Best Practices for Developing Real-time Embedded Systems

Development teams are always under pressure to deliver faster and at lower costs, but this is becoming more challenging as system complexity has risen exponentially with features for IoT and Machine Learning. The increased complexity can easily handcuff a development team and lead to not just longer development cycles with higher costs but also lower quality products.

In this session, we will explore best practices for developing real-time embedded systems that will help the modern developer stay on track and produce a quality product within their development cycle. We will explore best practices ranging from how to properly architect a system for scalability, how to manage a development cycle, secure and test a system. We will also discuss best practices for using frameworks and open source software.

The Bottom Line

Problem: Modern real-time embedded projects are growing in feature scope (IoT, ML, richer UIs) while budgets and schedules shrink, producing fragile, tightly coupled, hard-to-test systems that miss deadlines and carry high lifecycle costs.

Solution: Apply a disciplined, metrics-driven SDLC with architecture-first design (clear abstractions, SOLID-like principles), selective use and careful auditing of frameworks/open-source, and automated testing/CI pipelines that include on-target hardware tests. The talk gives pragmatic patterns and checklists to make this repeatable.

Technical Prerequisites

• Comfort programming in C and/or C++ (basic API design, modularity); familiarity with higher-level languages (Python) is helpful but not required.
• Understanding of RTOS concepts: tasks/threads, interrupts, synchronization primitives, and common RTOS trade-offs.
• Familiarity with version control workflows (Git/Bitbucket/GitLab/GitHub) and basic build systems/toolchains (cross-compilers, linker, flash tools).
• Basic software-engineering concepts: requirements → design → implementation → test → maintenance (SDLC), unit testing, and integration testing.
• Introductory knowledge of embedded security concepts (keys/certificates, threat modeling) and hardware isolation primitives (MPU, TrustZone) is useful for the security sections.
• Comfort reading architecture diagrams (component, layered, and data-flow diagrams) and simple UML is helpful for following the design advice.

Key Concepts

• Metrics-driven SDLC: Define simple, automated metrics (burndown, function size, cyclomatic complexity, test coverage, defect removal efficiency) and periodically audit the SDLC to tune process cost vs. value.
• Architecture-first & Abstraction: Design layered, modular architectures before coding. Use hardware and OS abstraction layers to minimize coupling and enable portability and reuse.
• Frameworks & OSS Selection: Use unbiased decision tools (K-T matrix) to choose frameworks; statically analyze and audit any third-party code you adopt and build exception documentation for non-compliant libraries.
• Automated Testing & CI/CD: Automate builds, static analysis, unit tests (TDD if possible), and include hardware-in-the-loop/on-target tests in CI. Don’t rely only on server-side tests—verify on real hardware.

Keywords

• SDLC — Software Development Life Cycle: requirements, design, construction, testing, maintenance; choose a model (waterfall, V-model, agile) appropriate to domain and regulation.
• SOLID — Set of design principles (Single responsibility, Open/Closed, Liskov substitution, Interface segregation, Dependency inversion) to improve modularity and extensibility.
• HAL — Hardware Abstraction Layer: an API layer isolating application code from vendor-specific registers and peripherals to ease porting.
• PSA — Platform Security Architecture: ARM’s framework for threat analysis, secure architecture, implementation, and certification for device security.
• K-T matrix — Kepner-Tregoe style weighted decision matrix used to evaluate and rank framework/RTOS options objectively.
• CI/CD — Continuous Integration/Continuous Deployment: automated build, test, and (optionally) release pipelines for rapid, repeatable verification.
• TDD — Test-Driven Development: write failing tests first, then implement code to pass them; helps build and maintain regression suites.

Toolbox

• Version control: Bitbucket, GitLab, GitHub (any Git hosting).
• Project management / planning: Jira, Wrike, Trac; time tracking: Harvest.
• CI / build servers: Jenkins (example used), or hosted CI providers.
• Unit test frameworks: CppUTest (example); other embedded test frameworks are applicable.
• Static analysis / complexity metrics: your compiler toolchain warnings, static analyzers (MISRA checks, cyclomatic complexity tools).
• UML / architecture tools: Enterprise Architect, Visual Paradigm.
• RTOS / middleware examples: FatFs (file system), ThreadX/FileX (middleware examples); evaluate via K-T matrix before selection.
• Hardware primitives: TrustZone, MPUs for hardware isolation and security layering.

Takeaway

After watching, you will be able to start (or improve) an auditable, metrics-driven SDLC that emphasizes architecture-first design with clear abstraction layers and an automated CI pipeline that includes on-target testing—reducing coupling, lowering cost of change, and improving time-to-market.

Final Note

Jacob Beningo’s talk is practical, well-paced, and grounded in years of embedded consulting across industries. He balances broad coverage with concrete, repeatable actions (metrics, SOLID-like design, K-T selection, CI with hardware tests) and emphasizes the discipline required to make best practices work in real teams. If you want actionable ways to make your next embedded project more predictable and maintainable, this session is worth your focused attention.