Benchmark: 1f6e53a6-0de2-4e9e-b160-f502c0678a94

Tests:

str.split().pop()
str = `lorem ipsum dolor sit amet consectetur adipiscing elit integer bibendum nunc felis vitae tristique ante luctus ultrices sed ac justo in dolor lobortis dapibus nunc porttitor molestie augue nec rutrum felis cursus eu in ut eros id urna ullamcorper auctor nulla sed metus in leo rhoncus tempor nunc sed facilisis ante praesent luctus dolor quis dictum pulvinar in a neque viverra convallis purus ac placerat libero donec ligula mauris elementum et consequat sit amet commodo quis felis quisque luctus nunc erat curabitur facilisis vehicula pretium ut at tellus sapien ut vitae urna augue nulla varius est ut suscipit varius nunc`; res = str.split(/\s+/).pop()
str.match()
str = `lorem ipsum dolor sit amet consectetur adipiscing elit integer bibendum nunc felis vitae tristique ante luctus ultrices sed ac justo in dolor lobortis dapibus nunc porttitor molestie augue nec rutrum felis cursus eu in ut eros id urna ullamcorper auctor nulla sed metus in leo rhoncus tempor nunc sed facilisis ante praesent luctus dolor quis dictum pulvinar in a neque viverra convallis purus ac placerat libero donec ligula mauris elementum et consequat sit amet commodo quis felis quisque luctus nunc erat curabitur facilisis vehicula pretium ut at tellus sapien ut vitae urna augue nulla varius est ut suscipit varius nunc`; res = str.match(/(?<=\s+)\w+$/)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
str.split().pop()
str.match()

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:104.0) Gecko/20100101 Firefox/104.0

Browser/OS: Firefox 104 on Linux

View result in a separate tab

Test name	Executions per second
str.split().pop()	102631.9 Ops/sec
str.match()	148096.2 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 2 months ago):

LLMs can make mistakes. Check important info.

I'll break down the provided JSON benchmark data into its components and explain what's being tested, compared, and their pros/cons.

**Benchmark Definition**

The `Benchmark Definition` is a JavaScript code snippet that represents the test case. In this case, there are two test cases:

1. `str.split().pop()`: This test case uses the `split()` method to split the string into an array of substrings and then returns the last element using the `.pop()` method.
2. `str.match()`: This test case uses the `match()` method to search for a pattern in the string.

**Options Compared**

The two test cases are comparing the performance of the `split()` method vs. the `match()` method in JavaScript.

**Pros/Cons of Different Approaches**

1. **`split()` Method**:
	* Pros: Can be used to split strings into arrays, and it's a widely supported method.
	* Cons: May not be efficient for large strings, as it creates an array with multiple elements.
2. **`match()` Method**:
	* Pros: More efficient than `split()`, especially for large strings, since it returns a single match object instead of creating an array.
	* Cons: Limited to searching for specific patterns in the string.

**Library**

There is no library explicitly mentioned in the provided code snippets. However, both methods rely on built-in JavaScript functionality.

**Special JS Feature/Syntax**

Neither test case uses any special JavaScript features or syntax beyond standard JavaScript syntax.

**Other Alternatives**

If you need to measure the performance of other string manipulation methods, such as:

* `concat()` vs. concatenation using the `+` operator
* Regular expressions (`regex`) for pattern matching
* String iteration (e.g., using `for...in` or `Array.prototype.forEach()`)
* Other libraries like Lodash or Moment.js

you can create new test cases to compare these methods.

**Best Practices**

To write effective benchmarking code:

1. Use a clear and concise name for your benchmark case.
2. Provide relevant context, such as the string being tested.
3. Use meaningful variable names to make your code easy to understand.
4. Test specific scenarios or edge cases to ensure accurate results.

By following these guidelines, you can create robust and informative benchmarks that help developers optimize their code.

Related benchmarks:

1f6e53a6-0de2-4e9e-b160-f502c0678a94 (version: 0)

Comparing performance of: str.split().pop() vs str.match()

Created: 2 years ago by: Guest

Jump to the latest result

str.split().pop()

str.match()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 2 months ago):