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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Arizona |
| Country | United States |
| Start Date | Apr 01, 2025 |
| End Date | Sep 30, 2025 |
| Duration | 182 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2520782 |
This I-Corps project is based on the development of a tool that enables small and medium sized businesses to adopt and scale microservice architectures. A microservice architectural approach is used to develop software applications as a collection of small, independent services that communicate with each other over a network. The challenge comes when these systems evolve.
System developers can foster expertise in individual microservices and their specific domains, but problems can occur when changes impact other microservices. Developers quickly lose track of microservices dependencies. This solution addresses these challenges in microservice architecture maintainability and quality by providing just-in-time insights into the architectural impact of changes.
The goal is to provide change impact analysis of cloud-native systems alongside quality assurances to improve system evolvability and reliability.
This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of change impact analysis of cloud-native systems alongside quality assurance. The solution uses static code analysis tailored to distributed, component-based development to enable holistic reasoning and reduce change impact propagation issues.
Improperly managing change impact may lead to costly errors during development, including increased communication overhead and delays. Improper management also results in challenges in identifying and addressing the impacts. The technology addresses a critical need for solutions capable of operating across multiple microservice codebases, supporting developers with change impact analysis to prevent inconsistencies and production errors in the system.
This tool is designed to automatically generate a comprehensive system representation overview (intermediate representation) by analyzing codebase artifacts, offering practitioners insights into the potential impacts of individual changes on the system-wide interconnected components. In addition, the tool is designed to integrate seamlessly into the existing development and operations pipelines, serving as a quality assurance checkpoint at each stage of system changes.
This technology may move the distributed systems community toward a more efficient, systematic process, improving evolvability and reliability.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Arizona
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