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Home Backend Development C++ How Do Dynamic Variables Impact C# Performance?

How Do Dynamic Variables Impact C# Performance?

Jan 19, 2025 am 07:31 AM

How Do Dynamic Variables Impact C# Performance?

C# Dynamic Variables: Performance Implications

Dynamic Variable Behavior and Performance

Using dynamic variables in C# introduces specific performance challenges. During compilation, the compiler must perform extra work to determine the variable's type and appropriate actions. This contrasts with statically-typed variables where type information is known at compile time.

The Dynamic Invocation Process

Each dynamic expression generates a dynamic call site object. While runtime caching of these call sites optimizes repeated invocations, the initial overhead remains.

Type Determination and Optimization

The Dynamic Language Runtime (DLR) identifies the type of dynamic objects. For specialized types (like COM objects or IronPython objects), optimizations are possible. However, with standard C# objects, the DLR necessitates a re-compilation step.

Re-compilation Overhead

This re-compilation uses a lightweight C# compiler to generate an Expression Tree representing the dynamic call. This tree is then compiled into an executable delegate and cached. The significant performance cost arises from this re-compilation process.

Caching Effects on Performance

The impact of dynamic variables depends heavily on caching. Repeated use of the same dynamic expression benefits from the cached delegate, minimizing the overhead. Conversely, multiple dynamic operations within a single expression create multiple call sites and caches, increasing the performance penalty.

Illustrative Example: A Timed Loop

The accompanying code example (not shown here, but referenced in the original text) demonstrates this performance difference. A Sum() method (baseline) iterates without dynamic operations. SumInt() uses a class with integer properties. DynamicSum() introduces a dynamic property, showcasing a substantial performance drop (approximately two orders of magnitude). This clearly illustrates the re-compilation overhead for dynamic operations within loops.

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