Benchmark: fde vs object-hash vs hash-sum

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/hash-sum@2.0.0/hash-sum.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/object-hash@2.0.3/dist/object_hash.min.js"></script>

Script Preparation code:

var fde = function r(t,e){if(t===e)return!0;if(t&&e&&"object"==typeof t&&"object"==typeof e){if(t.constructor!==e.constructor)return!1;var o,n,u;if(Array.isArray(t)){if((o=t.length)!=e.length)return!1;for(n=o;0!=n--;)if(!r(t[n],e[n]))return!1;return!0}if(t.constructor===RegExp)return t.source===e.source&&t.flags===e.flags;if(t.valueOf!==Object.prototype.valueOf)return t.valueOf()===e.valueOf();if(t.toString!==Object.prototype.toString)return t.toString()===e.toString();if((o=(u=Object.keys(t)).length)!==Object.keys(e).length)return!1;for(n=o;0!=n--;)if(!Object.prototype.hasOwnProperty.call(e,u[n]))return!1;for(n=o;0!=n--;){var f=u[n];if(!r(t[f],e[f]))return!1}return!0}return t!=t&&e!=e};

var context1 = {
  title: 'fish',
  position: 1
}

var context2 = {
  title: 'fish',
  position: 1
}

Tests:

sum(context1) === sum(context2)
sum(context1) === sum(context2)
objectHash(context1) === objectHash(context2)
objectHash(context1) === objectHash(context2)
fde
fde(context1, context2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
sum(context1) === sum(context2)
objectHash(context1) === objectHash(context2)
fde

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/111.0.0.0 Safari/537.36

Browser/OS: Chrome 111 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
sum(context1) === sum(context2)	351377.9 Ops/sec
objectHash(context1) === objectHash(context2)	6636.0 Ops/sec
fde	869435.5 Ops/sec

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

LLMs can make mistakes. Check important info.

**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON represents a benchmark with multiple test cases, each comparing different approaches for checking equality between two objects.

**Benchmark Definition**

The `Benchmark Definition` JSON defines three test cases:

1. **fde (Function Equality Detector)**: This test case uses the `fde` function to check if two objects are equal. The `fde` function is a custom implementation that checks the type and properties of both objects.
2. **object-hash**: This test case uses the `hash-sum` library to calculate the hash sum of each object. Two objects are considered equal if their hash sums match.
3. **sum (Hash Sum)**: This test case also uses the `hash-sum` library, but with a slight variation. It calculates the sum of all properties in both objects and checks if they match.

**Options Compared**

The three test cases compare different approaches to checking equality between two objects:

* **fde**: Uses a custom implementation that checks type and properties.
* **object-hash**: Uses a hash sum approach to calculate a unique identifier for each object.
* **sum**: Variations of the hash sum approach, where it calculates the sum of all properties instead of individual hash sums.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **fde (Function Equality Detector)**:
	* Pros: Provides a detailed check of object equality, including type and property comparisons.
	* Cons: Can be slower due to its custom implementation and potentially complex logic.
2. **object-hash**: 
	* Pros: Fast and efficient, as it only requires calculating the hash sum of each object.
	* Cons: May not work correctly for objects with circular references or other special properties.
3. **sum (Hash Sum)**:
	* Pros: Similar to `object-hash`, but with an additional layer of complexity by considering all properties.
	* Cons: Requires more computations, potentially making it slower.

**Other Considerations**

When choosing between these approaches, consider the following:

* If you need a detailed check of object equality, use **fde**. However, be aware that this may come at the cost of performance.
* For fast and efficient checks, **object-hash** is a good choice. Just ensure that your objects are suitable for this approach (e.g., no circular references).
* If you need to consider all properties in both objects, use **sum**.

**Libraries**

The `hash-sum` library is used in two test cases:

1. **object-hash**: Provides the `hashSum` function for calculating a unique identifier for each object.
2. **sum (Hash Sum)**: Uses the same `hashSum` function, but with an additional layer of complexity.

**Special JavaScript Features**

No special JavaScript features or syntax are mentioned in this benchmark.

Related benchmarks:

fde vs object-hash vs hash-sum (version: 0)

fde2

Comparing performance of: sum(context1) === sum(context2) vs objectHash(context1) === objectHash(context2) vs fde

Created: one year ago by: Guest

Jump to the latest result

sum(context1) === sum(context2)

objectHash(context1) === objectHash(context2)

fde

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):