Adaptive Application Structure - AUTOSAR Adaptive Platform

Deployment Unit

An Adaptive Application is deployed as a Software Package — a zip/tar archive containing:

One or more ELF executables (the Adaptive Application binaries)
Application Manifest (application_manifest.json) — per-process configuration
Service Instance Manifest (service_instance_manifest.json) — SOME/IP/DDS binding
Optional initialisation scripts and resource files

Software Package Layout

SensorApp.swcl (zip)
├── bin/
│   └── SensorApp          (ELF executable)
├── manifests/
│   ├── application_manifest.json
│   └── service_instance_manifest.json
└── META-INF/
    └── MANIFEST.MF        (package metadata, version, signature)

Entry Point Pattern

Every Adaptive Application follows the same lifecycle skeleton in main():

C++main.cpp

#include <ara/core/initialization.h>
#include <ara/exec/application_client.h>
#include "sensor_service_skeleton.h"

int main() {
    // 1. Connect to platform — MUST be first ara:: call
    ara::core::Initialize();

    // 2. Construct skeleton (registers service interface with CM)
    SensorServiceSkeleton skel(
        ara::core::InstanceSpecifier{"SensorApp/SensorService/Instance0"});

    // 3. Start serving
    skel.OfferService();

    // 4. Report Running state to Execution Manager
    ara::exec::ApplicationClient appClient;
    appClient.ReportApplicationState(
        ara::exec::ApplicationState::kRunning);

    // 5. Application loop
    while (!shutdown_requested) {
        auto data = ReadIMU();
        skel.ImuEvent.Send(data);
        std::this_thread::sleep_for(std::chrono::milliseconds(10));
    }

    // 6. Graceful shutdown
    appClient.ReportApplicationState(
        ara::exec::ApplicationState::kTerminating);
    skel.StopOfferService();
    ara::core::Deinitialize();
    return EXIT_SUCCESS;
}

⚠️ Mandatory Sequence

ara::core::Initialize() must precede any other ara:: call. Calling ara::log, ara::com, or ara::exec before initialization results in undefined behaviour. ReportApplicationState(kRunning) must be called within the EM-configured startupTimeout — failure to do so causes EM to send SIGTERM.

Threading Model

ara::com uses an internal dispatcher thread pool to invoke event callbacks and method handlers. Rules:

Never block on the ara::com callback thread (no std::this_thread::sleep_for, no blocking I/O).
Dispatch long work to a separate std::thread or a thread pool.
ara::core::Future callbacks (.then()) also run on the dispatcher pool.

C++consumer.cpp

// WRONG: blocks ara::com dispatcher
proxy.MyEvent.SetReceiveHandler([&] {
    proxy.MyEvent.GetNewSamples([](auto sample) {
        heavyComputation(*sample); // blocks! do NOT do this
    });
});

// CORRECT: dispatch to worker thread
proxy.MyEvent.SetReceiveHandler([&] {
    proxy.MyEvent.GetNewSamples([&](auto sample) {
        work_queue.push(*sample); // non-blocking enqueue
    });
});

Error Handling with ara::core::Result

Adaptive Applications targeting ASIL levels must not use C++ exceptions in safety-relevant code paths. Instead, ara::core provides Result<T, E> — a value-or-error type analogous to std::expected.

C++error_handling.cpp

#include <ara/core/result.h>

ara::core::Result<SensorData, SensorError> ReadSensor() {
    if (!sensor_ready) {
        return ara::core::Result<SensorData, SensorError>::FromError(
            SensorError::kNotReady);
    }
    return SensorData{ReadRaw()};
}

void ProcessLoop() {
    auto result = ReadSensor();
    if (result.HasValue()) {
        Process(result.Value());
    } else {
        ara::log::LogError() << "Sensor error: "
                             << result.Error().Message();
    }
}

💡 ara::core::Abort()

In ASIL context, unrecoverable errors call ara::core::Abort() which terminates the process immediately. PHM detects the exit and triggers the configured RecoveryAction. This replaces Classic's Det_ReportError + defensive programming pattern.

Summary

An Adaptive Application is a self-contained POSIX process with a well-defined lifecycle governed by EM. The ara::core::Initialize / Deinitialize bookends, ReportApplicationState calls, and Result<T,E> error propagation form the non-negotiable skeleton of every compliant application.

🔬 Deep Dive — Core Concepts Expanded

This section builds on the foundational concepts covered above with additional technical depth, edge cases, and configuration nuances that separate competent engineers from experts. When working on production ECU projects, the details covered here are the ones most commonly responsible for integration delays and late-phase defects.

Key principles to reinforce:

Configuration over coding: In AUTOSAR and automotive middleware environments, correctness is largely determined by ARXML configuration, not application code. A correctly implemented algorithm can produce wrong results due to a single misconfigured parameter.
Traceability as a first-class concern: Every configuration decision should be traceable to a requirement, safety goal, or architecture decision. Undocumented configuration choices are a common source of regression defects when ECUs are updated.
Cross-module dependencies: In tightly integrated automotive software stacks, changing one module's configuration often requires corresponding updates in dependent modules. Always perform a dependency impact analysis before submitting configuration changes.

🏭 How This Topic Appears in Production Projects

Project integration phase: The concepts covered in this lesson are most commonly encountered during ECU integration testing — when multiple software components from different teams are combined for the first time. Issues that were invisible in unit tests frequently surface at this stage.
Supplier/OEM interface: This is a topic that frequently appears in technical discussions between Tier-1 ECU suppliers and OEM system integrators. Engineers who can speak fluently about these details earn credibility and are often brought into critical design review meetings.
Automotive tool ecosystem: Vector CANoe/CANalyzer, dSPACE tools, and ETAS INCA are the standard tools used to validate and measure the correct behaviour of the systems described in this lesson. Familiarity with these tools alongside the conceptual knowledge dramatically accelerates debugging in real projects.

⚠️ Common Mistakes and How to Avoid Them

Assuming default configuration is correct: Automotive software tools ship with default configurations that are designed to compile and link, not to meet project-specific requirements. Every configuration parameter needs to be consciously set. 'It compiled' is not the same as 'it is correctly configured'.
Skipping documentation of configuration rationale: In a 3-year ECU project with team turnover, undocumented configuration choices become tribal knowledge that disappears when engineers leave. Document why a parameter is set to a specific value, not just what it is set to.
Testing only the happy path: Automotive ECUs must behave correctly under fault conditions, voltage variations, and communication errors. Always test the error handling paths as rigorously as the nominal operation. Many production escapes originate in untested error branches.
Version mismatches between teams: In a multi-team project, the BSW team, SWC team, and system integration team may use different versions of the same ARXML file. Version management of all ARXML files in a shared repository is mandatory, not optional.

📊 Industry Note

Engineers who master both the theoretical concepts and the practical toolchain skills covered in this course are among the most sought-after professionals in the automotive software industry. The combination of AUTOSAR standards knowledge, safety engineering understanding, and hands-on configuration experience commands premium salaries at OEMs and Tier-1 suppliers globally.