Simon Koch, David Klein, and Martin Johns (TU Braunschweig)

Are GitHub stars a good surrogate metric to assess the importance of open-source code? While security research frequently uses them as a proxy for importance, the reliability of this relationship has not been studied yet. Furthermore, its relationship to download numbers provided by code registries – another commonly used metric – has yet to be ascertained. We address this research gap by analyzing the correlation between both GitHub stars and download numbers as well as their correlation with detected deployments across websites. Our data set consists of 925 978 data points across three web programming languages: PHP, Ruby, and JavaScript. We assess deployment across websites using 58 hand-crafted fingerprints for JavaScript libraries. Our results reveal a weak relationship between GitHub Stars and download numbers ranging from a correlation of 0.47 for PHP down to 0.14 for JavaScript, as well as a high amount of low star and high download projects for PHP and Ruby and an opposite pattern for JavaScript with a noticeably higher count of high star and apparently low download libraries. Concerning the relationship for detected deployments, we discovered a correlation of 0.61 and 0.63 with stars and downloads, respectively. Our results indicate that both downloads and stars pose a moderately strong indicator of the importance of client-side deployed JavaScript libraries.

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Daniela Lopes (INESC-ID / IST, Universidade de Lisboa), Jin-Dong Dong (Carnegie Mellon University), Pedro Medeiros (INESC-ID / IST, Universidade de Lisboa), Daniel Castro (INESC-ID / IST, Universidade de Lisboa), Diogo Barradas (University of Waterloo), Bernardo Portela (INESC TEC / Universidade do Porto), João Vinagre (INESC TEC / Universidade do Porto), Bernardo Ferreira (LASIGE, Faculdade de…

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Jun Ying, Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan and Google)

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Lian Gao (University of California Riverside), Yu Qu (University of California Riverside), Sheng Yu (University of California, Riverside & Deepbits Technology Inc.), Yue Duan (Singapore Management University), Heng Yin (University of California, Riverside & Deepbits Technology Inc.)

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Arjun Arunasalam (Purdue University), Habiba Farrukh (University of California, Irvine), Eliz Tekcan (Purdue University), Z. Berkay Celik (Purdue University)

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