Below are the core functional requirements for our SSD validation proof of concept:
TLA+ File Integration:
The system must be able to process and interpret TLA+ files, enabling the generation of test sequences for SSD validation.
This will allow our test cases to be directly linked to formal models, improving test accuracy and coverage.
Pluspy Integration:
We need to integrate the Pluspy framework to facilitate the execution of TLA+ models and generate the required test sequences from the model.
This integration will be critical to ensure compatibility with the TLA+ formal specification and enhance the quality of our testing.
Command Execution via Python:
The system must provide functionality to execute NVMe-related commands, such as `mvme-cli`, directly from Python.
This is essential for automating the interaction with NVMe drives, allowing for easier integration and test execution.
Error Logging and Traceability:
We need a robust logging system that tracks errors and provides traceability. This will help identify the root cause of any test failures and improve debugging.
It will also store logs that trace test sequence execution, making it easier to recreate and address any anomalies.
Development Process
The development of this system will be carried out in phases to address different parts of the validation framework:
Phase 1: Command Execution:
The first step will involve enabling the ability to call NVMe commands from Python, ensuring that the system can interact with NVMe drives in a straightforward way.
This phase will also involve implementing basic error handling to ensure commands are executed successfully.
Phase 2: Pluspy Integration:
Once the basic command execution is functioning, the next step will be to integrate the Pluspy framework. This will allow the system to interpret TLA+ models and generate test sequences.
This phase will require modifying the existing Pluspy API to better suit our needs for NVMe testing.
Phase 3: Random Test Generation:
In this phase, we will implement a random test generation system based on TLA+ models. This will ensure that a wide variety of test scenarios are generated to test edge cases and uncommon behaviors.
The system will generate random seeds, ensuring that the tests are diverse and comprehensive.
Phase 4: Error Handling and Logging:
The final phase will focus on enhancing the error logging and traceability system. This will allow us to identify failures quickly and track the specific sequence of events that led to the error.
Additionally, we will optimize the system to ensure that test logs do not add significant overhead during test execution.
Document Reference
For further details, refer to the full project documentation:
