Benchmark: Jewels And Stones Leetcode

Tests:

for of loop
function findJewels (jewels, stones) { // iterate through our stones.. if it is a jewel, increment let count = 0; for (const char of stones) { if (jewels.includes(char)) count++; } return count; }; for (i = 0; i < 10; i++) { console.log(findJewels("aA", "aAAbbbb"), "3"); console.log(findJewels("z", "ZZ"), "0"); }
hashmap
function findJewels(jewels, stones) { const map = {}; let count = 0; for (const jewel of jewels) { map[jewel] = true; } for (const stone of stones) { if (map[stone]) { count++; } } return count; } for (i = 0; i < 10; i++) { console.log(findJewels("aA", "aAAbbbb"), "3"); console.log(findJewels("z", "ZZ"), "0"); }
for loop
function findJewels(jewels, stones) { // declare a count & length variable let count = 0; let len = stones.length; // Iterate through the longest array stones. Increment count by 1 if it exists in jewels for (let i = 0; i < len; i++) { if (jewels.indexOf(stones[i]) >= 0) { count++; } } return count; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for of loop
hashmap
for loop

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark, titled "Jewels And Stones Leetcode," tests the performance of different approaches to solving a problem on LeetCode.

**Test Cases**

There are three test cases:

1. **For Loop**: This approach uses a traditional `for` loop to iterate through the stones array and check if each stone is present in the jewels array.
2. **Hashmap**: This approach uses a JavaScript object (HashMap) to store the jewels as keys and increment a counter for each stone that matches a jewel.
3. **For of Loop**: This approach uses the `for...of` loop to iterate through the stones array and check if each stone is present in the jewels array.

**Options Compared**

The three approaches are compared in terms of their performance, which is measured by the number of executions per second (ExecutionsPerSecond).

**Pros and Cons of Each Approach**

1. **For Loop**:
	* Pros: Simple to understand and implement.
	* Cons: May be slower than other approaches due to the overhead of checking for element presence in the `indexOf` method.
2. **Hashmap**:
	* Pros: Can be faster than traditional `for` loops, especially for large datasets, since it uses a data structure optimized for lookups.
	* Cons: Requires additional memory for storing the HashMap and may have slower initialization times.
3. **For of Loop**:
	* Pros: Similar to the traditional `for` loop approach but with improved performance due to faster iteration through the array using the `for...of` loop syntax.
	* Cons: May be less intuitive for developers without experience with this syntax.

**Other Considerations**

* The use of `console.log` statements in the benchmark definition code may introduce additional overhead and should be avoided in production code.
* The test cases do not account for edge cases, such as an empty jewels array or a stones array with duplicate elements.

**Library Used**

In the "Hashmap" test case, JavaScript object (HashMap) is used. This is a built-in data structure in JavaScript that allows for efficient storage and lookup of key-value pairs.

**Special JS Feature/Syntax**

The "For of Loop" test case uses the `for...of` loop syntax, which is a newer feature introduced in ECMAScript 2015 (ES6). This syntax provides faster iteration through arrays using iterators, which can improve performance compared to traditional `for` loops.

Related benchmarks:

Jewels And Stones Leetcode (version: 0)

https://leetcode.com/problems/jewels-and-stones/description/

Comparing performance of: for of loop vs hashmap vs for loop

Created: 3 years ago by: Registered User

Jump to the latest result

for of loop

hashmap

for loop

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):