Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study. Sha, Z., Petrov, A., Tian, Y., & Hu, T. 2022. SSRN Electronic Journal, Available at SSRN: https://ssrn.com/abstract=4082801![Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper abstract bibtex 3 downloads The health and sustainability of an open-source software (OSS) ecosystem depends on its contributors' initiative. Unfortunately, studies have shown that OSS projects often suffer from high contributor turnover rates due to their open-source nature. High contributor turnover rates can have negative impacts on the community involved in individual projects and the ecosystem that relies on such projects. We propose a computational model to quantify the robustness of a software ecosystem to contributor loss and perform a case study on two OSS ecosystems, i.e., Ruby and PyPI. We utilize a simulation method to analyze project extinction risk due to contributor loss at the ecosystem-level. We apply the proposed method on 12,267,933 and 1,459,322 commits scraped from 102,447 Ruby projects and 69,311 PyPI libraries respectively, hosted on GitHub. To identify the factors that influence the robustness of ecosystems, we propose an ecosystem simulation method to generate artificial ecosystems with different control parameters.We find that contributor turnover and project abandonment frequently happen in Ruby and PyPI ecosystems. Moreover, the preference of developers to contribute to large projects in an OSS ecosystem negatively affects the robustness of the ecosystem. Both studied ecosystems are less robust to the loss of active contributors who either intensively or extensively contribute to the ecosystem than the random loss of contributors.Our proposed methods can be leveraged to analyze the robustness of a software ecosystem to contributor loss over time. Moreover, we provide a ecosystem simulation method to analyze how various factors determine the robustness of an OSS ecosystem, demonstrating the potential of testing a hypothesis without empirical data for ecosystem robustness analysis.
@unpublished{sha2022analyzing,
title = {Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study},
author = {Sha, Zhendong and Petrov, Alice and Tian, Yuan and Hu, Ting},
year = {2022},
note = {SSRN Electronic Journal, Available at SSRN: https://ssrn.com/abstract=4082801},
url_paper = {https://alicepetrov.github.io/assets/pdf/papers/2022/sha2022analyzing.pdf},
abstract = {The health and sustainability of an open-source software (OSS) ecosystem depends on its contributors' initiative. Unfortunately, studies have shown that OSS projects often suffer from high contributor turnover rates due to their open-source nature. High contributor turnover rates can have negative impacts on the community involved in individual projects and the ecosystem that relies on such projects. We propose a computational model to quantify the robustness of a software ecosystem to contributor loss and perform a case study on two OSS ecosystems, i.e., Ruby and PyPI. We utilize a simulation method to analyze project extinction risk due to contributor loss at the ecosystem-level. We apply the proposed method on 12,267,933 and 1,459,322 commits scraped from 102,447 Ruby projects and 69,311 PyPI libraries respectively, hosted on GitHub. To identify the factors that influence the robustness of ecosystems, we propose an ecosystem simulation method to generate artificial ecosystems with different control parameters.We find that contributor turnover and project abandonment frequently happen in Ruby and PyPI ecosystems. Moreover, the preference of developers to contribute to large projects in an OSS ecosystem negatively affects the robustness of the ecosystem. Both studied ecosystems are less robust to the loss of active contributors who either intensively or extensively contribute to the ecosystem than the random loss of contributors.Our proposed methods can be leveraged to analyze the robustness of a software ecosystem to contributor loss over time. Moreover, we provide a ecosystem simulation method to analyze how various factors determine the robustness of an OSS ecosystem, demonstrating the potential of testing a hypothesis without empirical data for ecosystem robustness analysis.},
keywords = {Software Engineering}
}
Downloads: 3
{"_id":"gdxeGcFzmD2F9S2W4","bibbaseid":"sha-petrov-tian-hu-analyzingtherobustnessofopensourcesoftwareecosystemstothelossofcontributorsacasestudy-2022","author_short":["Sha, Z.","Petrov, A.","Tian, Y.","Hu, T."],"bibdata":{"bibtype":"unpublished","type":"unpublished","title":"Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study","author":[{"propositions":[],"lastnames":["Sha"],"firstnames":["Zhendong"],"suffixes":[]},{"propositions":[],"lastnames":["Petrov"],"firstnames":["Alice"],"suffixes":[]},{"propositions":[],"lastnames":["Tian"],"firstnames":["Yuan"],"suffixes":[]},{"propositions":[],"lastnames":["Hu"],"firstnames":["Ting"],"suffixes":[]}],"year":"2022","note":"SSRN Electronic Journal, Available at SSRN: https://ssrn.com/abstract=4082801","url_paper":"https://alicepetrov.github.io/assets/pdf/papers/2022/sha2022analyzing.pdf","abstract":"The