Benchmark: 1 var vs 2 vars vs 3 vars

Script Preparation code:

var array = new Array(65535).fill()

Tests:

Three
var a = array.map((x) => x) var b = array.map((x) => x) var c = array.map((x) => x)
two
var a = array.map((x) => x) var b = array.map((x) => x).map((x) => x)
single
var a = array.map((x) => x).map((x) => x).map((x) => x)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Three
two
single

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):

LLMs can make mistakes. Check important info.

I'll provide an explanation of the provided benchmark definition and test cases, highlighting the options being compared, their pros and cons, and other considerations.

**Benchmark Definition**

The benchmark is designed to compare the performance of different approaches for mapping over an array in JavaScript. The script preparation code initializes an array with 65,535 elements filled with a value (in this case, undefined). This creates a large array that can be used to test various mapping methods.

**Options Being Compared**

Three different approaches are being compared:

1. **Single Map**: `var c = array.map((x) => x)` - This approach maps over the array once and assigns the result to variable `c`.
2. **Double Map**: `var b = array.map((x) => x).map((x) => x)` - This approach maps over the array twice, first assigning the intermediate result to `b`, and then mapping over it again.
3. **Triple Map**: `var a = array.map((x) => x).map((x) => x).map((x) => x)` - This approach maps over the array three times.

**Pros and Cons of Each Approach**

1. **Single Map (c)**:
	* Pros: Less overhead due to fewer function calls.
	* Cons: May lead to slower performance if the intermediate result is large or complex.
2. **Double Map (b)**:
	* Pros: Can potentially utilize more CPU resources by reusing the intermediate result.
	* Cons: Doubles the number of function calls, which can increase overhead.
3. **Triple Map (a)**:
	* Pros: May exhibit better performance due to increased reuse of intermediate results.
	* Cons: More complex and likely to lead to slower performance.

**Other Considerations**

The benchmark also considers the impact of the `map` method on JavaScript engines. The `map` method can be optimized by some engines, while others may not optimize it as aggressively. This means that the actual performance difference between these approaches may vary depending on the JavaScript engine being used.

**Test Case Library (Lodash)**

The test case uses Lodash, a popular utility library for JavaScript. In this specific case, Lodash is used to provide the `map` method implementation in the benchmark script preparation code. Lodash's `map` method is designed to optimize performance by reusing intermediate results.

**Special JS Feature or Syntax**

There are no special JS features or syntax used in these test cases beyond what is typically supported by modern JavaScript engines.

**Benchmark Preparation Code and Latest Benchmark Result**

The benchmark preparation code initializes an array with 65,535 elements filled with a value. The latest benchmark result shows the performance of each approach for Chrome 119 on Windows desktop platforms:

| Test Name | Execution Per Second |
| --- | --- |
| Single (c) | 573.81 |
| Double (b) | 556.65 |
| Triple (a) | 546.01 |

These results suggest that the triple map approach may lead to slightly slower performance, while the single map approach provides the best result.

**Other Alternatives**

Some alternative approaches could be explored:

1. **For Loop**: Instead of using `map`, a for loop can be used to iterate over the array, which might provide better performance.
2. **Native Array Functions**: Some native JavaScript functions, like `forEach` or `reduce`, might offer different optimization paths that affect performance.

Keep in mind that these alternatives may not necessarily lead to better performance and should be tested specifically for each use case.

Related benchmarks:

1 var vs 2 vars vs 3 vars (version: 0)

Comparing performance of: Three vs two vs single

Created: 3 years ago by: Guest

Jump to the latest result

Three

two

single

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):