Automated API Testing Framework for Scalable Service Oriented Applications

Abstract

Scalable service-oriented applications require reliable API testing because many endpoints, authentication rules, dependencies, and concurrent requests must be validated together. This study presents an automated API testing framework that combines specification-based request generation, response-schema validation, authentication testing, dependency-flow analysis, error-handling checks, and concurrent-load evaluation. The framework was tested across six increasing service-request levels and compared with script-based API testing and manual API validation. Results showed that the proposed approach maintained a fault detection rate above 94% and reached 97.3% at the highest load level. Its normalized average response time increased gradually from 32% to 61%, remaining lower than the comparison methods. The framework also detected interface errors, access-control failures, workflow problems, timeouts, and incorrect response structures under heavy demand. The proposed approach can support continuous testing, reduce manual effort, improve scalability assessment, and strengthen API reliability in large service-oriented software systems before deployment across complex and rapidly changing enterprise environments.