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POJO vs Functions no loop
(version: 21)
Comparing performance of:
POJO vs Function
Created:
9 years ago
by:
Registered User
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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_" } ] }; }
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Test case name
Result
POJO
Function
Fastest:
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Slowest:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
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.
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