Tooprani Sravani

Experienced in requirement analysis using DOORS for CAN-based HIL systems, DBC creation, and panel design in Vector CANoe. Skilled in CAPL scripting, manual testing with CANoe and CANalyzer (UDS services), and test automation in PCAN Explorer using Python. Proficient in ECU software flashing with CANape, Vector Vflash, and Trace 32. Hands-on experience in defect analysis, issue reproduction, regression, and confirmation testing. Familiar with dSPACE ControlDesk, Configuration, and AutomationDesk.

Designed and implemented a flexible Python-based sensor analysis framework for HMI applications, ensuring an easy-to-use API and adaptable data transfer via CAN, LIN, JTAG/Trace32, and UART. Developed multiple Python packages for versatile usage, including time-series data handling, pipeline orchestration, and optional graphical visualization components.

Developed and redesigned components for evaluating capacitive touch matrices in automotive displays. Built a configurable touch evaluation library using YAML for project-specific adaptations. Implemented a Python tool to parse YAML files and generate source files dynamically.

I have experience in testing within sandbox environments using GDE for ad-hoc testing and data verification. Skilled in creating test cases with Ab Initio, executing SQL queries for validation, and utilizing the Control Center for job monitoring. I’m proficient in debugging, automating tests, and generating detailed reports.