Why Is ImmutableArray Builder ItemRef Readonly in C#?

What Led Us to Investigate ImmutableArray Builder ItemRef in a FinTech System?

While working on a high-throughput, real-time risk calculation engine for a FinTech SaaS platform, performance and memory allocation were our top priorities. The system processes millions of financial instrument updates per second. To minimize garbage collection (GC) pressure, we extensively utilized value types (structs) and immutable collections to ensure thread-safe read operations across multiple processing nodes.

During the optimization phase, we sought to eliminate struct copying overhead while building our data sets. We utilized ImmutableArray<T>.Builder to construct our arrays efficiently. Our strategy was to allocate the builder, populate it with default structs and then update those structs in-place by reference before freezing the collection. We attempted to use the ItemRef(Int32) method to get a reference to the struct in the backing array, only to realize that it returns a ref readonly instead of a mutable ref.

This strict readonly constraint initially broke our zero-allocation, in-place mutation strategy. This challenge inspired this deep dive into the underlying memory safety mechanisms of .NET, so other teams can avoid the same architectural bottlenecks when they hire software developer teams to build high-performance applications.

How Did the ItemRef Readonly Constraint Impact Our Risk Calculation Architecture?

In our architecture, the risk engine ingests real-time tick data, evaluates market volatility and produces a frozen snapshot of the market state. These snapshots are distributed to downstream services. The data structure representing a market position was a relatively large struct.

When you have a large struct, copying it over and over (pass-by-value) becomes a CPU bottleneck. To avoid this, C# provides ref returns. Our goal was to do something like this:

// Hypothetical code illustrating our intent (which does not compile)
var builder = ImmutableArray.CreateBuilder<RiskPosition>(1000);
// ... populate builder ...
// Attempting to mutate in-place to avoid struct copy
ref RiskPosition position = ref builder.ItemRef(index); 
position.Exposure = newExposureValue; // Fails! ItemRef is ref readonly

Because the method returns a ref readonly, the compiler strictly prohibits modifying the struct’s fields. As a result, we were forced to read the struct, modify the copy and assign it back via the indexer, which meant moving memory around twice.

Why Does ImmutableArray Builder Return Ref Readonly Instead of a Mutable Ref?

Our initial assumption was that this restriction might be related to array resizing. If the builder resizes its internal array, any captured references would point to the old array, causing bugs. However, as any seasoned .NET engineer knows, this doesn’t explain the readonly part. Array reallocation would invalidate a ref readonly just as easily as a mutable ref.

The real reason lies in the core optimization of ImmutableArray<T> and its builder. To avoid unnecessary memory allocations, the builder has a method called MoveToImmutable() (and often ToImmutable() under the right capacity conditions). These methods do not create a new array; they extract the underlying, populated T[] from the builder and wrap it directly in the ImmutableArray<T> struct.

If ItemRef returned a mutable ref, it would create a massive security and data-integrity loophole in the .NET type system. Consider this scenario if mutable refs were allowed:

var builder = ImmutableArray.CreateBuilder<RiskPosition>(1);
builder.Add(new RiskPosition { Exposure = 100 });
// 1. Capture a mutable reference to the element
ref RiskPosition capturedRef = ref builder.ItemRef(0); 
// 2. Transfer ownership to the immutable array
ImmutableArray<RiskPosition> frozenArray = builder.MoveToImmutable();
// 3. Mutate the supposedly immutable array using the captured reference!
capturedRef.Exposure = 999; 

By returning ref readonly, the .NET runtime ensures that you cannot capture a reference that allows mutation after the builder’s backing array has been promoted to a deeply immutable state. This is a brilliant piece of API design that protects the integrity of ImmutableArray<T> while still providing the performance benefits of by-reference reads (avoiding struct copies when reading data out of the builder).

How Did We Approach the Solution for Zero-Allocation Struct Updates?

Understanding the runtime constraints, we had to re-evaluate our approach to building these collections. We needed the thread-safety of immutable arrays for the final state, but we required high-performance mutable state during the construction phase. We considered these solutions as well:

Did We Consider Using Standard List Collections?

Our first fallback was using List<T> and relying on CollectionsMarshal.AsSpan(list). This allows for excellent in-place mutation of structs via Spans. However, converting a List<T> to an ImmutableArray<T> at the end of the pipeline requires allocating a completely new array and copying all elements, which defeated our zero-allocation requirement.

What About Using ArrayPool and Memory Constructs?

