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twoSum test
(version: 0)
Comparing performance of:
twoSum1 vs twoSum2
Created:
6 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
// Naive appraoch - O(n^2) function twoSum1(arr, target) { for (let i = 0; i < arr.length; i++) { // for every integer of the array for (let j = i + 1; j < arr.length; j++) { // go through every integer after it and check the sum if (arr[i] + arr[j] === target) return true; } } return false; } // Using set - O(n) function twoSum2(arr, target) { // set to store difference of target and element const diffs = new Set(); // iterate through array for (let element of arr) { // current element exists in diffs, we saw its complement before if (diffs.has(element)) return true; // otherwise add the complement to the diffs else diffs.add(target - element); } // target sum not found return false; }
Tests:
twoSum1
const testArr = []; for (let i = 0; i < 10000; i++) { testArr.push(i); } twoSum1(testArr)
twoSum2
const testArr = []; for (let i = 0; i < 10000; i++) { testArr.push(i); } twoSum2(testArr)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
twoSum1
twoSum2
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the benchmark definition and test cases to understand what's being tested. **Benchmark Definition** The benchmark is for two implementations of the `twoSum` function, which takes an array of numbers and a target sum as input, and returns `true` if there are two elements in the array that add up to the target sum, and `false` otherwise. The two implementations are: 1. **Naive Approach**: This implementation has a time complexity of O(n^2), where n is the length of the array. It uses two nested loops to iterate through the array, comparing each element with every other element. 2. **Using Set**: This implementation has a time complexity of O(n), where n is the length of the array. It uses a `Set` data structure to store the differences between the target sum and each element in the array. **Options Compared** The two implementations are compared in terms of their performance, specifically: * Time complexity: O(n^2) vs O(n) * Number of iterations: Naive Approach (n^2) vs Using Set (n) **Pros and Cons** 1. **Naive Approach**: * Pros: Easy to understand and implement * Cons: Slow due to its high time complexity * Use case: This approach might be suitable for small arrays or educational purposes. 2. **Using Set**: * Pros: Fast due to its efficient use of the `Set` data structure * Cons: Requires additional memory to store the set, and may have higher overhead due to hash table operations **Library Used** The `Set` data structure is used in the "Using Set" implementation. A `Set` is a collection of unique values, which can be used to store the differences between the target sum and each element in the array. **Special JS Feature or Syntax** None mentioned in this benchmark definition. **Other Alternatives** If you want to optimize the `twoSum` function further, you could consider using other approaches such as: * Hash table-based approach (similar to "Using Set", but with a hash table instead of a set) * Sorting and binary search approach * Using a more efficient data structure like a trie or a prefix tree Keep in mind that the choice of implementation will depend on the specific requirements of your use case, such as performance, memory usage, and development time.
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