Code generation for C/C++ in MATLAB - Step-by-Step Execution

Concept Flow - Code generation for C/C++

Write MATLAB code

↓

Use codegen command

↓

MATLAB Coder analyzes code

↓

Generate C/C++ code files

↓

Compile and integrate C/C++ code

Start with MATLAB code, use the codegen tool to convert it step-by-step into C/C++ code files ready for compilation.

Execution Sample

MATLAB

function y = squareThis(x)
  y = x.^2;
end

% Run: codegen squareThis -args {5}

This MATLAB function squares input x, then codegen generates C code for it assuming input 5.

Execution Table

Step	Action	Input/Code	Result/Output
1	Write MATLAB function	function y = squareThis(x) y = x.^2; end	Function ready for codegen
2	Run codegen command	codegen squareThis -args {5}	MATLAB Coder starts analysis
3	Analyze code	Check input types and operations	Confirmed input is scalar double
4	Generate C code	Translate MATLAB to C	Created squareThis.c and squareThis.h files
5	Compile C code	Use generated files	Compiled executable or library ready
6	Exit	Code generation complete	C/C++ code ready for integration

💡 Code generation stops after creating and compiling C/C++ files.

Variable Tracker

Variable	Start	After codegen	After compile	Final
x	Not set	Input type double scalar	Used in generated code	Input parameter in C function
y	Not set	Output type double scalar	Computed as x*x in C	Output from C function

Key Moments - 3 Insights

Why do we specify input types with -args in codegen?

Because MATLAB is dynamic, codegen needs fixed input types to generate correct C code, as shown in step 2 and 3 of the execution_table.

What happens if MATLAB code uses unsupported functions?

Codegen will fail or warn during analysis (step 3), because only a subset of MATLAB functions can be converted to C/C++.

Is the generated C code human-readable?

Yes, generated C code files (step 4) are readable but optimized for performance, so may look different from handwritten code.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does MATLAB Coder confirm input types?

A Step 2

B Step 3

C Step 4

D Step 5

💡 Hint

Check the 'Analyze code' action in execution_table row 3.

According to variable_tracker, what is the final role of variable y?

A Input parameter in C function

B Not used in generated code

C Output from C function

D Temporary variable in MATLAB

💡 Hint

Look at the 'Final' column for y in variable_tracker.

If the MATLAB function used unsupported features, at which execution_table step would codegen likely stop?

A Step 3

B Step 1

C Step 4

D Step 5

💡 Hint

Refer to the 'Analyze code' step where MATLAB Coder checks code compatibility.

Concept Snapshot

Code generation for C/C++ in MATLAB:
- Write MATLAB function
- Use codegen with input types (-args)
- MATLAB Coder analyzes code
- Generates C/C++ source files
- Compile and integrate generated code
- Only supported MATLAB features convert successfully

Full Transcript

This visual execution shows how MATLAB code is converted to C/C++ code using the codegen tool. First, you write a MATLAB function. Then you run codegen with specified input types so MATLAB Coder knows what to expect. It analyzes the code to confirm types and compatibility. Next, it generates C and header files representing the MATLAB function. Finally, you compile these files to create executable or library code. Variables like inputs and outputs are tracked through this process. Key points include specifying input types and understanding that only supported MATLAB functions can be converted. The generated C code is readable but optimized. This step-by-step trace helps beginners see how MATLAB code turns into C/C++ code.

Practice

1. What is the primary purpose of using codegen in MATLAB for C/C++?

easy

A. To visualize MATLAB data in 3D plots

B. To debug MATLAB scripts line by line

C. To create graphical user interfaces in MATLAB

D. To convert MATLAB code into C/C++ code for faster execution or integration

Solution

1. Step 1: Understand the role of codegen

   codegen is used to generate C/C++ code from MATLAB functions.

2. Step 2: Identify the main benefit

   This conversion helps in faster execution and easier integration with other C/C++ projects.

3. Final Answer:

   To convert MATLAB code into C/C++ code for faster execution or integration -> Option D

4. Quick Check:

   Code generation = convert MATLAB to C/C++ [OK]

Hint: Remember: codegen means generate code in C/C++ [OK]

Common Mistakes:

• Confusing codegen with debugging tools
• Thinking codegen creates plots
• Assuming codegen builds GUIs

2. Which of the following is the correct syntax to generate C code for a MATLAB function myFunc with input type double scalar?

easy

A. codegen myFunc -args {double(0)}

B. codegen myFunc -args {single(1)}

C. codegen myFunc -args {int32(1)}

D. codegen myFunc -args {1+0i}

Solution

1. Step 1: Understand input argument specification

   For codegen, input types are specified using MATLAB data types like double(0) for a scalar double.

