The Art and Science of Analyzing Software Data 2015
DOI: 10.1016/b978-0-12-411519-4.00014-8
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Community Data for OSS Adoption Risk Management

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Cited by 6 publications
(4 citation statements)
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“…When observing occurrences, it is common to nd that around 80% of the occurrences are caused by 20% of the available reasons. 58 From Fig. 3(A)-(C), it was inferred and concluded that three inuencing considerations such as the equivalent ratio, biomass ratio and air ow rate were found to have a noteworthy effect on optimization of gas yield, tar yield and gas heating value.…”
Section: Pareto Analysismentioning
confidence: 98%
“…When observing occurrences, it is common to nd that around 80% of the occurrences are caused by 20% of the available reasons. 58 From Fig. 3(A)-(C), it was inferred and concluded that three inuencing considerations such as the equivalent ratio, biomass ratio and air ow rate were found to have a noteworthy effect on optimization of gas yield, tar yield and gas heating value.…”
Section: Pareto Analysismentioning
confidence: 98%
“…OSS projects are developed in open and distributed development communities, guided by heterogeneous personal and business objectives, and provided without quality of service agreements or formal commitments on the future roadmap. In this setting, risk assessment can benefit from the open nature of the OSS ecosystems [3]. In fact, a large amount of data is available in software repositories and community-related artefacts, describing several aspects of the OSS ecosystems.…”
Section: Motivation and Objectivesmentioning
confidence: 99%
“…In the approach proposed in RISCOSS [3] the analysis is based on a three layered view to risk management in OSS.…”
Section: The Risk Analysis Approachmentioning
confidence: 99%
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