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Native Loop
(version: 0)
Comparing performance of:
for-loop (push) vs for-loop (rest params) vs Array.prototype.map()
Created:
3 years ago
by:
Registered User
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Tests:
for-loop (push)
let i = 1000 while (i--) { let arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] let mappedArr = [] for (let each of arr) { mappedArr.push(each*5) } }
for-loop (rest params)
let i = 1000 while (i--) { let arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] let mappedArr = [] for (let each of arr) { mappedArr = [...mappedArr, each*5] } }
Array.prototype.map()
let i = 1000 while (i--) { let arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] let mappedArr = arr.map(each => each * 5) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
for-loop (push)
for-loop (rest params)
Array.prototype.map()
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 break down the provided JSON benchmark definitions and explain what is tested, the options compared, pros and cons of each approach, and other considerations. **Benchmark Definition** The benchmark definition json contains only one entry with empty fields for "Script Preparation Code" and "Html Preparation Code". This suggests that the script itself is the main focus of the benchmark, and any necessary setup or cleanup code has been omitted. **Individual Test Cases** There are three test cases, each representing a different approach to perform a similar operation: 1. **for-loop (push)**: This test case uses a traditional for loop with an array index variable (`i`) that decrements on each iteration. The loop iterates over the elements of an array and pushes each element multiplied by 5 onto another array. 2. **for-loop (rest params)**: Similar to the previous test case, but this time it uses rest parameters in the for loop declaration. This allows the `each` variable to take on all the values of the array at once, without the need for an index variable. 3. **Array.prototype.map()**: This test case uses the built-in `map()` method of JavaScript arrays, which applies a transformation function to each element of the array and returns a new array with the results. **Options Compared** The three test cases compare different approaches to perform a similar operation: * **for-loop (push)**: Iterates over the elements of an array using an index variable. * **for-loop (rest params)**: Uses rest parameters to iterate over all elements of an array at once. * **Array.prototype.map()**: Applies a transformation function to each element of an array and returns a new array with the results. **Pros and Cons** Here are some pros and cons of each approach: * **for-loop (push)**: + Pros: Simple, easy to understand, and suitable for small arrays. + Cons: Can be slower than other approaches for large arrays due to the overhead of incrementing an index variable. * **for-loop (rest params)**: + Pros: More concise and expressive than traditional loops, and can handle larger arrays more efficiently. + Cons: May require additional knowledge of JavaScript features like rest parameters. * **Array.prototype.map()**: + Pros: Fast and efficient for large arrays, as it uses optimized native code. + Cons: Requires the use of the `map()` method, which may not be familiar to all developers. **Other Considerations** When choosing an approach, consider the following factors: * Array size: For small arrays, traditional loops might be sufficient. For larger arrays, rest parameters or `map()` might provide better performance. * Code readability and maintainability: Choose an approach that is easy to understand and modify. * Developer expertise: If developers are not familiar with rest parameters or `map()`, traditional loops might be more suitable. **Alternative Approaches** Other alternative approaches could include: * Using a library like Lodash, which provides a `map()` function that can handle arrays of any size. * Implementing a custom iterator or generator using JavaScript's built-in `Symbol.iterator` feature. * Utilizing parallel processing techniques to speed up the iteration over large arrays. Keep in mind that these alternatives might introduce additional complexity and overhead, so it's essential to weigh the benefits against the costs.
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