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class vs function mk I
(version: 0)
Comparing performance of:
class vs function
Created:
2 years ago
by:
Guest
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Tests:
class
class Test { constructor(x) { this.x = x; } add() { return (Math.pow(this.x, 10) + Math.exp(this.x) + Math.sin(this.x) - Math.cos(this.x)); } } for (var i = 0; i < 100; i++) { new Test(34235345345342342323423422334423).add(); }
function
function add(x) { return (Math.pow(x, 10) + Math.exp(x) + Math.sin(x) - Math.cos(x)); } for (var i = 0; i < 100; i++) { add(34235345345342342323423422334423); }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
class
function
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:125.0) Gecko/20100101 Firefox/125.0
Browser/OS:
Firefox 125 on Mac OS X 10.15
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Test name
Executions per second
class
210906.5 Ops/sec
function
20574324.0 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmarking scenario. **Benchmark Definition and Preparation Code** The `Script Preparation Code` is empty, which means that no setup code needs to be executed before running the benchmark tests. This is often the case when comparing built-in functions or methods. **Individual Test Cases** There are two test cases: 1. **Class Test** * The `Benchmark Definition` is a JavaScript class definition with a constructor and an `add()` method. * The `Test Name` is "class", indicating that this test case uses the class-based approach. 2. **Function Test** * The `Benchmark Definition` is a standalone JavaScript function named `add()`. * The `Test Name` is "function", indicating that this test case uses the function-based approach. **Library Usage** None of the test cases use any external libraries or frameworks. **Special JS Feature/Syntax** There are no special JavaScript features or syntax used in these test cases. Both classes and functions follow standard JavaScript conventions. **Comparison** The two test cases compare the performance of class-based and function-based implementations of a simple mathematical operation (`add()`) with multiple iterations (100 times). **Pros and Cons of Different Approaches** 1. **Class-Based Approach** * Pros: + Can encapsulate data and behavior, promoting object-oriented programming principles. + May provide better code organization and reusability. * Cons: + Can result in slower execution due to the overhead of object creation and method invocation. 2. **Function-Based Approach** * Pros: + Is generally faster and more lightweight than class-based implementations. + Does not require the creation of objects, reducing memory allocation and garbage collection overhead. * Cons: + May lack encapsulation and code organization benefits. **Other Considerations** To accurately compare these test cases, it's essential to consider factors like: 1. **Method invocation overhead**: In class-based implementations, method invocation involves creating an object instance, which can lead to additional memory allocation and garbage collection overhead. 2. **Object creation overhead**: Class-based implementations require the creation of objects for each iteration, whereas function-based implementations do not create any objects. **Alternative Approaches** Other alternatives could be: 1. **Procedural Programming**: Implementing the `add()` operation using a traditional procedural programming style (e.g., using loops and arrays). 2. **Generator Functions**: Using generator functions to implement the `add()` operation, which can provide better performance due to the lack of object creation overhead. 3. **Arrow Functions**: Using arrow functions as an alternative to traditional function definitions. These alternatives could be used to compare their performance with class-based and function-based implementations in a separate benchmarking scenario.
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