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Use one Simulink model for shared algorithm logic, then build separate target artifacts for Linux and QNX. A coder.ExternalDependency subclass can wrap external C or C++ calls and provide the build information generated code needs. It does not make a Linux library compatible with QNX, and the MathWorks documentation reviewed for this article does not establish a supported QNX support-package or compiler pairing. Verify the QNX SDP, compiler, architecture, and sysroot for your specific MATLAB and Simulink release before committing to the deployment path.
What coder.ExternalDependency does in a Simulink project
coder.ExternalDependency is an abstract base class for connecting MATLAB code intended for code generation to external code. A subclass can encapsulate C or C++ source, object files, and libraries behind a MATLAB-facing interface. The model and wrapper can therefore share an interface while the build configuration supplies the files and options appropriate to each target.
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The wrapper’s static methods describe the dependency and its build context. The documented subclass contract includes getDescriptiveName, isSupportedContext, and updateBuildInfo. Methods that invoke an external function are compiled; generated-code paths can call the external function with coder.ceval.
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Check the build context explicitly
Use isSupportedContext(buildContext) to decide whether the dependency supports the current build. If a target is not supported, return a clear error rather than assuming that a library, header, or compiler is available. The check is a guardrail, not proof that a target’s entire toolchain or ABI is compatible.
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Separate interactive MATLAB behavior from generated code
If the same wrapper is used during MATLAB execution and code generation, branch where appropriate with coder.target('MATLAB'). The MATLAB branch can provide an interactive implementation; the generated-code branch can use coder.ceval to call the external function. Keep the two branches’ behavior aligned, and test them separately: successful interactive execution does not establish that the generated call links or behaves correctly on a target.
Put target-specific build details in updateBuildInfo
Configure the generated build with the target’s include paths, source files, library names and extensions, and linker options. Use build-context platform information when selecting platform-specific details; MathWorks documents getStdLibInfo as one source of information such as library extensions. Do not hard-code a Linux library name or extension and assume it applies to QNX.
Keep the model shared and the build outputs target-specific
Generated binaries are functional for the host operating system and hardware by default. To build for another platform, the deployment path needs a matching hardware support package and target configuration, a registered custom toolchain, or a source-generation workflow followed by a build in an already configured target environment. Which route is viable depends on the MATLAB/Simulink release and the target toolchain.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsFor Linux, MathWorks documents .a and .so as static and dynamic library extensions. Those extensions do not establish QNX compatibility. For each target, the library and generated code must agree on ABI, processor architecture, compiler, sysroot, dependency versions, and linker and runtime behavior. Reusing the model or MATLAB-facing wrapper does not make binaries interchangeable.
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Implementation sequence for a cross-platform dependency
- Define the external boundary. Identify the C or C++ functions the model needs, their headers and libraries, the data types and calling conventions, and which parts of the algorithm should remain common model logic.
- Create the MATLAB-facing wrapper. Subclass
coder.ExternalDependencyand implement the documented methods:getDescriptiveName,isSupportedContext, andupdateBuildInfo. Keep the public MATLAB interface stable where the underlying target APIs permit it. - Choose the execution path. Provide MATLAB behavior for interactive use where needed, and use generated-code calls such as
coder.cevalfor the external functions in the code-generation path. - Make context checks and build settings target-aware. Reject unsupported build contexts clearly. In
updateBuildInfo, provide the paths, sources, libraries, and options needed for the selected target rather than applying one platform’s configuration to every build. - Generate and inspect code for each target configuration. Review generated build information and makefiles to see which headers, sources, libraries, runtime support, and shared utilities are required. Treat a successful host build as a host result, not as a Linux or QNX target result.
- Build and verify each target separately. Link the generated component with the matching target dependencies and toolchain. Run generated-code verification and test the resulting application in the intended target environment before deployment.
When an external-dependency wrapper is a better fit than an S-function
The choice depends on the interface you need, not on a blanket rule that one mechanism is always more portable. Use coder.ExternalDependency when the dependency is naturally an external C or C++ call exposed through a MATLAB/Coder-facing wrapper. Retain an S-function when its Simulink block behavior, simulation integration, scheduling semantics, or established build mechanism is the right fit.
| Consideration | coder.ExternalDependency |
S-function |
|---|---|---|
| Natural interface | A MATLAB/Coder-facing wrapper around external C or C++ functions. | A Simulink block implemented against the Simulink C MEX S-function API. |
| Build configuration | The subclass supplies target-aware dependency information through updateBuildInfo. |
Block-based mechanisms can use header paths, makefile rules, SFunctionModules, and rtwmakecfg.m. |
| Code-generation handoff | Package the generated component and its required target dependencies. | Downstream code generation requires more than the MEX binary: generated C/C++ source, a header, the platform-dependent MEX file, and the _sfcn_rtw folder are among the required artifacts. |
| Host and target coordination | Build settings and external libraries still need to match the target. | The generated S-function’s Hardware Implementation parameter values reflect the host where it was built and must match the receiving model for code generation. |
An S-function is not inherently unsuitable for cross-platform delivery: MathWorks documents ways to package block-based dependencies and configure their build requirements. The practical question is whether the project needs a Simulink block abstraction or a MATLAB-facing wrapper for external calls, and which mechanism the receiving team can reliably build and maintain.
Choose the dependency mechanism that matches where the code enters
- Model- or system-target-level dependency: use Configuration Parameters > Code Generation > Custom Code to provide additional source files, libraries, and include folders. TLC hooks are another option.
- Block-based dependency: use the S-function or blockset build mechanisms appropriate to the block, including header paths, makefile rules,
SFunctionModules, orrtwmakecfg.m. - External C/C++ call behind a wrapper: use
coder.ExternalDependencyand implementupdateBuildInfofor the generated build.
Inspect the generated build information and makefiles regardless of which mechanism you use. They expose the dependency and compiler/linker requirements that must be satisfied by the target build.
What must be verified specifically for QNX
The MathWorks deployment guidance reviewed here describes Linux target workflows and general custom-toolchain or manual-deployment routes, but does not establish a current QNX-specific support package or a supported pairing of QNX SDP release, compiler, processor architecture, and sysroot. Treat QNX configuration as a project prerequisite to verify for the intended MATLAB/Simulink release; do not infer official support from the general external-dependency API.
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- Confirm the exact QNX SDP release, compiler, target architecture, and sysroot used by the project.
- Determine whether the intended MATLAB/Simulink release provides a matching target support package or whether the project must register a custom toolchain or generate source for a separate target build.
- Build or obtain QNX-compatible versions of every external dependency; Linux binaries are not substitutes.
- Check that headers, ABI, calling conventions, compiler options, link settings, and runtime dependencies match the target environment.
- Run generated-code verification and target-environment tests using the actual deployment configuration.
Build a component for integration with an external application
If an external program supplies main and schedules the generated component, build the component library or source for the target and integrate it with that program and the target code. Keep component generation, external interface review, target linking, and on-target verification as separate checkpoints: each can fail for a different reason.
For handoff or relocation, package only the required generated artifacts. MathWorks recommends packNGo rather than copying an entire code-generation folder indiscriminately. Include the target dependency files and build details needed by the receiving project, and make clear which target configuration produced them.
Release-sensitive details
MathWorks’ documentation pages consulted for this topic include R2026b-labelled material and live documentation accessed on October 7, 2026. Support-package availability, toolchain compatibility, and configuration details can change between releases. Confirm them against the exact MATLAB/Simulink release and target toolchain used for the deployment.
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