When processing large arrays or data structures, implement chunked processing to avoid stack size limitations and optimize performance. Break operations into manageable chunks rather than processing everything at once. **Key practices:** 1. Use appropriate chunk sizes (typically 100KB or less) when dealing with large binary data or strings 2. Choose the right collection operation for your use case: - Use `reduce()` when accumulating or combining values across collections - Use `map()` when transforming elements without combining them - Consider recursion for nested structures with appropriate base cases **Example:** ```typescript // Process large binary data in chunks to avoid stack overflow async asString(): Promise { const data = this.data ?? new Blob([]); const dataBuffer = await data.arrayBuffer(); const dataArray = new Uint8Array(dataBuffer); // Need to handle the array in smaller chunks to deal with stack size limits let ret = ""; const chunkSize = 102400; for (let i = 0; i < dataArray.length; i += chunkSize) { const chunk = dataArray.subarray(i, i + chunkSize); ret += String.fromCharCode(...chunk); } return ret; } ``` Implementing chunked processing improves application stability by preventing stack overflows and can improve performance by managing memory more efficiently. This pattern is especially important when handling user-generated content, large API responses, or binary data operations.