Improving Test Efficiency through Data Construction Platform and API Integration: A Case Study

Introduction

Testing can be perceived as a heavy workload, but with the right techniques and tools, efficiency can be greatly improved, especially when integrating standardized requirements.

Stage One: Discover and Solve Problems

1. Leveraging Tools for Internal Efficiency

As third‑party partners increased, manual data construction became costly; a low‑code front‑end platform combined with back‑end Java code was introduced to parameterize interfaces, allowing quick generation of mock data through simple page inputs.

API Interface Platform

To avoid duplicated maintenance, a shared API platform was adopted, enabling unified interface definitions and reducing the time needed for online regression testing.

2. Tool Empowerment – Freeing Hands

Repeated data construction for third‑party integration caused unpredictable delays; a self‑service verification approach was explored, allowing partners to obtain required data autonomously.

Self‑Service Verification Scheme

Key elements included providing HTTP‑based interfaces, exposing only a test environment, designing core and auxiliary APIs with log IDs for traceability, and implementing a shared secret key mechanism for access protection.

Documentation was prepared to guide third parties through the verification process, resulting in a reduction of integration time from five days to 1.5 days.

Stage Two: Replicating the Model and Standardization

1. Model Replication – Proactive Approach

Successful practices were distilled into repeatable patterns and applied to other business lines such as recycling and sales, continuously optimizing the capabilities offered.

2. Standardization Construction

Documentation and processes were standardized and presented on a SaaS platform, becoming an essential part of developers' testing and integration workflow and recognized as a standard capability by product teams.

Conclusion and Outlook

The two‑stage effort significantly shortened testing cycles, reduced manual effort, and established a scalable, efficient testing process; future work will focus on further automating online interactions to minimize human involvement.