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slice sort vs spread sort vs sort vs structured sort
(version: 0)
Comparing performance of:
slice sort vs spread sort vs sort vs structured sort
Created:
3 years ago
by:
Guest
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Script Preparation code:
var a=Array.from({length:100},()=>Math.random())
Tests:
slice sort
a.slice().sort();
spread sort
[...a].sort()
sort
a.sort()
structured sort
structuredClone(a).sort()
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (4)
Previous results
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Test case name
Result
slice sort
spread sort
sort
structured sort
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'll break down the provided JSON and explain what's being tested, the options compared, their pros and cons, and other considerations. **Benchmark Definition** The benchmark is designed to compare four different sorting algorithms: slice sort, spread sort, regular sort, and structured sort. The script preparation code creates an array of 100 random numbers using `Array.from` and `Math.random`. There's no HTML preparation code provided. **Individual Test Cases** Each test case represents a specific sorting algorithm: 1. **Slice Sort**: `a.slice().sort()` * This approach uses the `slice()` method to create a shallow copy of the array, followed by the regular `sort()` method. * Pros: Can be efficient for small arrays and might have good cache locality. * Cons: Creates an additional object in memory, which can lead to slower performance for large datasets. Also, it modifies the original array. 2. **Spread Sort**: `[...a].sort()` * This approach uses the spread operator (`[...]`) to create a new array from the existing one, followed by the regular `sort()` method. * Pros: Does not modify the original array and can be more memory-efficient than slice sort. * Cons: Creates an additional object in memory, which can lead to slower performance for large datasets. Also, it may incur a higher overhead due to the spread operator. 3. **Regular Sort**: `a.sort()` * This approach uses only the regular `sort()` method without any modifications or creations of new arrays. * Pros: Typically the most efficient and well-tested algorithm for sorting arrays in JavaScript. * Cons: May not have good cache locality, especially for large datasets, due to the overhead of comparing elements during the sort process. 4. **Structured Sort**: `structuredClone(a).sort()` * This approach uses the `structuredClone` function (introduced in ECMAScript 2022) to create a deep clone of the array, followed by the regular `sort()` method. * Pros: Preserves the original array and avoids potential issues with array modification or creation. * Cons: Can be slower due to the overhead of cloning the entire array. Additionally, it may not be supported in older browsers. **Library and Special JS Features** The `structuredClone` function is a new feature introduced in ECMAScript 2022, which allows for creating deep clones of objects and arrays while preserving their properties and structure. **Alternatives** Other sorting algorithms that could be compared in this benchmark include: 1. **Quicksort**: A fast and efficient algorithm with an average time complexity of O(n log n), but can have poor performance on certain input datasets. 2. **Merge Sort**: Another efficient algorithm with a time complexity of O(n log n), but may have higher overhead due to the merge operation. 3. **Radix Sort**: A non-comparative sorting algorithm suitable for large datasets, but may not be as widely supported in JavaScript environments. Keep in mind that this is just a selection of alternatives, and there are many other sorting algorithms with varying trade-offs between performance, memory usage, and complexity.
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