Performance of GitHub Open-Source Software Project: An Empirical Analysis

Joy, Abin; Thangavelu, Senthilkumar; Jyotishi, Amalendu

doi:10.1109/icaecc.2018.8479462

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…This method is designed for characterizing vulnerabilities and providing users with a concise vulnerability awareness. Houmb et al (2010) used CVSS and Bayesian Belief Network (BBN) (Jensen 1996) to quantitatively estimate the security risk of a system or a specific part of the system, where CVSS is used to build the model and its value is input for running the BBN model. They reorganized CVSS metrics to evaluate the performance of a system.…”

Section: Vulnerabilitymentioning

confidence: 99%

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Evaluation indicators for open-source software: a review

et al. 2021

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In recent years, the widespread applications of open-source software (OSS) have brought great convenience for software developers. However, it is always facing unavoidable security risks, such as open-source code defects and security vulnerabilities. To find out the OSS risks in time, we carry out an empirical study to identify the indicators for evaluating the OSS. To achieve a comprehensive understanding of the OSS assessment, we collect 56 papers from prestigious academic venues (such as IEEE Xplore, ACM Digital Library, DBLP, and Google Scholar) in the past 21 years. During the process of the investigation, we first identify the main concerns for selecting OSS and distill five types of commonly used indicators to assess OSS. We then conduct a comparative analysis to discuss how these indicators are used in each surveyed study and their differences. Moreover, we further undertake a correlation analysis between these indicators and uncover 13 confirmed conclusions and four cases with controversy occurring in these studies. Finally, we discuss several possible applications of these conclusions, which are insightful for the research on OSS and software supply chain.

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Section: Vulnerabilitymentioning

confidence: 99%

“…Last but not least, Wu et al (2007) andJoy et al (2018) proposed programming language had none promotion effect on the popularity of OSS. But in the next work, Ghapanchi and Tavana (2015) found programming language had a positive influence on the popularity.…”

Section: Controversial Correlationsmentioning

confidence: 99%

Evaluation indicators for open-source software: a review

et al. 2021

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“…Code repositories like SourceForge, GitHub, GitLab, Bitbucket and Google Code contain a lot of information (Güemes-Peña et al, 2018). These companies offer services that go beyond simple hosting and version control of the software (Joy et al, 2018). Therefore, source code repositories have been attracting a huge interest from many researchers (Lee et al, 2013).…”

Section: Code Repository Analysismentioning

confidence: 99%

“…These kinds of systems have been adopted by the industry and are used by a significant number of open source projects (Joy et al, 2018). Thereby, such systems have become an important source of technical and social information about software development that is used to identify conventions, patterns, artifacts, etc.…”

Section: Code Repository Analysismentioning

confidence: 99%

A Systematic Mapping Study on Analysis of Code Repositories

Sayago-Heredia¹,

Pérez‐Castillo²,

Piattini³

2021

Informatica

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Code repositories contain valuable information, which can be extracted, processed and synthesized into valuable information. It enabled developers to improve maintenance, increase code quality and understand software evolution, among other insights. Certain research has been made during the last years in this field. This paper presents a systematic mapping study to find, evaluate and investigate the mechanisms, methods and techniques used for the analysis of information from code repositories that allow the understanding of the evolution of software. Through this mapping study, we have identified the main information used as input for the analysis of code repositories (commit data and source code), as well as the most common methods and techniques of analysis (empirical/experimental and automatic). We believe the conducted research is useful for developers working on software development projects and seeking to improve maintenance and understand the evolution of software through the use and analysis of code repositories.

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