QA Maturity Assessment

Robot Arm Based Testing

Robot Arm Based Testing

Validating end to end use case scenarios in new age digital applications using conventional approaches are challenging due to rich user interaction inputs such as gestures via touch screens, signals via sensors like GPS, accelerometer, barometer, and NFC, etc.

Gadgeon’s non-Intrusive validation approach using Robot aided test automation framework could give a completely new form and benefits of testing. In our approach, we would make no assumptions, relying on the device’s connectivity, display and other physical interfaces between the user and the application.

We offer non-intrusive validation for applications across embedded devices, panel pc / desktop, and mobile applications.

  • Connectivity testing
  • User interface functionality and performance validation
  • Long term duration testing
  • Manufacturing test support for production houses.
  • Interface and functionality testing
  • User interface and localization testing
  • Long run stability testing
  • Functionality testing
  • Usability testing
  • Digital coverage testing
  • Automated long duration testing
  • Built in robotic arm controller libraries for emulating the real user experience
  • Relay/Servomotor for simulating the power cycle / button press events.
  • Light sensor module for validating the visual indications.
  • Voice and text conversion libraries for voice/text commands verifications.
  • Built in libraries for Image recognition and OCR (Optical Character Recognition).
  • Supports configurable option that supports recovery from fatal errors in target devices
  • Built in libraries to compile and build embedded, application for various system components at scheduled intervals
  • Built in libraries to Deploy embedded/firmware/application images on target devices or environments
  • Capability to add more realistic test cases for an end to end use case level validation.
  • Improved test precision and repeatability
  • Experienced Test architects with deep knowledge in hardware and firmware development of complex systems.
  • High precision control of Robotic arm based on image processing using Machine Learning or traditional methods to handle dynamic content in UI verification.

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