A Consumer-Driven Contract-Based Approach to Verifying User Interface Integration in Microservices Architectures
Abstract
Context: Microservices Architectures (MSA) enhance deployment velocity and service autonomy, but traditional End-to-End (E2E) User Interface (UI) testing often reintroduces systemic coupling, leading to slow feedback cycles and high-test flakiness. This friction undermines the core benefits of MSA.
Objective: This research proposes and evaluates a novel, Consumer-Driven Contract (CDC) testing framework—the CDC-UI Hybrid Model—to strategically replace brittle E2E tests for verifying UI-to-backend integration in MSA environments. The goal is to harmonize testing across service boundaries and the presentation layer, accelerating the feedback loop.
Methodology: The study introduces a two-layer contract strategy: standard service-to-service CDC, complemented by a dedicated UI-Consumer Contract where the UI layer defines its expectations of the Backend-for-Frontend (BFF)/API Gateway. A simulated MSA case study was used to compare a baseline E2E-heavy approach against the proposed CDC-UI hybrid model, measuring key indicators such as test execution time, flakiness rate, and defect detection efficacy.
Results: The implementation of the CDC-UI Hybrid Model yielded a notable reduction in overall integration test execution time and a significant decrease in the test suite's non-deterministic flakiness. The approach successfully shifted the detection of UI-backend integration faults earlier in the development pipeline, correlating with a lower Defect Escape Rate.
Conclusion: The CDC-UI Hybrid Model provides a highly effective and pragmatic solution for validating UI integration in microservices. It aligns strategically with modern testing practices, dramatically improving test stability and accelerating the feedback loop, thereby preserving team autonomy and realizing the velocity potential of distributed architectures.
Keywords
References
Similar Articles
- Prof. Lucas F. Oliveira, SM9-ENHANCED KEY-POLICY ATTRIBUTE-BASED ENCRYPTION: DESIGN, ANALYSIS, AND APPLICATIONS , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 06 (2025): Volume 02 Issue 06
- Dr. Julian C. Vance, Prof. Anya Sharma, Synergistic Integration of AI and Blockchain: A Framework for Decentralized and Trustworthy Systems , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 08 (2025): Volume 02 Issue 08
- Felicia S. Lee, A COMPARATIVE ANALYSIS OF SERVICE MESH PROXY ARCHITECTURES: FROM SIDECARS TO AMBIENT AND PROXYLESS MODELS IN CLOUD-NATIVE ENVIRONMENTS , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Dr. Felicia S. Lee, Ivan A. Kuznetsov, Bridging The Gap: A Strategic Framework for Integrating Site Reliability Engineering with Legacy Retail Infrastructure , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 11 (2025): Volume 02 Issue 11
- Tang Shu Qi, Autonomous Resilience: Integrating Generative AI-Driven Threat Detection with Adaptive Query Optimization in Distributed Ecosystems , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 11 (2025): Volume 02 Issue 11
- Dr. Rohan S. Whitaker, Predictive and Intelligent HVAC Systems: Integrative Frameworks for Performance, Maintenance, and Energy Optimization , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 10 (2025): Volume 02 Issue 10
- Dr. Alejandro Martínez, Explainable Artificial Intelligence As A Foundation For Trust, Sustainability, And Responsible Decision-Making Across Business And Healthcare Ecosystems , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 01 (2026): Volume 03 Issue 01
- Dr. Arjun S. Patel, Prof. Elena D. Petrovna, CONVERGENT DATABASE ARCHITECTURES: MULTI-MODEL DESIGN AND QUERY OPTIMIZATION IN NEWSQL SYSTEMS , International Journal of Modern Computer Science and IT Innovations: Vol. 2 No. 02 (2025): Volume 02 Issue 02
- Dr. Elena Marovic, Hyperautomation-Driven Financial Workflow Transformation: Integrating Generative Artificial Intelligence, Process Mining, and Enterprise Digital Architectures , International Journal of Modern Computer Science and IT Innovations: Vol. 3 No. 01 (2026): Volume 03 Issue 01
You may also start an advanced similarity search for this article.