Benchmark: AlgoBenchmark - MeasureThat.net

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

let arr = Array.from({ length: 1_000_000 }, () => 'XmlHttpRequest');

Tests:

Concat
function camelToSnake(text) { // your code here let result = ''; for (let i = 0; i < text.length; i++) { const char = text[i]; if (char.toUpperCase() === char) { if (i !== 0) { result += '_'; } result += char.toLowerCase(); } else { result += char; } } return result; } return arr.map(camelToSnake);
Join Array
function camelToSnake(text) { if (text.length === 0) { return text; } let result = [text[0].toLowerCase()]; for (let i = 1; i < text.length; i++) { if (text[i] === text[i].toLowerCase()) { result.push(text[i]); continue; } result.push(`_${text[i].toLowerCase()}`); } return result.join(''); } return arr.map(camelToSnake);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Concat
Join Array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36

Browser/OS: Chrome 136 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Concat	2.5 Ops/sec
Join Array	3.5 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

The benchmark you provided tests two different implementations of a function that converts camel case strings into snake case. This transformation involves changing strings like "camelCaseExample" to "camel_case_example".

### Test Cases Overview

1. **Test Name: "Concat"**
   - **Functionality:** This implementation builds the result string by contiguous character concatenations.
   - **Implementation Details:**
     - Initializes an empty string, carries out a loop through each character in the input string.
     - If a character is uppercase (indicating the start of a new word), it adds an underscore ('_') before appending the lowercase version of that character.
     - Other characters are directly appended to the result.
   - **Pros:**
     - Straightforward and simple to understand.
   - **Cons:**
     - String concatenation in JavaScript (using `+=`) can be computationally expensive, especially in a loop, due to immutability of strings. Each concatenation creates a new string, thus incurring performance costs.

2. **Test Name: "Join Array"**
   - **Functionality:** This implementation uses an array to collect characters and then joins them at the end.
   - **Implementation Details:**
     - Initializes an array with the first character converted to lowercase.
     - Loops through the input string and pushes either the lowercase character or an underscore followed by the lowercase character into the array.
     - Joins the array into a final string using `Array.prototype.join('')`.
   - **Pros:**
     - More efficient than string concatenation in the first implementation since it only builds one string after all characters are collected.
   - **Cons:**
     - Slightly more complex in terms of code and logic due to the use of an intermediate array.

### Performance Results
The benchmark results indicate that the "Join Array" implementation was executed approximately 3.47 times per second, while the "Concat" version achieved about 2.53 executions per second. This clearly shows that the array-based implementation is more efficient in this context.

### Other Considerations
- **Browser Environment:** Both tests were run in Chrome 136 on a Mac OS X environment, which means results can vary based on the engine and platform.
- **Libraries and Techniques:** The benchmark did not utilize any specific external libraries or advanced JavaScript features beyond standard practices; both implementations utilize inherent JavaScript capabilities (like string manipulation and array operations).

### Alternatives
1. **Using Regular Expressions:** 
   - Alternative approaches may utilize regex for transformation, which can express the logic in a more compact form but could be less performant for very large strings given the overhead of regex processing.
   
2. **Typed Arrays (if applicable):**
   - If performance is a critical concern for extremely large datasets, exploring the use of Typed Arrays or optimized string processing libraries that handle strings in a more memory-efficient manner can offer additional performance benefits.

3. **WebAssembly:**
   - For computationally intensive string operations, utilizing WebAssembly (with languages like Rust or C) might provide a performance boost through lower-level optimizations, especially useful in performance-critical applications.

In conclusion, both implementations serve the same purpose, but they differ greatly in terms of performance, especially when scaling up for larger input sizes, highlighting the importance of choosing the right algorithmic approach for string manipulation tasks.

Related benchmarks:

AlgoBenchmark (version: 1)

Comparing performance of: Concat vs Join Array

Created: one year ago by: Guest

Jump to the latest result

Concat

Join Array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):