Exploring the sustainability of open source software projects : clustering and pattern analysis = 오픈소스 소프트웨어 프로젝트의 지속가능성 연구 : 클러스터링과 패턴 분석 clustering and pattern analysis

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Open source software (OSS) has a large number of users, and as their number increases, the effects of OSS failures also increase. This thesis research conducted clustering based on the shape of the graph of development processes of OSS projects. After clustering, the OSS success factors suggested in previous studies were analyzed cluster-by-cluster to identify clusters that had many of these successful projects. Then, the success factors proposed were analyzed cluster-by-cluster to determine which had real effects. This study used the top 5,000 GitHub projects and divided them into four clusters. Of the four clusters, the most successful, sustainable projects were those in which development began in the early stage and progressed slowly over time. The projects in this cluster were more likely to operate on organizational accounts that used project names, and they attracted developers’ attention by using dedicated homepages and search keyword tags. They also had a large number of core developers, few pending issues, and more releases than the other clusters.
Advisors
Zo, Hangjungresearcher조항정researcher
Description
한국과학기술원 :기술경영학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 기술경영학부, 2019.2,[iv, 37 p. :]

Keywords

Open source▼aclustering▼asuccess factor▼atime-series data▼ak-shape algorithm; 오픈 소스▼a클러스터링▼a성공 요인▼a시계열 데이터▼ak-shape 알고리즘

URI
http://hdl.handle.net/10203/265975
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843070&flag=dissertation
Appears in Collection
MG-Theses_Master(석사논문)
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