LLM-Generated Microservice Implementations from RESTful API Definitions
Saurabh Chauhan, Zeeshan Rasheed, Abdul Malik Sami, Zheying Zhang,, Jussi Rasku, Kai-Kristian Kemell, and Pekka Abrahamsson

TL;DR
This paper introduces a system leveraging Large Language Models to automate RESTful microservice development from API specifications, enhancing speed and reducing manual effort in software engineering.
Contribution
It presents a novel LLM-based approach for automated microservice generation and refinement guided by API definitions and log analysis, improving development efficiency.
Findings
System accelerates microservice development process.
Automates code generation and debugging tasks.
Practitioners find it useful for rapid prototyping.
Abstract
The growing need for scalable, maintainable, and fast-deploying systems has made microservice architecture widely popular in software development. This paper presents a system that uses Large Language Models (LLMs) to automate the API-first development of RESTful microservices. This system assists in creating OpenAPI specification, generating server code from it, and refining the code through a feedback loop that analyzes execution logs and error messages. By focusing on the API-first methodology, this system ensures that microservices are designed with well-defined interfaces, promoting consistency and reliability across the development life-cycle. The integration of log analysis enables the LLM to detect and address issues efficiently, reducing the number of iterations required to produce functional and robust services. This process automates the generation of microservices and also…
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Taxonomy
TopicsSoftware System Performance and Reliability · Service-Oriented Architecture and Web Services · Cloud Computing and Resource Management
