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array vs set 2
(version: 0)
Comparing performance of:
Test1 vs Test2
Created:
5 years ago
by:
Guest
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Tests:
Test1
const blocks = [1,2,3,4,5] const remotes = [[1,2],[1,2],[2,3],[5],[5]] let relatedBlocks = [] remotes.forEach(ids => { ids.forEach(blockId => ids.includes(blockId) || relatedBlocks.push(blockId)) }) console.log(relatedBlocks)
Test2
const blocks = [1,2,3,4,5] const remotes = [[1,2],[1,2],[2,3],[5],[5]] let relatedBlocks = new Set() remotes.forEach(ids => { ids.forEach(blockId => relatedBlocks.add(blockId)) }) console.log(...relatedBlocks)
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Suite status:
<idle, ready to run>
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Test case name
Result
Test1
Test2
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to explain what's being tested in this benchmark. **What is being tested?** This benchmark is comparing two approaches to find related elements in an array: using an explicit loop with nested `includes()` method, and using a `Set` data structure. The test case contains two JavaScript functions: 1. The first function uses an explicit loop to iterate over the `remotes` array, and for each inner array, it iterates over its elements using another loop. For each element, it checks if the element is present in the original `blocks` array using the `includes()` method, and if not, it adds the element to a new array called `relatedBlocks`. 2. The second function uses a `Set` data structure to store unique elements. It creates an empty set, and then iterates over the `remotes` array, adding each element to the set using the `add()` method. **Options compared** The two options being compared are: 1. **Explicit loop with nested includes()**: This approach uses a traditional loop-based approach to find related elements. 2. **Set data structure**: This approach uses a data structure specifically designed for storing unique elements to efficiently find related elements. **Pros and cons of each approach** * **Explicit loop with nested includes()**: + Pros: Easy to understand, no additional dependencies required. + Cons: Can be slow due to the nested loops, may not perform well for large datasets. * **Set data structure**: + Pros: Efficiently handles duplicate elements, fast lookup times. + Cons: Requires additional dependency (the `Set` class), can be less intuitive for developers without experience with sets. **Library and syntax used** In the first test case, the `includes()` method is used to check if an element is present in an array. This method is a part of the standard JavaScript API. The second test case uses a `Set` data structure, which is also part of the standard JavaScript API. The `add()` and `forEach()` methods are used to manipulate the set. **Special JS feature or syntax** None of the code snippets use any special JavaScript features or syntax that would require specific knowledge to understand. **Other alternatives** If the author wanted to compare other approaches, they could have included additional test cases, such as: * Using a `Map` data structure instead of a `Set` * Using a library like Lodash or Ramda for set operations * Using a different algorithm for finding related elements (e.g. using a hash table) * Using a different programming language or virtual machine However, the current benchmark is focused on comparing two basic approaches to find related elements in an array: using an explicit loop with nested `includes()` method, and using a `Set` data structure.
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