Mitch English, Product Development Team Lead at Inertia, dives into the QP framework for embedded systems. He discusses his experience implementing QP in a medical device project, emphasizing its efficiency in managing complex state machines. The conversation covers event communication strategies, revealing how a shift to a publish-subscribe pattern could enhance flexibility. Mitch also highlights the importance of starting simple and gradually increasing complexity, and he underscores the QP framework's advantages over traditional solutions in real-time applications.
The QP framework's actor model and message-passing design significantly reduce concurrency issues, streamlining embedded systems development.
Utilizing hierarchical state machines within QP enhances code maintainability and simplifies complex state management, improving overall application clarity.
Deep dives
Introduction to the QP Framework
The QP framework, developed by Miro Samick, implements an actor model where active objects operate within their own threads and communicate solely through message passing. This design approach addresses concurrency issues that arise in traditional real-time operating systems (RTOS), making it easier to manage multiple processes. The framework also features a hierarchical state machine, simplifying complex state management by allowing transitions to be defined more succinctly, which helps mitigate the common pitfalls of homegrown systems. This comprehensive architecture makes it significantly more efficient for developers to build, maintain, and troubleshoot applications.
Benefits of Using Hierarchical State Machines
Hierarchical state machines in the QP framework help to manage complexity in applications by allowing states to be nested and shared amongst various subsystems. For instance, if a button has a pressed state, it can also include substates such as 'pressed for 10 seconds,' avoiding the need for a redundant state management approach. This reduces code duplication and enhances maintenance as the exit handlers for nested states are simplified, allowing developers to specify behaviors in one place. By isolating the intricate sequence of states, such as those involved in device management, developers gain clarity and can focus on high-level application logic more effectively.
Adopting Asynchronous Programming
The QP framework embraces asynchronous programming by requiring developers to handle state transitions and events explicitly, as opposed to using blocking code typical in traditional RTOS. This allows for greater control over event processing and minimizes issues like priority inversion, giving developers higher confidence in system behavior. By maintaining an event queue and ensuring that states reflect the actual operations occurring, testing and debugging become simpler and more intuitive. As a result, the architecture becomes not only more robust but also facilitates clearer documentation and easier collaboration with non-technical stakeholders.
Best Practices and Recommendations
For those starting with the QP framework, it's advisable to read Miro Samick's introductory book and experiment with example code from the repository to grasp fundamental concepts. It is beneficial to begin with simple projects, like a basic LED blinking example, as this approach minimizes overwhelm from the framework's numerous features. As development progresses, leveraging the publish-subscribe mechanism can enhance decoupling between components, simplifying unit testing and event logging. Overall, adopting a structured architecture with clearly defined active objects fosters seamless integration and scalability for future projects.
The episode features a discussion with Mitch English, a product development team lead at Inertia, about using the QP (Quantum Platform) framework for embedded systems development. Mitch and Jeff recently collaborated on a medical device project where they successfully implemented QP. The framework, created by Miro Samek, implements the actor model with active objects running in their own threads and communicating via messages. This approach helps avoid common concurrency issues found in traditional RTOS implementations.
The discussion covers how QP's hierarchical state machine framework makes it easier to manage complex state transitions and system behaviors. They share their experience using QP on a blood analyzer project, discussing how they structured the code with different layers of abstraction and maintained multiple test builds throughout development. The team found that QP's architecture helped make the system's complexity more manageable and testable.
A key learning they shared was about event communication - while they initially used direct posting between active objects, they later realized that using the publish-subscribe pattern more extensively would have made testing easier and the system more flexible. They recommend starting with QP's simple examples and gradually building up complexity rather than trying to implement complex examples right away.
Key Timestamps: 00:00:00 - Introduction and background 00:03:00 - Overview of QP framework and actor model 00:06:30 - Discussion of hierarchical state machines 00:19:30 - Project architecture and implementation approach 00:27:00 - Testing strategies and development process 00:30:00 - Team structure and collaboration 00:35:00 - Hardware/software integration 00:39:00 - Advice for getting started with QP 00:41:50 - About Inertia and contact information