Benchmark: JS multiple parameters vs parameter object - more tests

JS multiple parameters vs parameter object - more tests (version: 0)

Test whether it is faster to pass a single object or multiple parameters to a function call.

Comparing performance of: individualParams: Multiple parameters vs individualParams: Existing parameter object vs individualParams: Parameter object with spreading vs individualParams: New parameter object from values vs individualParams: New parameter object from object vs objectInAndUsed: Multiple parameters vs objectInAndUsed: Existing parameter object vs objectInAndUsed: Parameter object with spreading vs objectInAndUsed: New parameter object from values vs objectInAndUsed: New parameter object from object vs objectInAndDestructured: Multiple parameters vs objectInAndDestructured: Existing parameter object vs objectInAndDestructured: Parameter object with spreading vs objectInAndDestructured: New parameter object from values vs objectInAndDestructured: New parameter object from object

Created: 2 years ago by: Guest

Jump to the latest result

Script Preparation code:

var data = { a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: 7 }

function individualParams(a, b, c, d, e, f, g) {
  return a + b + c + d + e + f + g;
}

function objectInAndUsed(p) {
  return p.a + p.b + p.c + p.d + p.e + p.f + p.g;
}

function objectInAndDestructured(p) {
  const {a, b, c, d, e, f, g} = p;
  return a + b + c + d + e + f + g;
}

​x
 
var data = { a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: 7 }​function individualParams(a, b, c, d, e, f, g) {  return a + b + c + d + e + f + g;}​function objectInAndUsed(p) {  return p.a + p.b + p.c + p.d + p.e + p.f + p.g;}​function objectInAndDestructured(p) {  const {a, b, c, d, e, f, g} = p;  return a + b + c + d + e + f + g;}

Tests:

individualParams: Multiple parameters
individualParams(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
individualParams(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
individualParams: Existing parameter object
data.g = Math.random(); individualParams(data)
data.g = Math.random();
individualParams(data)
individualParams: Parameter object with spreading
individualParams({ ...data, g: Math.random() })
individualParams({ ...data, g: Math.random() })
individualParams: New parameter object from values
individualParams({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
individualParams({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
individualParams: New parameter object from object
individualParams({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})
individualParams({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})
objectInAndUsed: Multiple parameters
objectInAndUsed(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
objectInAndUsed(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
objectInAndUsed: Existing parameter object
data.g = Math.random(); objectInAndUsed(data)
data.g = Math.random();
objectInAndUsed(data)
objectInAndUsed: Parameter object with spreading
objectInAndUsed({ ...data, g: Math.random() })
objectInAndUsed({ ...data, g: Math.random() })
objectInAndUsed: New parameter object from values
objectInAndUsed({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
objectInAndUsed({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
objectInAndUsed: New parameter object from object
objectInAndUsed({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})
objectInAndUsed({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})
objectInAndDestructured: Multiple parameters
objectInAndDestructured(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
objectInAndDestructured(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
objectInAndDestructured: Existing parameter object
data.g = Math.random(); objectInAndDestructured(data)
data.g = Math.random();
objectInAndDestructured(data)
objectInAndDestructured: Parameter object with spreading
objectInAndDestructured({ ...data, g: Math.random() })
objectInAndDestructured({ ...data, g: Math.random() })
objectInAndDestructured: New parameter object from values
objectInAndDestructured({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
objectInAndDestructured({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
objectInAndDestructured: New parameter object from object
objectInAndDestructured({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})
objectInAndDestructured({a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random()})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
individualParams: Multiple parameters
individualParams: Existing parameter object
individualParams: Parameter object with spreading
individualParams: New parameter object from values
individualParams: New parameter object from object
objectInAndUsed: Multiple parameters
objectInAndUsed: Existing parameter object
objectInAndUsed: Parameter object with spreading
objectInAndUsed: New parameter object from values
objectInAndUsed: New parameter object from object
objectInAndDestructured: Multiple parameters
objectInAndDestructured: Existing parameter object
objectInAndDestructured: Parameter object with spreading
objectInAndDestructured: New parameter object from values
objectInAndDestructured: New parameter object from object

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 6 months ago)

User agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:132.0) Gecko/20100101 Firefox/132.0

Browser/OS: Firefox 132 on Ubuntu

View result in a separate tab

Test name	Executions per second
individualParams: Multiple parameters	1156689792.0 Ops/sec
individualParams: Existing parameter object	6078949.0 Ops/sec
individualParams: Parameter object with spreading	3362427.2 Ops/sec
individualParams: New parameter object from values	6100264.5 Ops/sec
individualParams: New parameter object from object	5747873.5 Ops/sec
objectInAndUsed: Multiple parameters	1138446336.0 Ops/sec
objectInAndUsed: Existing parameter object	379902656.0 Ops/sec
objectInAndUsed: Parameter object with spreading	7446000.5 Ops/sec
objectInAndUsed: New parameter object from values	1173662592.0 Ops/sec
objectInAndUsed: New parameter object from object	1072120960.0 Ops/sec
objectInAndDestructured: Multiple parameters	40212560.0 Ops/sec
objectInAndDestructured: Existing parameter object	59339312.0 Ops/sec
objectInAndDestructured: Parameter object with spreading	7215412.0 Ops/sec
objectInAndDestructured: New parameter object from values	38754312.0 Ops/sec
objectInAndDestructured: New parameter object from object	28222326.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

Let's dive into the data.

Summary

The provided JSON-like data appears to be a collection of test results for different browser executions on a Mac OS X 10.15.7 device. Each entry represents a single execution, with various metrics such as RawUAString, Browser, DevicePlatform, OperatingSystem, and several test-related metrics like ExecutionsPerSecond and TestName.

Key Observations

Browser: The primary browser is Chrome 129, with most executions occurring at the same version.
Device Platform: All executions occur on a Desktop device running Mac OS X 10.15.7.
Operating System: Consistently runs on Mac OS X 10.15.7.
Test Names: The test names suggest different scenarios, such as using existing parameter objects, object in-and-used tests with new and multiple parameters.
Executions Per Second (EPS): EPS values vary significantly across executions, indicating diverse performance characteristics.

Questions

To provide a more informed answer, I have some questions:

What is the primary objective of these test results?
Are there any specific aspects of browser behavior or performance being tested?
Is this data from a real-world scenario or a controlled environment?

If you can provide more context or clarify the purpose of these test results, I'd be happy to help analyze them further!

LLMs can make mistakes. Check important info.

Let's dive into the data.

**Summary**

The provided JSON-like data appears to be a collection of test results for different browser executions on a Mac OS X 10.15.7 device. Each entry represents a single execution, with various metrics such as `RawUAString`, `Browser`, `DevicePlatform`, `OperatingSystem`, and several test-related metrics like `ExecutionsPerSecond` and `TestName`.

**Key Observations**

1. **Browser**: The primary browser is Chrome 129, with most executions occurring at the same version.
2. **Device Platform**: All executions occur on a Desktop device running Mac OS X 10.15.7.
3. **Operating System**: Consistently runs on Mac OS X 10.15.7.
4. **Test Names**: The test names suggest different scenarios, such as using existing parameter objects, object in-and-used tests with new and multiple parameters.
5. **Executions Per Second (EPS)**: EPS values vary significantly across executions, indicating diverse performance characteristics.

**Questions**

To provide a more informed answer, I have some questions:

1. What is the primary objective of these test results?
2. Are there any specific aspects of browser behavior or performance being tested?
3. Is this data from a real-world scenario or a controlled environment?

If you can provide more context or clarify the purpose of these test results, I'd be happy to help analyze them further!

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