Benchmark: test for anargam

Tests:

with methods
function doer (s,t) { return [...s].sort().join("") == t } doer("alireza" , "arlizae")
without methods
let isAnagram = function(s, t) { if (s.length !== t.length) { return false; } let freq = new Array(26).fill(0); for (let i = 0; i < s.length; i++) { freq[s.charCodeAt(i) - 'a'.charCodeAt(0)]++; freq[t.charCodeAt(i) - 'a'.charCodeAt(0)]--; } for (let i = 0; i < freq.length; i++) { if (freq[i] !== 0) { return false; } } return true; }; isAnagram("alireza" , "arlizae")

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
with methods
without methods

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/113.0

Browser/OS: Firefox 113 on Windows

View result in a separate tab

Test name	Executions per second
with methods	1442534.8 Ops/sec
without methods	2975174.5 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Purpose**
The test is designed to measure the performance difference between two approaches: using built-in JavaScript functions (in this case, `sort()` method) versus implementing a custom algorithm from scratch. The goal is to compare which approach is faster for checking if two strings are anagrams of each other.

**Options Compared**

1. **Built-in JavaScript Function (`sort()` Method)**:
	* Pros: Easy to implement, reliable results, and well-optimized by the browser.
	* Cons: May not be optimized for this specific task, can be slower due to the overhead of sorting the entire string.
2. **Custom Algorithm (without methods)**:
	* Pros: Optimized specifically for this task, can be faster than the built-in approach.
	* Cons: Requires manual implementation and may have errors or performance issues if not implemented correctly.

**Custom Algorithm (with methods)**
The custom algorithm uses a frequency count approach to compare the two strings. It creates an array of 26 elements (one for each letter of the alphabet) and increments/decrements the corresponding index based on the character code of each string. If all indices are zero, it means the strings are anagrams.

**Other Considerations**

* The test also measures the number of executions per second (ExecutionsPerSecond), which provides an idea of the raw performance difference between the two approaches.
* The `DevicePlatform` and `OperatingSystem` fields indicate that the test was run on a desktop computer with Windows 10, using Firefox 113.

**Library Used**
There is no explicit library used in this benchmark. However, it's worth noting that the `charCodeAt()` method is used to get the ASCII code of each character, which is a built-in JavaScript method.

**Special JS Feature/Syntax**
There are no specific JavaScript features or syntax mentioned in the benchmark definition or individual test cases.

**Alternative Approaches**

1. **Using `set` and `size` Properties**: Instead of using an array to store frequency counts, you could use the `Set` constructor and `size` property to achieve a more concise implementation.
2. **Using Regular Expressions**: You can use regular expressions to check if two strings are anagrams by comparing their character sets. This approach might be faster but also less readable than the custom algorithm.

In summary, the benchmark tests the performance difference between using built-in JavaScript functions (in this case, `sort()` method) versus implementing a custom algorithm from scratch for checking if two strings are anagrams of each other.

Related benchmarks:

test for anargam (version: 0)

Comparing performance of: with methods vs without methods

Created: one year ago by: Registered User

Jump to the latest result

with methods

without methods

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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