Benchmark: Computational efficiency: 0 vs. false (or true) v1.1

Script Preparation code:

const good = true;
const bad = false;

Tests:

!0
const good = true; good == !0
boolean true
const good = true; good == true
!1
const bad = false; bad == false
boolean false
const bad = false; bad == false

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
!0
boolean true
!1
boolean false

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.100 Safari/537.36

Browser/OS: Chrome 69 on Windows XP

View result in a separate tab

Test name	Executions per second
!0	328055808.0 Ops/sec
boolean true	324373472.0 Ops/sec
!1	330643104.0 Ops/sec
boolean false	327799232.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring computational efficiency is crucial in JavaScript development, and MeasureThat.net provides a valuable platform for benchmarking different approaches.

**Benchmark Definition**

The provided JSON represents a simple benchmark definition with two options being compared:

1. `true` (or `"!0"`)
2. `false` (or `"!1"`)

The script preparation code defines two variables: `good` and `bad`, initialized to `true` and `false`, respectively.

**Options Comparison**

The test case uses the following options for comparison:

* Option 1: `good == !0`
* Option 2: `good == true`
* Option 3: `bad == false`
* Option 4: `bad == "boolean false"`

Let's analyze each option:

Pros and Cons:

* **Option 1 (`good == !0`)**: This option is equivalent to using the unary NOT operator (`!`) on a boolean value. While this might seem like a good idea, it can lead to unexpected behavior if not used carefully.
	+ Pros: Simple and concise.
	+ Cons: May be confusing or hard to read for some developers.
* **Option 2 (`good == true`)**: This option is straightforward and easy to understand.
	+ Pros: Easy to read and maintain.
	+ Cons: May lead to incorrect assumptions about the behavior of `!0`.
* **Option 3 (`bad == false`)**: Similar to Option 1, but with a negative value.
	+ Pros: Same pros and cons as Option 1.
* **Option 4 (`bad == "boolean false"`):** This option is using template literals or string concatenation to create a string literal `"boolean false"`. While this might seem like a good idea for readability, it's not the most efficient way to compare values in JavaScript.
	+ Pros: Easy to read and maintain (for developers familiar with template literals).
	+ Cons: Less efficient than other options.

**Library Use**

In the benchmark definition, there is no explicit library use mentioned. However, some test cases might use libraries like `lodash` or `moment.js`, which are not relevant to this specific benchmark.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in this benchmark, such as ES6 modules, async/await, or destructuring.

**Other Alternatives**

If you wanted to measure the computational efficiency of a different approach, you could consider using:

* `null` instead of `false`
* An empty string (`""`) instead of `"boolean false"`
* A numerical value (e.g., `0`) instead of `true` or `false`

Keep in mind that the best approach depends on the specific use case and requirements of your project.

Overall, MeasureThat.net provides a valuable platform for benchmarking different approaches to measuring computational efficiency in JavaScript. By understanding the pros and cons of each option, developers can make informed decisions about how to optimize their code for better performance.

Related benchmarks:

Computational efficiency: 0 vs. false (or true) v1.1 (version: 1)

Comparing performance of: !0 vs boolean true vs !1 vs boolean false

Created: 3 years ago by: Registered User

Jump to the latest result

!0

boolean true

!1

boolean false

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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