Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/29886
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ibba, G | - |
dc.contributor.author | Aufiero, S | - |
dc.contributor.author | Neykova, R | - |
dc.contributor.author | Bartolucci, S | - |
dc.contributor.author | Ortu, M | - |
dc.contributor.author | Tonelli, R | - |
dc.contributor.author | Destefanis, G | - |
dc.coverage.spatial | Porto de Galinhas, Brazil | - |
dc.date.accessioned | 2024-10-06T10:34:15Z | - |
dc.date.available | 2024-10-06T10:34:15Z | - |
dc.date.issued | 2024-07-10 | - |
dc.identifier | ORCiD: Rumyana Neykova https://orcid.org/0000-0002-2755-7728 | - |
dc.identifier | ORCiD: Giuseppe Destefanis https://orcid.org/0000-0003-3982-6355 | - |
dc.identifier.citation | Ibba, G. et al. (2024) 'A Curated Solidity Smart Contracts Repository of Metrics and Vulnerability', PROMISE 2024 - Proceedings of the 20th International Conference on Predictive Models and Data Analytics in Software Engineering, Co-located with: ESEC/FSE 2024, 2024, pp. 32 - 41. doi: 10.1145/3663533.3664039. | en_US |
dc.identifier.isbn | 979-8-4007-0675-2 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29886 | - |
dc.description | Data Availability Statement: Our dataset is available on Zenodo (https://zenodo.org/records/11075555), offering a repository encompassing valuable resources such as smart contracts source codes, and associated software metrics and vulnerability reports, encouraging researchers and developers to enhance the current literature in SC security and analysis. | - |
dc.description.abstract | Smart contracts (SCs) significance and popularity increased exponentially with the escalation of decentralised applications (dApps), which revolutionised programming paradigms where network controls rest within a central authority. Since SCs constitute the core of such applications, developing and deploying contracts without vulnerability issues become key to improve dApps robustness to external attacks. This paper introduces a dataset that combines smart contract metrics with vulnerability data identified using Slither, a leading static analysis tool proficient in detecting a wide spectrum of vulnerabilities. Our primary goal is to provide a resource for the community that supports exploratory analysis, such as investigating the relationship between contract metrics and vulnerability occurrences. Further, we discuss the potential of this dataset for the development and validation of predictive models aimed at identifying vulnerabilities, thereby contributing to the enhancement of smart contract security. Through this dataset, we invite researchers and practitioners to study the dynamics of smart contract vulnerabilities, fostering advancements in detection methods and ultimately, fortifying the resilience of smart contracts. | en_US |
dc.format.extent | 32 - 41 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Association for Computing Machinery (ACM) | en_US |
dc.relation.uri | https://zenodo.org/records/11075555 | - |
dc.rights | Attribution 4.0 International | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.source | PROMISE '24: 20th International Conference on Predictive Models and Data Analytics in Software Engineering | - |
dc.source | PROMISE '24: 20th International Conference on Predictive Models and Data Analytics in Software Engineering | - |
dc.subject | smart contracts | en_US |
dc.subject | Ethereum | en_US |
dc.subject | blockchain | en_US |
dc.subject | vulnerability detection | en_US |
dc.subject | software engineering | en_US |
dc.subject | data analysis | en_US |
dc.title | A Curated Solidity Smart Contracts Repository of Metrics and Vulnerability | en_US |
dc.type | Conference Paper | en_US |
dc.date.dateAccepted | 2024-04-19 | - |
dc.identifier.doi | https://doi.org/10.1145/3663533.3664039 | - |
dc.relation.isPartOf | PROMISE 2024 - Proceedings of the 20th International Conference on Predictive Models and Data Analytics in Software Engineering, Co-located with: ESEC/FSE 2024 | - |
pubs.finish-date | 2024-07-16 | - |
pubs.finish-date | 2024-07-16 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2024-07-16 | - |
pubs.start-date | 2024-07-16 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
dc.rights.holder | owner/author(s) | - |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | © 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/). | 931.45 kB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License