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Array splice vs object re assign
(version: 0)
Comparing performance of:
Array splice vs Object re assign
Created:
4 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var input = []; for (var i = 0; i < 50000; i++) { input.push({ id: i, data: 'something' }) }
Tests:
Array splice
const index = input.findIndex(val => val.id === 999); input.splice(index, 1);
Object re assign
var input = []; for (var i = 0; i < 49999; i++) { input.push({ id: i, data: 'something' }) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Array splice
Object re assign
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the provided benchmark and explain what is tested, compared, pros and cons of different approaches, and other considerations. **Benchmark Definition** The provided JSON represents a JavaScript microbenchmark named "Array splice vs object re assign". This benchmark tests the performance difference between two approaches: 1. **Array Splice**: Using `splice()` method to remove an element from an array. 2. **Object Re Assign**: Creating a new array and assigning it to a variable, which effectively achieves the same result as removing an element from the original array. **Benchmark Preparation Code** The script preparation code for this benchmark creates an array with 50,000 elements, each containing `id` and `data` properties. ```javascript var input = []; for (var i = 0; i < 50000; i++) { input.push({ id: i, data: 'something' }); } ``` **Individual Test Cases** There are two test cases: 1. **Array Splice**: This test case uses the `splice()` method to find and remove an element from the array. ```javascript const index = input.findIndex(val => val.id === 999); input.splice(index, 1); ``` 2. **Object Re Assign**: This test case creates a new array with 50,000 elements, which achieves the same result as removing an element from the original array. **Pros and Cons of Different Approaches** 1. **Array Splice**: * Pros: Simple and straightforward. * Cons: + Can be slow for large arrays due to the overhead of finding the index. + May cause additional work when shifting elements after removal. 2. **Object Re Assign**: * Pros: + Avoids the overhead of finding the index. + Does not modify the original array. * Cons: + Creates a new array, which can be memory-intensive for large arrays. + May have performance implications if the new array is created frequently. **Library Usage** There is no explicit library usage in this benchmark. However, the `findIndex()` method used in the Array Splice test case is a part of the ECMAScript standard and is supported by most modern JavaScript engines. **Special JS Features or Syntax** The benchmark uses ES6 syntax features: * `const` declaration for variable binding. * Arrow functions (`=>`) for defining small anonymous functions. * Template literals (`\r\n`) for creating multiline strings. **Other Considerations** When evaluating the performance of these two approaches, consider factors such as: * Array size and complexity * Memory constraints (e.g., if memory allocation or copying is costly) * CPU instructions and architecture * Cache locality and coherence The benchmark results provided show that Chrome 96 on a Desktop platform has faster execution times for both test cases. However, the actual performance differences may vary depending on specific use cases and environments. **Alternatives** If you need to optimize array manipulation performance, consider the following alternatives: 1. **Use `map()` or `filter()`**: Instead of `splice()`, use these methods to create new arrays with modified elements. 2. **Use a library like Lodash**: Some libraries provide optimized implementations for array manipulation operations. 3. **Consider using a different data structure**: If performance is critical, consider switching to a different data structure, such as a linked list or a hash table. Remember that the best approach depends on your specific use case and requirements. Always profile and benchmark your code to determine the most efficient solution.
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