End-to-End Test Coverage Metrics in Microservice Systems: An Automated Approach

TL;DR

This paper introduces automated metrics and a visualization approach to evaluate and improve end-to-end test coverage of microservice system endpoints, addressing gaps in testing completeness.

Contribution

It presents novel coverage metrics and an automated tool for assessing E2E test completeness in microservice architectures, with a case study validation.

Findings

The approach effectively identifies coverage gaps in microservice endpoints.

Automated metrics provide conclusive feedback on test suite completeness.

Visualization guides testers to improve testing strategies.

Abstract

Microservice architecture gains momentum by fueling systems with cloud-native benefits, scalability, and decentralized evolution. However, new challenges emerge for end-to-end (E2E) testing. Testers who see the decentralized system through the user interface might assume their tests are comprehensive, covering all middleware endpoints scattered across microservices. However, they do not have instruments to verify such assumptions. This paper introduces test coverage metrics for evaluating the extent of E2E test suite coverage for microservice endpoints. Next, it presents an automated approach to compute these metrics to provide feedback on the completeness of E2E test suites. Furthermore, a visual perspective is provided to highlight test coverage across the system's microservices to guide on gaps in test suites. We implement a proof-of-concept tool and perform a case study on a well-established system benchmark showing it can generate conclusive feedback on test suite coverage over system endpoints.