When implementing algorithms, prioritize efficiency in both time and space complexity. Consider these specific optimizations: 1. **Use bitwise operations** for mathematical computations when appropriate. For random number generation in ranges, bitwise operations can be more efficient than arithmetic expressions: ```javascript // Instead of: Math.floor(Math.random() * (65535 - 32768 + 1)) + 32768 // Use: Math.random() * 0x8000 | 0x8000 ``` 2. **Prefer iterative solutions** over recursive ones when the recursion depth could be problematic or when a simple loop would be more efficient and readable. Even if recursion is unlikely to cause issues, iterative approaches often have better performance characteristics and avoid potential stack overflow risks. 3. **Understand memory implications** of data structure operations. When working with TypedArrays, use `subarray()` to create views instead of `slice()` to create copies, unless you specifically need a copy. This avoids unnecessary memory allocation and copying: ```javascript // For views (no copy): array.subarray(start, end) // For copies (when needed): array.slice(start, end) ``` These optimizations become particularly important in performance-critical code paths, large datasets, or resource-constrained environments.