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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022 . Peer-reviewed
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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Technical Leverage Dataset for Java Dependencies in Maven

Authors: Massacci, Fabio; Pashchencko, Ivan;

Technical Leverage Dataset for Java Dependencies in Maven

Abstract

In finance, leverage is the ratio between assets borrowed from others and one's own assets. A matching situation is present in software: by using free open-source software (FOSS) libraries a developer leverages on other people's code to multiply the offered functionalities with a much smaller own codebase. In finance as in software, leverage magnifies profits when returns from borrowing exceed costs of integration, but it may also magnify losses, in particular in the presence of security vulnerabilities. We aim to understand the level of technical leverage in the FOSS ecosystem and whether it can be a potential source of security vulnerabilities. Also, we introduce two metrics change distance and change direction to capture the amount and the evolution of the dependency on third-party libraries. Our analysis published in [1] shows that small and medium libraries (less than 100KLoC) have disproportionately more leverage on FOSS dependencies in comparison to large libraries. We show that leverage pays off as leveraged libraries only add a 4% delay in the time interval between library releases while providing four times more code than their own. However, libraries with such leverage (i.e., 75% of libraries in our sample) also have 1.6 higher odds of being vulnerable in comparison to the libraries with lower leverage. This dataset is the original dataset used in the publication [1]. It includes 8494 distinct library versions from the FOSS Maven-based Java libraries An online demo for computing the proposed metrics for real-world software libraries is also available under the following URL: https://techleverage.eu/. The original publication is [1]. An executive summary of the results is avialble as the publication [2]. This work has been funded by the European Union with the project AssureMOSS (https://www.assuremoss.eu). [1] Massacci, F., & Pashchenko, I. (2021, May). Technical leverage in a software ecosystem: Development opportunities and security risks. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) (pp. 1386-1397). IEEE. [2] Massacci, F., & Pashchenko, I. (2021). Technical Leverage: Dependencies Are a Mixed Blessing. IEEE Secur. Priv., 19(3), 58-62.

{"references": ["Massacci, F., & Pashchenko, I. (2021, May). Technical leverage in a software ecosystem: Development opportunities and security risks. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) (pp. 1386-1397). IEEE.", "Massacci, F., & Pashchenko, I. (2021). Technical Leverage: Dependencies Are a Mixed Blessing. IEEE Secur. Priv., 19(3), 58-62."]}

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Keywords

open source software, vulnerabilities, software dependencies, java, security

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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