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Minimize memory allocations by avoiding intermediate objects, sharing underlying buffers, and eliminating unnecessary array operations. This is particularly important in hot code paths and when processing large datasets.

Key strategies:

• Share underlying buffers instead of copying data: Buffer.from(arg.buffer, arg.byteOffset, arg.byteLength) instead of Buffer.from(arg)
• Avoid creating intermediate arrays when chaining operations: inline map operations rather than creating separate arrays
• Construct objects directly when possible: new Uint8Array(value) instead of new Uint8Array(Buffer.from(value).buffer)
• Move expensive computations out of frequently called functions to constructors or initialization phases
• Only store data structures when the intermediate results are actually needed

Example of optimization:

// Before: Creates unnecessary intermediate array
const results: Value[] = []
for (const arg of node.args) {
  results.push(await this.interpretNode(arg, queryable, scope, generators))
}
return results[results.length - 1]

// After: Only compute what's needed
let lastResult: Value
for (const arg of node.args) {
  lastResult = await this.interpretNode(arg, queryable, scope, generators)
}
return lastResult

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