Regarding a testing framework designed to assess performance and compatibility in IoT systems

Modern Internet of Things (IoT) systems operate in highly heterogeneous environments with billions of devices, diverse protocols, and continuously evolving software versions. The primary challenge lies in ensuring performance under high load while maintaining cross-platform compatibility. Traditional testing methods address these factors independently, missing a critical class of errors that emerge only at their intersection-termed PC-Critical errors. This paper proposes PC-Testing, an integrated framework combining platform diversity modeling, distributed load simulation, and the Performance Degradation Index (PDI). Deployed on an Intelligent Transportation System (ITS) with 10,000 virtual devices using Locust, Appium, and NetEm, the framework revealed that the worst-case scenario (Android 8 with 300ms network latency) caused nonlinear degradation of 37.1× and 0.61% data loss-significantly worse than theoretical predictions. Experimental validation on Google Colab demonstrates the framework’s effectiveness in detecting PC-Critical errors before production deployment.