NOTE: the code related to the publication on SEAA-2023 can be found under the seaa-2023 tag.
μsVision - MSA Architectural Pattern and Smell Detector.
μsVision is a detection tool written in Kotlin that identifies patterns and smells within microservices architectures. Leveraging microservices metrics, it analyzes and generates detailed reports about your applications. Because it relies on metrics for analysis, this tool is technology-agnostic and does not require access to source code.
Our primary objectives are to:
- Automate Pattern Detection: Streamline the process of identifying patterns in MSA.
- Detect Architectural Debts: Uncover architectural debts within microservices architectures.
- Enable High-Scale Analysis: Provide a tool capable of conducting large-scale analysis in MSA.
Additionally, the software assists with:
- Structured Metric Mapping: Offers a systematic method to map microservices metrics.
- Pattern and Anti-Pattern Detection: Identifies both patterns and anti-patterns.
- Architectural Debt Prioritization: Helps prioritize architectural debts effectively.
μsVision is designed for various users, including:
- Software Developers
- System Administrators
- IT Managers
- IT Architects
We love contributors.
Would you like to contribute or share your insights?
Your contributions are welcome. Create an issue or pull request on GitHub to get started.
If you appreciate this project, you can also show your support by starring the repository. We truly appreciate your recognition.
Thank you for being a part of our community!
This project is licensed under the terms of the MIT license.