Gokul A. D
Senior Embedded Software Tester
Mysuru
Summary
Bringing 3.5 years of experience in Automotive Embedded Software Testing, specializing in the verification and validation of infotainment ECU systems. Expertise spans unit testing, integration testing, system testing, and acceptance testing. Hands-on experience in tools such as CANoe, Hardware-in-the-Loop (HIL) setups, NI cards, and Automotive Audio Bus (A2B) technology, equipping for effective management and enhancement of automotive software solutions.
Overview
3
3
years of professional experience
Work History
Senior Embedded Software Tester
L and T Technology Services
09.2021 - Current
- Project: Automotive Infotainment ECU Verification and Validation (BOSE Amplifier).
- Consistently ensured the timely delivery of 35 validations across four different software projects for General Motors(GM).
- Demonstrated a strong commitment to meeting project timelines and requirements for full, focused, sanity, and tuning validations within set deadlines.
- Automated 85% of functional requirements by developing test scripts.
- Implemented the automation using an NI-based HIL setup and Python, with .NET to facilitate communication at the hardware driver level.
- Utilized CANoe and CANalyzer for diagnostics and audio routing in bench setups, ensuring robust system performance and reliability.
- Performed comprehensive testing and validation of automotive infotainment systems using A2B (Automotive Audio Bus) technology, ensuring seamless audio transmission and robust, error-free data transfer across devices in both upstream and downstream configurations.
- Automated Unified Diagnostic Services (UDS) functionalities using NI HIL setup, including session control, reading and writing DIDs, DTC's and checking Negative Response Codes (NRCs) such as invalid length and sequence error.
- Managed requirements with JAMA for full traceability in the software development lifecycle, maintained project documentation and collaborated with team members using Confluence, handled version control with SVN, and tracked and reported bugs through JIRA to streamline defects and ensure timely resolutions.
Education
B.Tech/B.E. - Electronics/Telecommunication
University of Kerala
Thiruvananthapuram 07.2013 - 1 2017
M.Tech - Robotics and Automation
College of Engineering
Thiruvananthapuram 06.2019 - 1 2021
Skills
- Programming Languages : Python, C, C, CAPL
- Framework : OOPS, Robot Framework, Pytest Framework
- Automotive Protocols : CAN, A2B, UDS
- Operating System : Windows, Linux, Robotic Operating System (ROS)
- Hardware Tools : Ni HIL Setup, Vector CAN/LIN(VN1630A), Mentor A2B analyzer, Mentor A2B bus monitor, Picoscope
- Testing and Quality Assurance :Test Planning, Test case design, Test Execution, Defect Tracking and Reporting, Automotive ECU testing
- Software Tools : Jira, Jama, Confluence, Vector CANalyzer, Vector CANoe, Mentor A2B analyzer/bus monitor, GIT, SVN
- Python Libraries : TensorFlow, pytest, socket, PyBullet etc
Accomplishments
- Promoted to Engineer (25th September,2022).
- Promoted to Senior Engineer (10th October,2024)
- Spot Award, Awarded for supporting HIL maintenance.
- Filed For Patent 'Methods And System For Optimizing ADAS Testing' -202341085611 , A system to develop an efficient automated testing tool, which analyses ADAS tones using a trained AI model. (December,2023)
Internship
L&T Technology Services (LTTS) : Development of a workspace for verification and validation of automotive ECU in a HIL setup., Written Functions using python for automotive diagnostics., Diagnosed and validated internal relays of the HIL for Diagnostic Trouble Codes (DTCs) using NI-max.
Projects
- Method and System for Optimizing ADAS testing : Developed a machine learning-based Advanced Driver Assistance System (ADAS) testing tool featuring a pre-trained noise cancellation and classification module. This tool records ADAS announcements from the infotainment ECU, classifies them, and validates the accuracy of the tone produced, significantly reducing manual testing efforts.
- Brick Laying Robot using Deep Reinforcement Learning : Developed a PyBullet-based simulation featuring a 6 DOF manipulator and a group of bricks, where the manipulator is trained using deep reinforcement learning and Markov decision processes to construct a wall-like structure.
- Cornea Controlled Wheel Chair : Developed a system utilizing IR sensors to track the eye movements of paralyzed patients, employing C programming for control logic. This setup enables an Arduino to direct the wheelchair’s motor, allowing movement in the direction preferred by the patient.
Timeline
Senior Embedded Software Tester
L and T Technology Services
09.2021 - Current
M.Tech - Robotics and Automation
College of Engineering
06.2019 - 1 2021
B.Tech/B.E. - Electronics/Telecommunication
University of Kerala
07.2013 - 1 2017
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