An Empirical Study of README contents for JavaScript Packages

Open-source software (OSS) is widely reused as it provides convenience and efficiency in software development. Despite evident benefits, unmanaged OSS components can introduce threats, such as vulnerability propagation and license violation. Unfortunately, however, identifying reused OSS components is a challenge as the reused OSS is predominantly modified and nested. In this paper, we propose CENTRIS, a precise and scalable approach for identifying modified OSS reuse. By segmenting an OSS code base and detecting the reuse of a unique part of the OSS only, CENTRIS is capable of precisely identifying modified OSS reuse in the presence of nested OSS components. For scalability, CENTRIS eliminates redundant code comparisons and accelerates the search using hash functions. When we applied CENTRIS on 10,241 widely-employed GitHub projects, comprising 229,326 versions and 80 billion lines of code, we observed that modified OSS reuse is a norm in software development, occurring 20 times more frequently than exact reuse. Nonetheless, CENTRIS identified reused OSS components with 91% precision and 94% recall in less than a minute per application on average, whereas a recent clone detection technique, which does not take into account modified and nested OSS reuse, hardly reached 10% precision and 40% recall.

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“…• Metadata files: One of the README, LICENSE, and COPYING files in the top-level directory of the OSS ([23], [24]).…”

Section: A Accuracy O F Centrismentioning

confidence: 99%

CENTRIS: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse

Woo¹,

Park²,

Kim

et al. 2021

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)

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“…• Metadata files: One of the README, LICENSE, and COPYING files in the top-level directory of the OSS ( [23], [24]).…”

Section: A Accuracy Of Centrismentioning

confidence: 99%

CENTRIS: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse

Woo¹,

Park²,

Kim³

et al. 2021

Preprint

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“…This result indicates that project contributors consider links as an important instrument to provide further details about their projects. Ikeda et al [22] performed a similar study to evaluate README.md contents. Inspired by these works, we initiated our investigation on the relationship between academic papers and the scientific projects hosted on GitHub through the reference links embedded in their project README.md files.…”

Section: Related Workmentioning

confidence: 99%

GitHub Repositories with Links to Academic Papers: Public Access, Traceability, and Evolution

Supatsara¹,

Chinthanet²,

Hata³

et al. 2020

Preprint

Self Cite

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Traceability between published scientific breakthroughs and their implementation is essential, especially in the case of Open Source Software implements bleeding edge science into its code. However, aligning the link between GitHub repositories and academic papers can prove difficult, and the link impact remains unknown. This paper investigates the role of academic paper references contained in these repositories. We conducted a large-scale study of 20 thousand GitHub repositories to establish prevalence of references to academic papers. We use a mixed-methods approach to identify Open Access (OA), traceability and evolutionary aspects of the links. Although referencing a paper is not typical, we find that a vast majority of referenced academic papers are OA. In terms of traceability, our analysis revealed that machine learning is the most prevalent topic of repositories. These repositories tend to be affiliated with academic communities. More than half of the papers do not link back to any repository. A case study of referenced arXiv paper shows that most of these papers are high-impact and influential and do align with academia, referenced by repositories written in different programming languages. From the evolutionary aspect, we find very few changes of papers being referenced and links to them.

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An Empirical Study of README contents for JavaScript Packages

Cited by 6 publications

References 12 publications

CENTRIS: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse

CENTRIS: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse

CENTRIS: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse

GitHub Repositories with Links to Academic Papers: Public Access, Traceability, and Evolution

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