Show an optimized version of the code with error handling.

When optimizing code, the goal is to reduce time and space complexity while keeping the logic clear. A common pattern is to wrap potentially failing operations in a try/catch block so that errors are caught and handled gracefully. For example, if you have a function that processes an array of items, you can use a for‑of loop with async/await and a try/catch inside the loop:

async function processItems(items) {
  const results = [];
  for (const item of items) {
    try {
      const result = await processItem(item); // could throw
      results.push(result);
    } catch (err) {
      console.error(`Failed to process ${item}:`, err.message);
      // optionally push a fallback value or skip
    }
  }
  return results;
}

This approach has O(n) time complexity, where n is the number of items, and O(1) additional space per iteration. By handling errors locally, the loop continues, preventing a single failure from aborting the entire batch. If the function is CPU‑bound, consider using a memoization map to avoid recomputing results for duplicate inputs, which can reduce complexity from O(n·m) to O(n) where m is the cost of processing a single item. Always benchmark after changes to confirm that the optimization actually improves performance in your specific context.