Benchmark: NaN speed - MeasureThat.net

Script Preparation code:

var a = 8

Tests:

NaN
return isNaN(NaN)
not NaN
return isNaN(5)
0 or zero
return NaN === 0
0 or zero 2
return 5 === 0

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
NaN
not NaN
0 or zero
0 or zero 2

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 break down the explanation into smaller sections to make it easier to understand.

**Benchmark Definition and Script Preparation Code**

The provided benchmark definition JSON represents a simple JavaScript function that tests for the presence of NaN (Not a Number) values. The script preparation code is:

`var a = 8`

This line simply assigns the value `8` to a variable named `a`. This code is executed before each test case.

**Html Preparation Code**

There is no HTML preparation code provided, which means that the benchmark does not generate any HTML content for testing.

**Individual Test Cases**

The individual test cases are defined as follows:

1. `return isNaN(NaN)` - Tests if NaN can be recognized by the JavaScript engine.
2. `return isNaN(5)` - Tests if a number (in this case, 5) is considered non-NaN by the JavaScript engine.
3. `return NaN === 0` - Tests for equality with zero using the loose comparison operator (===).
4. `return 5 === 0` - Tests for equality between two numbers using the strict comparison operator (===).

**Library Used: None**

There is no library explicitly mentioned in the benchmark definition.

**Special JavaScript Feature/Syntax**

The use of `NaN` (Not a Number) is specific to JavaScript and represents an uninitialized or invalid numeric value. It's not a feature commonly discussed, but its purpose is essential for testing numerical computations.

**Pro cons of different approaches**

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

1. **isNaN(NaN)**:
	* Pros: This test case checks if NaN can be recognized as such.
	* Cons: If the JavaScript engine incorrectly identifies NaN, this test may fail.
2. **isNaN(5)**:
	* Pros: This test case verifies that numbers are not considered non-NaN (NaN).
	* Cons: If the JavaScript engine incorrectly identifies 5 as NaN, this test may fail.
3. **NaN === 0**:
	* Pros: This test case checks for equality with zero using a loose comparison operator.
	* Cons: The loose comparison operator can be misleading in some cases.
4. **5 === 0**:
	* Pros: This test case checks for strict equality between two numbers.
	* Cons: It may not work correctly if the JavaScript engine performs implicit type conversions.

**Other Considerations**

When writing benchmarks, consider the following factors:

1. **Test coverage**: Ensure that your benchmark covers various edge cases and scenarios to obtain accurate results.
2. **Algorithmic complexity**: Measure the performance of algorithms with varying levels of complexity, such as loops, conditional statements, and data structures.
3. **Library dependencies**: Identify if any libraries are used in your benchmarks and measure their impact on performance.

**Alternative Benchmarking Frameworks**

Some popular alternative benchmarking frameworks include:

1. **Benchmark.js**: A lightweight, modular benchmarking framework for Node.js applications.
2. **Benchmarks.net**: Another JSON-based benchmarking framework that allows you to create and run microbenchmarks.
3. **jsperf.com**: A web-based platform for creating and comparing JavaScript benchmarks.

Keep in mind that the choice of benchmarking framework ultimately depends on your specific use case, performance requirements, and personal preferences.

Related benchmarks:

NaN speed (version: 0)

Hi im test

Comparing performance of: NaN vs not NaN vs 0 or zero vs 0 or zero 2

Created: 9 years ago by: Registered User

Jump to the latest result

NaN

not NaN

0 or zero

0 or zero 2

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):