David
Tong, Hanghang
LIM, Ee Peng
Faloutsos, Christos
Recommending People in Developers' Collaboration Network
description Many software developments involve collaborations of developers across the globe. This is true for both open-source and closed-source development efforts. Developers collaborate on different projects of various types. As with any other teamwork endeavors, finding compatibility among members in a development team is helpful towards the realization of the team’s goal. Compatible members tend to share similar programming style and naming strategy, communicate well with one another, etc. However, finding the right person to work with is not an easy task. In this work, we extract information available from Sourceforge.Net, the largest database of open source software, and build developer collaboration network comprising of information on developers, projects, and project properties. Based on an input developer, we then recommend a list of top developers that are most compatible based on their programming language skills, past projects and project categories they have worked on before, via a random walk with restart procedure. Our quantitative and qualitative experiments show that we are able to recommend reasonable developer candidates from snapshots of Sourceforge.Net consisting of tens of thousands of developers and projects, and hundreds of project properties.
format text
author SURIAN, Didi
LIU, Nian
LO, David
Tong, Hanghang
LIM, Ee Peng
Faloutsos, Christos
author_facet SURIAN, Didi
LIU, Nian
LO, David
Tong, Hanghang
LIM, Ee Peng
Faloutsos, Christos
author_sort SURIAN, Didi
title Recommending People in Developers' Collaboration Network
title_short Recommending People in Developers' Collaboration Network
title_full Recommending People in Developers' Collaboration Network
title_fullStr Recommending People in Developers' Collaboration Network
title_full_unstemmed Recommending People in Developers' Collaboration Network
title_sort recommending people in developers' collaboration network
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/1395
https://ink.library.smu.edu.sg/context/sis_research/article/2394/viewcontent/wcre11_recommend.pdf
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