health and sustainability of an open-source software (OSS) ecosystem depends on its contributors' initiative. Unfortunately, studies have shown that OSS projects often suffer from high contributor turnover rates due to their open-source nature. High contributor turnover rates can have negative impacts on the community involved in individual projects and the ecosystem that relies on such projects. We propose a computational model to quantify the robustness of a software ecosystem to contributor loss and perform a case study on two OSS ecosystems, i.e., Ruby and PyPI. We utilize a simulation method to analyze project extinction risk due to contributor loss at the ecosystem-level. We apply the proposed method on 12,267,933 and 1,459,322 commits scraped from 102,447 Ruby projects and 69,311 PyPI libraries respectively, hosted on GitHub. To identify the factors that influence the robustness of ecosystems, we propose an ecosystem simulation method to generate artificial ecosystems with different control parameters.We find that contributor turnover and project abandonment frequently happen in Ruby and PyPI ecosystems. Moreover, the preference of developers to contribute to large projects in an OSS ecosystem negatively affects the robustness of the ecosystem. Both studied ecosystems are less robust to the loss of active contributors who either intensively or extensively contribute to the ecosystem than the random loss of contributors.Our proposed methods can be leveraged to analyze the robustness of a software ecosystem to contributor loss over time. Moreover, we provide a ecosystem simulation method to analyze how various factors determine the robustness of an OSS ecosystem, demonstrating the potential of testing a hypothesis without empirical data for ecosystem robustness analysis.","keywords":"Software Engineering","bibtex":"@unpublished{sha2022analyzing,\n title = {Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study},\n author = {Sha, Zhendong and Petrov, Alice and Tian, Yuan and Hu, Ting},\n year = {2022},\n note = {SSRN Electronic Journal, Available at SSRN: https://ssrn.com/abstract=4082801},\n url_paper = {https://alicepetrov.github.io/assets/pdf/papers/2022/sha2022analyzing.pdf},\n abstract = {The health and sustainability of an open-source software (OSS) ecosystem depends on its contributors' initiative. Unfortunately, studies have shown that OSS projects often suffer from high contributor turnover rates due to their open-source nature. High contributor turnover rates can have negative impacts on the community involved in individual projects and the ecosystem that relies on such projects. We propose a computational model to quantify the robustness of a software ecosystem to contributor loss and perform a case study on two OSS ecosystems, i.e., Ruby and PyPI. We utilize a simulation method to analyze project extinction risk due to contributor loss at the ecosystem-level. We apply the proposed method on 12,267,933 and 1,459,322 commits scraped from 102,447 Ruby projects and 69,311 PyPI libraries respectively, hosted on GitHub. To identify the factors that influence the robustness of ecosystems, we propose an ecosystem simulation method to generate artificial ecosystems with different control parameters.We find that contributor turnover and project abandonment frequently happen in Ruby and PyPI ecosystems. Moreover, the preference of developers to contribute to large projects in an OSS ecosystem negatively affects the robustness of the ecosystem. Both studied ecosystems are less robust to the loss of active contributors who either intensively or extensively contribute to the ecosystem than the random loss of contributors.Our proposed methods can be leveraged to analyze the robustness of a software ecosystem to contributor loss over time. Moreover, we provide a ecosystem simulation method to analyze how various factors determine the robustness of an OSS ecosystem, demonstrating the potential of testing a hypothesis without empirical data for ecosystem robustness analysis.},\n keywords = {Software Engineering}\n}\n","author_short":["Sha, Z.","Petrov, A.","Tian, Y.","Hu, T."],"key":"sha2022analyzing","id":"sha2022analyzing","bibbaseid":"sha-petrov-tian-hu-analyzingtherobustnessofopensourcesoftwareecosystemstothelossofcontributorsacasestudy-2022","role":"author","urls":{" paper":"https://alicepetrov.github.io/assets/pdf/papers/2022/sha2022analyzing.pdf"},"keyword":["Software Engineering"],"metadata":{"authorlinks":{}},"downloads":3},"bibtype":"unpublished","biburl":"https://raw.githubusercontent.com/alicepetrov/alicepetrov.github.io/main/_bibliography/papers.bib","dataSources":["adWMgNS3S9SmwmtLP","2Eox22rXM4CLdebT7","Q3hkt85LkKqqkfHnA"],"keywords":["software engineering"],"search_terms":["analyzing","robustness","open","source","software","ecosystems","loss","contributors","case","study","sha","petrov","tian","hu"],"title":"Analyzing the Robustness of Open Source Software Ecosystems to the Loss of Contributors: A Case Study","year":2022,"downloads":3}