215 research outputs found

    Authors\u27 Moral Rights in Non-European Nations: International Agreements, Economics, \u3cem\u3eMannu Bhandari\u3c/em\u3e, and the Dead Sea Scrolls

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    This note undertakes to examine authors\u27 moral rights in non-European countries. Section I will provide a brief comparative description of moral rights. Section II will discuss the treatment of moral rights in the Berne convention and the TRIPS agreement. Section III will then examine moral rights law in India and Israel, and two important cases from these nations, Mannu Bhandari v. Kala Vikas Pictures from India, and Qimron v. Shanks, from Israel. Mannu Bhandari deals with an author\u27s moral right in the film adaptation of her work, Qimron with the moral rights of a scholar in the reconstruction of one of the Dead Sea Scroll texts. Finally, Section IV will discuss the economic rationale for moral rights and the role of moral rights in non-European countrie

    CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software

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    CVEfixes is a comprehensive vulnerability dataset that is automatically collected and curated from Common Vulnerabilities and Exposures (CVE) records in the public U.S. National Vulnerability Database (NVD). The goal is to support data-driven security research based on source code and source code metrics related to fixes for CVEs in the NVD by providing detailed information at different interlinked levels of abstraction, such as the commit-, file-, and method level, as well as the repository- and CVE level. At the initial release, the dataset covers all published CVEs up to 9 June 2021. All open-source projects that were reported in CVE records in the NVD in this time frame and had publicly available git repositories were fetched and considered for the construction of this vulnerability dataset. The dataset is organized as a relational database and covers 5495 vulnerability fixing commits in 1754 open source projects for a total of 5365 CVEs in 180 different Common Weakness Enumeration (CWE) types. The dataset includes the source code before and after fixing of 18249 files, and 50322 functions. Because of limitations in GitHub storage, we provide a compressed SQL dump of the CVEfixes vulnerability dataset via Zenodo with DOI: 10.5281/zenodo.4476563. This repository includes the code to replicate the data collection. The complete process has been documented in the paper "CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open- Source Software", a copy of which you will find in the Doc folder. Citation and Zenodo links Please cite this work by referring to the published paper: Guru Bhandari, Amara Naseer, and Leon Moonen. 2021. CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software. In Proceedings of the 17th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE '21). ACM, 10 pages. https://doi.org/10.1145/3475960.3475985 @inproceedings{bhandari2021:cvefixes, title = {{CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software}}, booktitle = {{Proceedings of the 17th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE '21)}}, author = {Bhandari, Guru and Naseer, Amara and Moonen, Leon}, year = {2021}, pages = {10}, publisher = {{ACM}}, doi = {10.1145/3475960.3475985}, copyright = {Open Access}, isbn = {978-1-4503-8680-7}, language = {en} } The dataset has been released on Zenodo with DOI:10.5281/zenodo.4476563. The GitHub repository containing the code to automatically collect the dataset can be found at https://github.com/secureIT-project/CVEfixes, released with DOI:10.5281/zenodo.5111494.This work has been financially supported by the Research Council of Norway through the secureIT project (RCN contract #288787)

    Correction: Design of crack-free laser additive manufactured Inconel 939 alloy driven by computational thermodynamics method (MRS Communications, (2022), 12, 5, (844-849), 10.1557/s43579-022-00253-x)

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    The article Design of crack-free laser additive manufactured Inconel 939 alloy driven by computational thermodynamics method, written by Congyuan Zeng, Huan Ding, Uttam Bhandari, S. M. Guo, was originally published electronically on the publisher’s internet portal on 9 September 2022 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 20 December 2022 to © The Author(s) 2022 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder

    CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software

    No full text
    CVEfixes is a comprehensive vulnerability dataset that is automatically collected and curated from Common Vulnerabilities and Exposures (CVE) records in the public U.S. National Vulnerability Database (NVD). The goal is to support data-driven security research based on source code and source code metrics related to fixes for CVEs in the NVD by providing detailed information at different interlinked levels of abstraction, such as the commit-, file-, and method level, as well as the repository- and CVE level. At the initial release, the dataset covers all published CVEs up to 9 June 2021. All open-source projects that were reported in CVE records in the NVD in this time frame and had publicly available git repositories were fetched and considered for the construction of this vulnerability dataset. The dataset is organized as a relational database and covers 5495 vulnerability fixing commits in 1754 open source projects for a total of 5365 CVEs in 180 different Common Weakness Enumeration (CWE) types. The dataset includes the source code before and after fixing of 18249 files, and 50322 functions. Because of limitations in GitHub storage, we provide a compressed SQL dump of the CVEfixes vulnerability dataset via Zenodo with DOI: 10.5281/zenodo.4476563. This repository includes the code to replicate the data collection. The complete process has been documented in the paper "CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open- Source Software", a copy of which you will find in the Doc folder. Citation and Zenodo links Please cite this work by referring to the published paper: Guru Bhandari, Amara Naseer, and Leon Moonen. 2021. CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software. In Proceedings of the 17th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE '21). ACM, 10 pages. https://doi.org/10.1145/3475960.3475985 @inproceedings{bhandari2021:cvefixes, title = {{CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software}}, booktitle = {{Proceedings of the 17th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE '21)}}, author = {Bhandari, Guru and Naseer, Amara and Moonen, Leon}, year = {2021}, pages = {10}, publisher = {{ACM}}, doi = {10.1145/3475960.3475985}, copyright = {Open Access}, isbn = {978-1-4503-8680-7}, language = {en} } The dataset has been released on Zenodo with DOI:10.5281/zenodo.4476563. The GitHub repository containing the code to automatically collect the dataset can be found at https://github.com/secureIT-project/CVEfixes, released with DOI:10.5281/zenodo.5111494.This work has been financially supported by the Research Council of Norway through the secureIT project (RCN contract #288787)
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