Our Customer’s Struggle with In-House Validation Tool and the Need for a More Efficient Solution
A leading semiconductor company renowned for its innovative chip designs and industry leadership relied on an in-house tool to validate I2C and I3C protocols. However, the tool lacked scalability and was challenging to enhance for evolving industry needs. Setting up the validation environment took at least three months and required constant expert support. As validation grew more complex, each update demanded extensive refactoring, diverting engineering resources from core testing and analysis.
1. Executing a Single Temperature Validation Cycle Took Approximately 4 Hours
The customer sought to validate whether the Device Under Test (DUT) adhered to the required timing specifications and behavior across a range of operating temperatures. The in-house validation tool took approximately 4 hours to validate a single temperature, as it needed extensive manual configuration for each test, setting up parameters, and verifying results.
2. Only Achieve Rise Time Down to a Minimum of 40 ns
The customer needed to characterize the rise and fall time behavior of the DUT. Their in-house tool, however, could only achieve rise time down to a minimum of 40 ns. This limitation restricted their ability to accurately characterize the DUT’s actual response and determine its fastest possible transitions.
3. Manual & Complex Bit-Level Configuration
The in-house validation tool required engineers to manually configure high/low signal transitions for each bit and define precise timing parameters. For clock and data lines, this meant programming each bit sequence manually, increasing validation time and complexity. Additionally, engineers needed in-depth protocol knowledge to set up and debug signal generation.
4. Limited Coverage & Flexibility in In-House Validation
The customer’s in-house validation tool was built for specific test cases, limiting the overall coverage.
- Key gaps in electrical, timing, and functional validation increased the risk of missing fault and glitch test conditions.
- Expanding coverage, such as testing frequency limits, voltage levels, and fault injection, required significant effort.
- Each new validation parameter demanded manual updates, scripting, and debugging, making the process slow and resource-intensive.
These challenges made it difficult to scale validation efficiently.