White‑Box Analysis in Game Feature Testing: Definition, Significance, and Practical Practices

In functional testing, the author shares many skill‑related test cases and demonstrates how white‑box analysis helps resolve difficult issues.

What is white‑box analysis? It is a broad concept that combines static inspection (code, resources, configuration tables) and interface testing, covering the entire lifecycle from requirement (test left‑shift) to online and post‑release (test right‑shift). The goal is to examine internal structures, clarify implementation logic, and enable cross‑team knowledge sharing.

For small operations or systems, white‑box analysis increases test accuracy and efficiency; for large new systems it can influence planning, development, testing, online monitoring, and even automation script development.

Significance of white‑box analysis

It improves precision in functional testing, speeds up issue localization, and reduces manual effort by exposing hidden code problems early.

Testing workflow (left‑shift)

The workflow consists of four stages: requirement, testing, online, and stable release. The author defines left‑shift as the requirement stage only, focusing on understanding and analyzing the logic before development.

Examples include analyzing a new attribute requirement in an old game, where the QA used logs and source code to discover hidden calculation layers, and examining skill damage calculation to avoid design misunderstandings.

# 某个老项目，策划和程序都迭代了多次，有一天：
某数值策划：“我想要给技能结算加个新数值系统，但我猜里面会乘以某些系数，比如A，至于是哪些系数以及怎么乘，现在估计只有代码知道了。”
我：“好的。”（内心：***）

White‑box analysis in testing phase

Typical white‑box techniques include reviewing server‑side code for common errors such as faulty conditional statements or similarly named method calls, and adding logs to verify data during runtime.

Condition‑checking errors in reward chest configuration.

Misnamed method calls causing incorrect logic.

White‑box analysis in black‑box testing

When bugs are hard to reproduce, white‑box analysis helps locate relevant code, add logs, and verify data. Examples include AI behavior failures, precision checks for skill damage, and buff effect inconsistencies.

Right‑shift analysis (online and stable release)

During online monitoring, white‑box analysis quickly identifies root causes, such as an unexpected coefficient affecting threat value in a boss‑kill reward scenario, allowing rapid fixes.

Personal insights

Traditional methods involve log tracing, monitoring client‑server interfaces, searching IDE for exposed methods, and iteratively adding logs until the issue is pinpointed.

Tips include reusing saved interface scripts, documenting code reviews, and maintaining a knowledge base for future reference.

Summary

Timely organization and documentation of white‑box analysis findings are essential. QA should not rely solely on developers or designers; instead, combine black‑box verification with white‑box techniques to ensure robust quality.

Thank you for reading.