2. Step 2: Check each option

   codegen myFunc -args {double(0)} uses double(0) which correctly specifies a double scalar input. Others either use incorrect syntax or values.

3. Final Answer:

   codegen myFunc -args {double(0)} -> Option A

4. Quick Check:

   Input type double scalar = double(0) [OK]

Hint: Use double(0) to specify a double scalar input [OK]

Common Mistakes:

• Using numeric literals directly without type
• Using curly braces incorrectly
• Confusing input value with input type

3. Given the MATLAB function

function y = squarePlusOne(x)
y = x.^2 + 1;
end

What will be the output C code function signature generated by codegen squarePlusOne -args {zeros(3,1)}?

medium

A. void squarePlusOne(const double x[3], double y[3])

B. double squarePlusOne(double x)

C. void squarePlusOne(double x, double *y)

D. double squarePlusOne(const double x[3])

Solution

1. Step 1: Analyze input argument

   The input is a 3x1 double vector, so the generated C function will take an array of 3 doubles as input.

2. Step 2: Determine output type

   The output is also a 3x1 vector, so the output is an array passed by reference.

3. Step 3: Match function signature

   void squarePlusOne(const double x[3], double y[3]) matches the expected signature: void function with input array and output array parameters.

4. Final Answer:

   void squarePlusOne(const double x[3], double y[3]) -> Option A

5. Quick Check:

   Array input/output = void func(const double x[3], double y[3]) [OK]

Hint: Array inputs generate functions with array parameters [OK]

Common Mistakes:

• Assuming scalar input/output signatures
• Missing const qualifier for input arrays
• Returning output instead of using output parameter

4. You try to generate C code for this MATLAB function:

function y = addVectors(a, b)
y = a + b;
end

using codegen addVectors -args {zeros(3,1), zeros(4,1)}. What is the main issue?

medium

A. Function syntax is incorrect for code generation

B. Input vectors have different sizes causing a code generation error

C. You must specify input types as integers, not doubles

D. codegen cannot handle vector inputs

Solution

1. Step 1: Check input argument sizes

   The inputs are vectors of sizes 3x1 and 4x1, which cannot be added element-wise due to size mismatch.

2. Step 2: Understand codegen requirements

   Code generation requires consistent input sizes for operations like addition.

3. Final Answer:

   Input vectors have different sizes causing a code generation error -> Option B

4. Quick Check:

   Size mismatch in inputs = error [OK]

Hint: Ensure input sizes match for element-wise operations [OK]

Common Mistakes:

• Ignoring input size mismatch
• Assuming codegen auto-resizes inputs
• Confusing data type with size issues

5. You want to generate C++ code from this MATLAB function that computes the sum of positive elements only:

function s = sumPositive(v)
s = sum(v(v > 0));
end

Which input argument specification is best for codegen to handle variable-length vectors?

hard

A. codegen sumPositive -args {double(0)}

B. codegen sumPositive -args {zeros(10,1)}

C. codegen sumPositive -args {coder.typeof(0,[Inf,1],[1,0])}

D. codegen sumPositive -args {coder.typeof(0,[10,1],[0,0])}

Solution

1. Step 1: Understand variable-size input specification

   To handle variable-length vectors, coder.typeof with [Inf,1] size and [1,0] variable-size flags is used.

2. Step 2: Evaluate options

   codegen sumPositive -args {coder.typeof(0,[Inf,1],[1,0])} correctly specifies a variable-length column vector of doubles. Others specify fixed sizes or scalars.

3. Final Answer:

   codegen sumPositive -args {coder.typeof(0,[Inf,1],[1,0])} -> Option C

4. Quick Check:

   Variable-size vector = coder.typeof with Inf size [OK]

Hint: Use coder.typeof with Inf size for variable-length inputs [OK]

Common Mistakes:

• Using fixed-size arrays for variable-length inputs
• Not setting variable-size flags correctly
• Confusing scalar input with vector input