Benchmark: hash-sum vs object-hash3

HTML Preparation code:

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

Script Preparation code:

var context1 = {show: true, icon: '/point.png', size: 10, color: '#333'}

var context2 = {show: true, icon: '/point.png', size: 10, color: '#333'}

Tests:

Sum
sum(context1) === sum(context2)
JSON stringify
JSON.stringify(context1) === JSON.stringify(context2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Sum
JSON stringify

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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Let's break down the provided benchmark definition and test cases.

**Benchmark Definition**

The benchmark is designed to compare two approaches: using the `hash-sum` library for computing the sum of values in an object, and comparing strings directly (i.e., using the `===` operator).

**Options Compared**

Two options are being compared:

1. **Hashing**: The `hash-sum` library uses a hashing algorithm (likely `sha256`) to compute a fixed-size hash value from the input values.
2. **Direct Comparison**: Directly comparing strings using the `===` operator, which is a simple and lightweight way to compare values.

**Pros and Cons**

1. **Hashing**:
	* Pros: Hashing can be faster for large inputs, as it produces a fixed-size hash value that doesn't require comparing individual elements.
	* Cons: Hashing may not produce accurate results if the input values are not uniformly distributed or have similar hash values (known as " collisions").
2. **Direct Comparison**:
	* Pros: Direct comparison is simple and fast, but can be slower for large inputs due to string comparisons.
	* Cons: Direct comparison requires comparing individual elements, which can lead to performance issues.

**Other Considerations**

1. **Object Hashing**: The `hash-sum` library uses an object hashing approach, where the hash value is computed by summing up all the values in the object. This approach ensures that the order of values doesn't affect the result.
2. **String Comparison**: Direct comparison of strings can be affected by issues like Unicode normalization and character encoding.

**Library: Hash-Sum**

The `hash-sum` library is a JavaScript implementation of a hash sum algorithm. It takes an array of values as input and returns a fixed-size hash value representing the sum of those values.

**Special JS Feature/Syntax**

None mentioned in this benchmark.

**Alternative Approaches**

Other approaches for computing sums or comparing strings include:

1. **Using `reduce()`**: Instead of using the `hash-sum` library, you can use the `Array.prototype.reduce()` method to compute the sum of an array of values.
2. **Using `forEach()` and `summing up manually**`: You can iterate over an array of values using `forEach()` and manually sum them up using a loop or recursion.

For comparing strings, other approaches include:

1. **Using `String.prototype.localeCompare()`**: Instead of using the `===` operator, you can use the `localeCompare()` method to compare strings in a locale-aware manner.
2. **Using `JSON.stringify()` with a custom replacer** : You can create a custom replacer function that compares strings according to your specific requirements.

These alternative approaches may have different trade-offs and performance characteristics compared to using the `hash-sum` library or direct comparison.

Related benchmarks:

hash-sum vs object-hash3 (version: 0)

Comparing performance of: Sum vs JSON stringify

Created: 3 years ago by: Guest

Jump to the latest result

Sum

JSON stringify

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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