Benchmark: POJO vs Functions no loop

Tests:

POJO
var x = { value : 10, label : 'Codice fiscale, valueStyle : { fontsize: 14 }, isEmpty : function() { return 2%2 == 0 }, isVisible : true, style : { xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5 }, otherStuff: [ { style: {color: "red", xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5} , class: "test_" }, { style: {color: "blue"}, class: "toast_" } ] };
Function
var xxx = { value : 20, label : 'Codice fiscale', valueStyle : { fontsize: 14 }, isEmpty : function() { return 2%2 == 0 }, isVisible : true, style : { xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5 }, otherStuff: [ { style: {color: "red", xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5} , class: "test_" }, { style: {color: "blue"}, class: "toast_" } ] }; var y = function() { return { value : 10, label : 'Codice fiscale', valueStyle : { fontsize: 14 }, isEmpty : function() { return 2%2 == 0 }, isVisible : true, style : { xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5 }, otherStuff: [ { style: {color: "red", xs_width: "100%", sm_width: "50%", xs_marginBottom: 20, sm_paddingRight: 5} , class: "test_" }, { style: {color: "blue"}, class: "toast_" } ] }; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
POJO
Function

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Measuring the performance of JavaScript objects and functions is crucial in understanding how different approaches can impact application performance.

**Benchmark Definition**

The benchmark is defined by two test cases:

1. **POJO (Plain Old JavaScript Object)**: This test case creates a JavaScript object with various properties, including `value`, `label`, `isEmpty`, `isVisible`, `style`, and `otherStuff`. The object is designed to mimic a real-world data structure.
2. **Function**: This test case defines a function that returns a similar object to the POJO test case.

**Options Compared**

The benchmark compares two approaches:

1. **POJO (Plain Old JavaScript Object)**: This approach creates and manipulates a JavaScript object directly.
2. **Function**: This approach defines a self-contained function that returns the desired object structure.

**Pros and Cons of Each Approach**

### POJO (Plain Old JavaScript Object)

Pros:

* More readable and maintainable code
* Can be easily extended or modified
* Native JavaScript object behavior

Cons:

* May incur overhead due to object creation and manipulation
* May lead to slower performance compared to other approaches

### Function

Pros:

* Encapsulates data and behavior into a single unit
* Can reduce overhead by avoiding unnecessary object creation
* Can provide better encapsulation and protection from external modifications

Cons:

* May require additional setup and configuration
* Can be more complex and harder to read
* May lead to slower performance due to function call overhead

**Library Used**

In this benchmark, the `toString()` method is used to convert objects to strings. The `JSON.stringify()` method is also used in some test cases.

The `JSON.stringify()` method can add overhead compared to using `toString()`, as it performs additional parsing and formatting steps.

**Special JS Feature or Syntax**

None mentioned.

**Other Considerations**

* **Object creation**: Creating objects can be an expensive operation, especially when compared to creating arrays. The benchmark measures the performance of object creation in both approaches.
* **Function call overhead**: Defining a function can incur additional overhead due to the need for function lookups and calls. The `Function` test case uses this approach to create and manipulate objects.

**Alternatives**

Other alternatives to consider when optimizing JavaScript performance include:

1. **Array-based data structures**: Using arrays instead of objects can provide faster performance in some cases.
2. **Prototype-based programming**: Using prototype chains instead of object creation can reduce overhead and improve performance.
3. **Just-In-Time (JIT) compilation**: Enabling JIT compilation can provide significant performance improvements for certain use cases.

These alternatives should be evaluated on a case-by-case basis to determine the best approach for specific performance-critical code paths.

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36

Browser/OS: Chrome 55 on Windows

View result in a separate tab

Test name	Executions per second
POJO	842936.4 Ops/sec
Function	62792236.0 Ops/sec
Function w/ return	6307678.0 Ops/sec

Related benchmarks:

POJO vs Functions no loop (version: 21)

Comparing performance of: POJO vs Function

Created: 7 years ago by: Registered User

Jump to the latest result

POJO

Function

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):