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We first cover what happens when structured data gets marshalled by the CLR in the case of nontrivial argument types. Here we show the SumC function responsible for adding two complex numbers defined by the Complex C data structure: typedef struct _Complex { double re; double im; } Complex; Complex CINTEROPDLL_API SumC(Complex c1, Complex c2) { Complex ret; ret.re = c1.re + c2.re; ret.im = c1.im + c2.im; return ret; } To invoke this function from F#, you must define a data structure in F# corresponding to the Complex C structure. If the memory layout of an instance of the F# structure is the same as that of the corresponding C structure, then values can be shared between the two languages. But how can you control the memory layout of a managed data structure Fortunately, the PInvoke specification helps with custom attributes that allow specifying memory layout of data structures. The StructLayout custom attribute consents to indicate the strategy adopted by the runtime to lay out fields of the data structure. By default, the runtime adopts its own strategy in the attempt to optimize the size of the structure, keeping fields aligned to the machine world in order to ensure fast access to the fields of the structure. The C standard ensures that fields are laid out in memory sequentially in the order they appear in the structure definition; other languages may use different strategies. Using an appropriate argument, you can indicate that a C-like sequential layout strategy should be adopted. Moreover, it is also possible to provide an explicit layout for the structure indicating the offset in memory for each field of the structure. For this example, here we use the sequential layout for the Complex value type:

module CInterop = [<Struct; StructLayout(LayoutKind.Sequential)>] type Complex = val mutable re:double val mutable im:double new(r,i) = { re = r; im = i; } [<DllImport("CInteropDLL")>] extern Complex SumC(Complex c1, Complex c2) let c1 = CInterop.Complex(1.0, 0.0) let c2 = CInterop.Complex(0.0, 1.0) let mutable c3 = CInterop.SumC(c1, c2) printf "c3 = SumC(c1, c2) = %f + %fi\n" c3.re c3.im; The SumC prototype refers to the F# Complex value type, but since the layout in memory of the structure is the same as the corresponding C structure, the runtime passes the bits that are consistent with those expected by the C code.

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A critical aspect in dealing with PInvoke is to ensure that values are marshalled correctly between managed and native code, and vice versa. The memory layout of a structure does not depend on the order of the fields only. Compilers often introduce padding to align fields to memory addresses so that access to fields requires fewer memory operations since CPUs load data into registers with the same strategy. Padding may speed up access to the data structure, though it introduces inefficiencies in memory usage since there may be gaps in the structures leading to allocated but unused memory. Consider, for instance, the following C structure: struct Foo { int i; char c; short s; }; Depending on compiler decision, it may occupy from 8 up to 12 bytes on a 32-bit architecture. The most compact version of the structure uses the first four bytes for i, a single byte for c, and two more bytes for s. If the compiler aligns fields to addresses that are multiples of four, then the integer i occupies the first slot, four more bytes are allocated for c (though only one is used), and the same happens for s. Padding is a common practice in C programs, and since it may affect performance and memory usage, compilers provide directives to instruct the compiler about padding. It is possible to have data structures with different padding strategies running within the same program. The first step to be faced when using PInvoke to access native code is to find the definition of data structures, including information about padding. Then it is possible to annotate F# structures to have the same layout as the native ones, and the CLR can automate the marshalling of data. It is important to note that it is

Table 1-5. Dates Data Table for Normalized Weather Data from Table 1-1

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