Reinventing CI/CD for Collaborative Sciences: A Blockchain-Integrated Decentralized Middleware for Scalable and Fault-Tolerant Workflows

The expansion in the scale of collaborative scientific efforts has brought about numerous challenges in continuous integration/deployment (CI/CD). Current CI/CD tools solely depend on centralized data management, resulting in reliability and scalability concerns. To address the issue, this paper advocates for and demonstrates a decentralized approach that leverages lightweight data management techniques and distributed computing principles. Our middleware solution, DeQL, transforms the current CI/CD workflows, and uses decentralized logic for automated code analysis before GitHub commits. The involvement of distributed participants (i.e., GitHub contributors), together as a part of the decentralized network, ensures code integrity, security and reliable integration processes. For ensuring low overheads and scalability, this paper introduces lightweight consensus protocols designed for efficient smart contract execution, significantly reducing overhead compared to traditional decentralized data management solutions. We incorporate a fine-grained CI/CD commit dependency graph that effectively manages CI/CD commit complexity, facilitating faster (and more reliable) processing. Experimental results show that the proposed decentralized protocol outperforms the traditional centralized CI/CD system and state-of-the-art blockchain protocols, achieving up to 80% faster response times and handling 7× more commits in a given amount of time.

Authors

Institutions

Publication Details

Published
2025-09-15
DOI
https://doi.org/10.1109/escience65000.2025.00026
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reinventing CI/CD for Collaborative Sciences: A Blockchain-Integrated Decentralized Middleware for Scalable and Fault-Tolerant Workflows

Abdullah Al-Mamun, Amena Begum Farha, Gagan Agrawal, Ahmed Aleroud
Scientific Computing and Data Management
article

Reinventing CI/CD for Collaborative Sciences: A Blockchain-Integrated Decentralized Middleware for Scalable and Fault-Tolerant Workflows

Abdullah Al-Mamun, Amena Begum Farha, Gagan Agrawal, Ahmed Aleroud
article en

Abstract

The expansion in the scale of collaborative scientific efforts has brought about numerous challenges in continuous integration/deployment (CI/CD). Current CI/CD tools solely depend on centralized data management, resulting in reliability and scalability concerns. To address the issue, this paper advocates for and demonstrates a decentralized approach that leverages lightweight data management techniques and distributed computing principles. Our middleware solution, DeQL, transforms the current CI/CD workflows, and uses decentralized logic for automated code analysis before GitHub commits. The involvement of distributed participants (i.e., GitHub contributors), together as a part of the decentralized network, ensures code integrity, security and reliable integration processes. For ensuring low overheads and scalability, this paper introduces lightweight consensus protocols designed for efficient smart contract execution, significantly reducing overhead compared to traditional decentralized data management solutions. We incorporate a fine-grained CI/CD commit dependency graph that effectively manages CI/CD commit complexity, facilitating faster (and more reliable) processing. Experimental results show that the proposed decentralized protocol outperforms the traditional centralized CI/CD system and state-of-the-art blockchain protocols, achieving up to 80% faster response times and handling 7× more commits in a given amount of time.

University of Georgia (US), Augusta University (US)
Openalex Percentile: Top 73%
Scientific Computing and Data Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.