Benchmark: Operators - MeasureThat.net

Tests:

*
var x = 42 * 42;
+
var x = 42 + 42;
-
var x = 42 - 42;
/
var x = 42 / 42;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
*
+
-
/

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 benchmark and explain what's being tested, compared, and some pros and cons of each approach.

**Benchmark Overview**

The benchmark is designed to measure the performance of arithmetic operators (*, +, -, /) in JavaScript. The benchmark consists of four individual test cases, each with a different operator.

**Script Preparation Code and Html Preparation Code**

Both fields are empty, indicating that no script or HTML code needs to be prepared for the benchmark. This suggests that the benchmark is focused solely on measuring the performance of the arithmetic operators themselves.

**Individual Test Cases**

Each test case has two main components:

1. **Benchmark Definition**: A string that defines the JavaScript expression to be executed during the benchmark. The expressions are simple arithmetic operations:
	* `var x = 42 * 42;`
	* `var x = 42 + 42;`
	* `var x = 42 - 42;`
	* `var x = 42 / 42;`
2. **Test Name**: The name of the test case, which is simply the operator being tested (*, +, -, /).

**Comparison**

The benchmark compares the performance of each arithmetic operator in different browsers and devices. The comparison is based on the "Executions Per Second" metric, which measures how many times the expression is executed per second.

**Options Compared**

In this context, the options compared are:

* Arithmetic operators (*, +, -, /)
* Different browsers (Mobile Safari 14)
* Different devices (iPhone with iOS 14.2.1)

**Pros and Cons of Each Approach**

Each approach has its pros and cons:

* **Operator-based approach**: This approach focuses on measuring the performance of individual arithmetic operators. Pros: allows for a clear understanding of each operator's performance, independent of other factors. Cons: might not accurately reflect real-world scenarios where operators are used together.
* **Browser-based approach**: This approach measures the performance of each browser in different devices. Pros: provides insight into how browsers perform on various hardware configurations. Cons: might be influenced by factors like browser caching, rendering engines, and device-specific optimizations.
* **Device-based approach**: This approach focuses on measuring the performance of each device in different browsers. Pros: helps identify performance issues related to specific hardware configurations. Cons: might not accurately reflect browser-specific performance differences.

**Library Use**

There is no library explicitly mentioned in the benchmark definition or test cases. However, it's likely that the browser's built-in JavaScript engine is being used for these tests.

**Special JS Features or Syntax**

None of the test cases use special JS features or syntax. The expressions are simple arithmetic operations that do not rely on any advanced features like async/await, generators, or decorators.

**Alternatives**

Some alternative approaches to benchmarking arithmetic operators in JavaScript might include:

* Using a testing framework like Jest or Mocha to write unit tests for specific arithmetic functions.
* Creating a library specifically designed for performance-critical arithmetic operations.
* Using a benchmarking library like Benchmark.js or Microbenchmark to create more complex benchmarks.

Keep in mind that these alternatives would require additional setup and configuration, and might not provide the same level of insight into the performance characteristics of individual operators.

Related benchmarks:

Operators (version: 0)

Benchmarking arithmetic

Comparing performance of: * vs + vs - vs /

Created: 5 years ago by: Guest

Jump to the latest result

*

+

-

/

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):