TY - GEN
T1 - Sociotechnical Dynamics in Open Source Smart Contract Repositories
T2 - 20th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2024, co-located with the International Conference on the Foundations of Software Engineering, FSE 2024
AU - Costa, Saori
AU - Paixao, Matheus
AU - Steinmacher, Igor
AU - Soares, Pamella
AU - Araújo, Allysson Allex
AU - Souza, Jerffeson
N1 - Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/7/10
Y1 - 2024/7/10
N2 - Blockchain and Smart Contracts (SCs) have emerged as a promising avenue for organizations looking to innovate. Similar to other fields of software engineering, collaborative platforms, such as GitHub, are gaining attention in SCs development. Moreover, public blockchain platforms, such as Ethereum, commonly serve as a medium to deploy SCs. This ecosystem serves as the basis on which the sociotechnical phenomenon of SC development emerges. Despite the growth of research regarding SCs, there is a gap in understanding the sociotechnical factors involved in their development, specially the ones with high market value. To address this issue, we leveraged Sociotechnical Theory and Data Analysis to investigate the sociotechnical dynamics in open source repositories of SCs deployed on Ethereum. To ensure suitability for our analysis, we curated a list of 16 high market value SCs deployed on Ethereum. Our research yielded four primary analyses. First, we unveiled how collaboration aspects are impacted by the deployment of SCs. Second, we explored the characteristics of contributors participating in these projects. Third, we looked into commit messages to categorize commonly performed software changes. Fourth, we investigated the relationship between market metrics and SC evolution. These analyses help to deepen the understanding of sociotechnical dynamics within SC repositories, assisting organizations in designing better strategies to support their development efforts.
AB - Blockchain and Smart Contracts (SCs) have emerged as a promising avenue for organizations looking to innovate. Similar to other fields of software engineering, collaborative platforms, such as GitHub, are gaining attention in SCs development. Moreover, public blockchain platforms, such as Ethereum, commonly serve as a medium to deploy SCs. This ecosystem serves as the basis on which the sociotechnical phenomenon of SC development emerges. Despite the growth of research regarding SCs, there is a gap in understanding the sociotechnical factors involved in their development, specially the ones with high market value. To address this issue, we leveraged Sociotechnical Theory and Data Analysis to investigate the sociotechnical dynamics in open source repositories of SCs deployed on Ethereum. To ensure suitability for our analysis, we curated a list of 16 high market value SCs deployed on Ethereum. Our research yielded four primary analyses. First, we unveiled how collaboration aspects are impacted by the deployment of SCs. Second, we explored the characteristics of contributors participating in these projects. Third, we looked into commit messages to categorize commonly performed software changes. Fourth, we investigated the relationship between market metrics and SC evolution. These analyses help to deepen the understanding of sociotechnical dynamics within SC repositories, assisting organizations in designing better strategies to support their development efforts.
KW - Exploratory Data Analysis
KW - Smart Contracts
KW - Sociotechnical Theory
KW - Software Evolution
UR - http://www.scopus.com/inward/record.url?scp=85200010494&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85200010494&partnerID=8YFLogxK
U2 - 10.1145/3663533.3664038
DO - 10.1145/3663533.3664038
M3 - Conference contribution
AN - SCOPUS:85200010494
T3 - PROMISE 2024 - Proceedings of the 20th International Conference on Predictive Models and Data Analytics in Software Engineering, Co-located with: ESEC/FSE 2024
SP - 22
EP - 31
BT - PROMISE 2024 - Proceedings of the 20th International Conference on Predictive Models and Data Analytics in Software Engineering, Co-located with
A2 - Shang, Weiyi
A2 - Lamothe, Maxime
A2 - Wan, Zhiyuan
PB - Association for Computing Machinery, Inc
Y2 - 16 July 2024
ER -