We looked into renting arrays from ArrayPool<T>.Shared. We could rent a large array, mutate the structs in-place using array indexing or Spans and then wrap the final subset in a custom readonly struct. This is highly efficient and common when you hire dotnet developers for enterprise modernization projects. However, the downstream consumer services strictly required the ImmutableArray<T> type to integrate with legacy APIs.

Could We Restructure the Data Pipeline?

We also debated shifting to a class-based model, but reference types introduced unacceptable GC pauses during peak trading hours. We knew we had to keep value types and find a way to populate the immutable array directly without post-insertion mutation.

What Was the Final Implementation for High-Performance Struct Mutation?

To satisfy both the strict immutability guarantees of .NET and our performance thresholds, we decoupled the calculation phase from the array construction phase.

Instead of adding empty or partial structs to the builder and mutating them later, we utilized Span<T> backed by stack-allocated memory or small pooled arrays for the transient calculation phase. Once a RiskPosition struct was fully calculated and mathematically finalized, it was passed by value (or by in parameter to avoid copy during the method call) into the ImmutableArray<T>.Builder.

Here is a sanitized representation of our approach:

// 1. Rent a temporary array for the mutable calculation phase
var tempBuffer = ArrayPool<RiskPosition>.Shared.Rent(requiredCapacity);
Span<RiskPosition> calculationSpan = tempBuffer.AsSpan(0, requiredCapacity);
// 2. Perform in-place mutations safely on the Span
for (int i = 0; i < calculationSpan.Length; i++)
{
    // fully construct and mutate the struct in the temporary buffer
    calculationSpan[i].Exposure = CalculateExposure(tickData[i]);
    calculationSpan[i].Volatility = CalculateVolatility(tickData[i]);
}
// 3. Construct the builder with exact capacity to ensure MoveToImmutable optimization
var builder = ImmutableArray.CreateBuilder<RiskPosition>(calculationSpan.Length);
// 4. Add finalized structs to the builder
for (int i = 0; i < calculationSpan.Length; i++)
{
    builder.Add(calculationSpan[i]);
}
// 5. Freeze without allocation (since capacity matches count)
ImmutableArray<RiskPosition> frozenState = builder.MoveToImmutable();
// 6. Return buffer to pool
ArrayPool<RiskPosition>.Shared.Return(tempBuffer);

This implementation preserved our zero-allocation goals for the final data structure, satisfied the runtime’s safety requirements and provided the downstream consumers with the exact immutable types they expected. The minor overhead of copying the finalized struct once from the rented array into the builder was negligible compared to the GC cost of reference types.

What Can Engineering Teams Learn About .NET Memory and Immutability Guarantees?

Architectural challenges like this often separate basic applications from highly tuned enterprise systems. Here are the core insights engineering teams should take away:

• Trust the API Design: When a low-level .NET API restricts an operation (like returning ref readonly), there is almost always a profound memory-safety or concurrency reason behind it. In this case, preventing mutable references from outliving the mutability phase of the collection.
• Understand MoveToImmutable: Using MoveToImmutable() is a powerful zero-allocation trick, but it requires the builder’s count to exactly match its capacity. Otherwise, it is forced to allocate a new, correctly sized array.
• Decouple Calculation from Storage: Don’t use storage containers (like Builders or Lists) as scratchpads for complex struct mutations. Do the heavy lifting in transient buffers (Spans, ArrayPools) and use the collections strictly for storage and routing.
• Structs and In-Place Mutation: Value types are fantastic for reducing GC pressure, but they require careful architectural planning. Avoid large structs if they must be repeatedly modified across method boundaries without access to Spans or mutable refs.
• Cross-Disciplinary Learnings: Memory safety isn’t just a .NET concern. Whether you hire python developers for scalable data systems using NumPy or rust developers building memory-safe engines, the principles of immutability and reference tracking remain universally critical.

How Can We Wrap Up This Deep Dive into C# Immutability?

The discovery of the ref readonly constraint on ImmutableArray<T>.Builder.ItemRef was a vital reminder that performance optimization cannot circumvent language safety guarantees. By understanding how the runtime protects immutable structures from malicious or accidental modification via captured references, we were able to redesign our data pipeline using ArrayPools and Spans. This resulted in a thread-safe, high-performance risk engine that seamlessly handles massive scale without taxing the Garbage Collector.

If your enterprise is dealing with complex performance bottlenecks, legacy system modernization or needs to scale its engineering capabilities with a team that deeply understands architecture, contact us. We help tech leaders augment their projects with pre-vetted, high-caliber engineering talent.

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