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Automated CPS Testing Framework - Automated continuous testing framework combining SIL simulation, HIL simulation, and actual robotic platform testing... Activation: CPS testing, cyber-physical systems, robotic testing.

hiyenwong By hiyenwong schedule Updated 6/3/2026

name: automated-cps-testing description: "Automated CPS Testing Framework - Automated continuous testing framework combining SIL simulation, HIL simulation, and actual robotic platform testing... Activation: CPS testing, cyber-physical systems, robotic testing." version: v1.0.0 last_updated: 2026-04-14 source: arXiv:2604.11708v1

Automated CPS Testing Framework

Overview

Source Paper: ACT: Automated CPS Testing for Open-Source Robotic Platforms
Authors: Aditya A. Krishnan, Donghoon Kim, Hokeun Kim
Published: 2026-04-13 | Category: cs.SE

Description

Automated continuous testing framework combining SIL simulation, HIL simulation, and actual robotic platform testing

Core Concepts

  • software-in-the-loop
  • hardware-in-the-loop
  • continuous integration
  • robotic platform testing
  • open-source CPS

Activation Keywords

  • CPS testing
  • cyber-physical systems
  • robotic testing
  • continuous testing
  • SIL/HIL simulation
  • ROS testing
  • 自动化CPS测试

Methodology

Problem Statement

Open-source software for cyber-physical systems (CPS) often lacks robust testing involving robotic platforms, resulting in critical errors that remain undetected.

Key Contributions

  1. Software-In-The-Loop: Implements software-in-the-loop to achieve systematic optimization
  2. Hardware-In-The-Loop: Leverages hardware-in-the-loop for efficient execution
  3. Continuous Integration: Utilizes continuous integration for enhanced performance

Implementation Workflow

Step 1: Problem Formulation

  • Define the system objectives and constraints
  • Identify key performance indicators
  • Establish evaluation metrics

Step 2: Framework Setup

  • Configure the software-in-the-loop components
  • Initialize hardware-in-the-loop parameters
  • Set up monitoring and telemetry

Step 3: Execution

  • Run the optimization loop
  • Collect performance data
  • Iterate based on feedback

Step 4: Validation

  • Verify solution quality
  • Compare against baselines
  • Document lessons learned

Applications

  • Systems engineering projects
  • Distributed system optimization
  • Autonomous system validation
  • Multi-agent coordination

References

Tags

systems engineering, cs.SE, software-in-the-loop, hardware-in-the-loop, continuous integration, robotic platform testing, open-source CPS

Install via CLI
npx skills add https://github.com/hiyenwong/ai_collection --skill automated-cps-testing
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