Peephole Optimizer in JavaScript

Peephole optimization is a simple yet effective technique in compiler design that analyzes a small "window" (the peephole) of instructions and attempts to replace it with a more efficient sequence. This challenge asks you to implement a basic peephole optimizer for a simplified JavaScript-like instruction set. It's a great exercise in understanding code transformation and optimization principles.

Problem Description

You are tasked with creating a peephole optimizer that can identify and replace specific instruction patterns within a sequence of JavaScript-like instructions with more efficient equivalents. The instructions are represented as an array of strings. The optimizer should focus on recognizing and replacing a single pattern: ["a", "+", "b", "*", "c"] with ["d", "*", "c"], where a, b, c, and d are variables. This simplification assumes that (a + b) * c can be optimized to d * c where d is the result of a + b.

Key Requirements:

• Input: An array of strings representing a sequence of instructions.
• Pattern Recognition: Identify occurrences of the pattern ["a", "+", "b", "*", "c"].
• Replacement: Replace the identified pattern with ["d", "*", "c"].
• Immutability: The original input array should not be modified. A new array with the optimized instructions should be returned.
• No Match: If the pattern is not found, return a copy of the original input array.

Expected Behavior:

The optimizer should iterate through the instruction sequence, looking for the specified pattern. When a match is found, it should create a new array with the pattern replaced. The optimizer should only replace the first occurrence of the pattern.

Edge Cases to Consider:

• Empty input array.
• Input array with fewer than 5 elements.
• Input array where the elements are not strings. (Assume strings for simplicity, but consider how you might handle other types in a more robust implementation).
• The pattern elements are not valid variable names (e.g., contain spaces or special characters). Assume they are valid for this challenge.

Examples

Example 1:

Input: ["a", "+", "b", "*", "c"]
Output: ["d", "*", "c"]
Explanation: The pattern is found and replaced directly.

Example 2:

Input: ["a", "+", "b", "*", "c", "e", "+", "f"]
Output: ["d", "*", "c", "e", "+", "f"]
Explanation: The pattern is found and replaced, but the rest of the array is preserved.

Example 3:

Input: ["x", "+", "y", "/", "z"]
Output: ["x", "+", "y", "/", "z"]
Explanation: The pattern is not found, so the original array is returned.

Example 4:

Input: []
Output: []
Explanation: Empty input, return empty array.

Example 5:

Input: ["a", "+", "b"]
Output: ["a", "+", "b"]
Explanation: Input array is too short to contain the pattern.

Constraints

• The input array will contain only strings.
• The length of the input array can be between 0 and 100.
• The pattern to be optimized is always ["a", "+", "b", "*", "c"].
• The replacement pattern is always ["d", "*", "c"].
• The optimizer should only replace the first occurrence of the pattern.
• The solution should be reasonably efficient (avoid unnecessary iterations or complex data structures). O(n) time complexity is expected, where n is the length of the input array.

Notes

Consider using array slicing or the slice() method to create the new array with the optimized instructions. Think about how to efficiently check for the pattern without iterating through the entire array multiple times. Focus on clarity and readability in your code. The goal is to demonstrate understanding of the peephole optimization concept, not to create a highly complex or general-purpose optimizer.