Efficient Number Representation: Implementing SMI Optimization in JavaScript

JavaScript's Number type is a double-precision 64-bit floating-point format (IEEE 754). While this provides a wide range of values, it's inefficient for representing small integers (typically -2³¹ to 2³¹ - 1). SMI (Small Integer) optimization aims to represent these small integers as 32-bit integers, saving memory and potentially improving performance. This challenge asks you to implement a function that identifies and optimizes small integers within an array.

Problem Description

You are tasked with creating a JavaScript function called optimizeSMI(arr) that takes an array of numbers as input and returns a new array where small integers (within the range of -2³¹ to 2³¹ - 1) are represented as 32-bit integers, while all other numbers remain as their original 64-bit floating-point representation. The function should not modify the original array. The goal is to demonstrate understanding of JavaScript's Number type and how to conditionally optimize small integers.

Key Requirements:

• The function must accept an array of numbers as input.
• The function must return a new array with the optimized representation.
• Numbers within the SMI range (-2³¹ to 2³¹ - 1) should be represented as 32-bit integers.
• Numbers outside the SMI range should remain as 64-bit floating-point numbers.
• The function should handle various input types, including arrays containing a mix of integers, floating-point numbers, and potentially other data types (though only numbers should be processed).
• The function should be efficient and avoid unnecessary operations.

Expected Behavior:

The function should iterate through the input array and check each element. If an element is a number and falls within the SMI range, it should be converted to a 32-bit integer. Otherwise, it should be kept as is. The new array should contain the modified elements in the same order as the original array.

Edge Cases to Consider:

• Empty input array.
• Array containing only numbers outside the SMI range.
• Array containing only numbers within the SMI range.
• Array containing a mix of numbers within and outside the SMI range.
• Array containing non-numeric values (should be ignored).
• NaN, Infinity, and -Infinity (should remain as is).

Examples

Example 1:

Input: [1, 2, 3, 4, 5]
Output: [1, 2, 3, 4, 5]
Explanation: All numbers are within the SMI range and are already represented as 32-bit integers.

Example 2:

Input: [1.5, 2.7, 3.14, 4.0, 5.2]
Output: [1.5, 2.7, 3.14, 4.0, 5.2]
Explanation: All numbers are floating-point and outside the SMI range, so they remain unchanged.

Example 3:

Input: [-2147483648, 0, 2147483647, 1000000000]
Output: [-2147483648, 0, 2147483647, 1000000000]
Explanation: The first three numbers are within the SMI range and are converted to 32-bit integers. The last number is outside the SMI range and remains as a 64-bit floating-point number.

Example 4:

Input: [1, "hello", 2, null, 3, NaN, Infinity]
Output: [1, "hello", 2, null, 3, NaN, Infinity]
Explanation: Only numbers are processed. Strings, null, NaN, and Infinity are left untouched.

Constraints

• The SMI range is defined as -2³¹ to 2³¹ - 1 (inclusive), which is -2147483648 to 2147483647.
• The input array arr can contain any number of elements.
• The function must return a new array; the original array must not be modified.
• The function should have a time complexity of O(n), where n is the length of the input array.
• The function should handle potential type errors gracefully (e.g., non-numeric values in the array).

Notes

• You can use the Number.isInteger() method to check if a value is an integer.
• Consider using the bitwise operators (e.g., | 0) to explicitly convert a number to a 32-bit integer. However, this is not strictly required.
• Focus on clarity and efficiency in your implementation. Avoid unnecessary complexity.
• Remember that JavaScript's Number type can represent integers and floating-point numbers. The goal is to conditionally optimize the representation of small integers.