When implementing algorithms, break down complex methods that handle multiple concerns into smaller, more focused methods. This improves maintainability, makes edge cases easier to handle, and allows for more flexible reuse of algorithm components.
When implementing algorithms, break down complex methods that handle multiple concerns into smaller, more focused methods. This improves maintainability, makes edge cases easier to handle, and allows for more flexible reuse of algorithm components.
For example, instead of having a single method that handles multiple responsibilities:
static gboolean
get_common_simd_info (MonoClass *vector_klass, MonoMethodSignature *csignature,
MonoTypeEnum *atype, int *vector_size, int *arg_size, int *scalar_arg)
{
// Complex logic handling multiple concerns:
// 1. Getting size information
// 2. Determining element type
// 3. Finding scalar arguments
// ...
}
Break it into focused methods with clear responsibilities:
static gboolean
get_common_simd_info (MonoClass *klass, MonoTypeEnum *atype,
int *klass_size, int *arg_size)
{
// Focus only on getting class size and element type information
}
static int
get_common_simd_scalar_arg (MonoMethodSignature *csignature)
{
// Focus only on finding scalar arguments
}
This approach makes algorithms more adaptable to changing requirements, such as supporting additional intrinsics or handling different types of operations. It also simplifies testing and debugging by isolating specific functionality into well-defined methods with clearer purposes.
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