Benchmark: hgftyguhijokpl[;]

Script Preparation code:

const ALPHABET = 'abcdefghijklmnopqrstuvwxyz'
const makeSet = () => {
    const count = Math.round(Math.min(Math.random() * 4 + 1, ALPHABET.length))
    let out = []
    for (let i = 0; i < count; i++) {
        let char
        do
            char = ALPHABET[Math.floor(Math.random() * ALPHABET.length)]
        while (out.includes(char))
        out.push(char)
    }
    return out.sort().join('')
}

const shuffleSet = (set) => {
    let out = ' '.repeat(Math.round(Math.random() * (set.length * 2) + 3))
    for (const char of set) {
        const count = Math.round(Math.random() * 3 + 1)
        for (let j = 0; j < count; j++) {
            const idx = Math.floor(Math.random() * out.length)
            out = out.slice(0, idx) + char + out.slice(idx)
        }
    }

    return out
}

const makeCase = () => {
    const filler = makeSet()
    let answer
    do {
        answer = makeSet()
    } while (answer === filler)
    answer = shuffleSet(answer)
    const count = Math.random() * 6 + 4

    const input = []
    for (let i = 0; i < count; i++)
        input.push(shuffleSet(filler))
    input.splice(Math.floor(Math.random() * input.length), 0, answer)

    return { input, answer }
}

var cases = [
    makeCase(),
    makeCase(),
    makeCase(),
]

Tests:

Solution next day
function findUniq(strings) { const uniq = {} for (let i = 0; i < strings.length; i++) { const l = new Set(strings[i].replace(/\s+/g, '').toLowerCase()).size uniq[l] = !(l in uniq) ? strings[i] : null } return Object.values(uniq).find(v => v) } for (const { input, result } of cases) console.assert(findUniq(input) === result)
Solution on interview
function findUniq(strings) { const s1 = strings.map((s) => s.toLowerCase().replaceAll(/\s/g, '')) const s2 = s1.map((s) => [...new Set(s)].sort().join('')) let out = [] for (let i = 0; i < s2.length; i++) { const elm = s2[i] if (out.some((idx) => s2[idx] === elm)) out = out.filter((idx) => s2[idx] !== elm) else out.push(i) } return strings[out[0]] } for (const { input, result } of cases) console.assert(findUniq(input) === result)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Solution next day
Solution on interview

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36

Browser/OS: Chrome 128 on Linux

View result in a separate tab

Solution next day

58K/s

Solution on interview

32K/s

View exact numbers

Test name	Executions per second
✓ Solution next day	57,513 Ops/sec
Solution on interview	31,611 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The benchmark you provided tests the performance of two different solutions for finding the unique string in an array.

**Benchmark Definition**

The first test case, "Solution next day," uses a simple approach to find the unique string. It creates a set of strings where each string is converted to lowercase and whitespace characters are removed using a regular expression. The set is then used to find the unique string by iterating through its elements and returning the one that is not present in any other element.

The second test case, "Solution on interview," uses a more complex approach. It first converts each string to lowercase and removes whitespace characters. Then, it sorts the resulting strings using a set, which automatically removes duplicates. The sorted strings are used to find the unique string by filtering out elements that have already been found.

**Options Compared**

The two solutions compared in this benchmark are:

1. **Solution next day**: This solution uses a simple approach with a time complexity of O(n^2), where n is the number of elements in the input array.
2. **Solution on interview**: This solution uses a more complex approach with a time complexity of O(n log n), where n is the number of elements in the input array.

**Pros and Cons**

**Solution next day**:

Pros:

* Simple to implement
* Easy to understand

Cons:

* Time complexity is O(n^2), which can be slow for large inputs
* Not suitable for production use due to its high time complexity

**Solution on interview**:

Pros:

* Time complexity is O(n log n), which is faster than the first solution
* Uses sets and sorting, which are efficient data structures

Cons:

* More complex to implement
* Requires understanding of set operations and sorting algorithms

**Other Considerations**

Both solutions have their trade-offs. The "Solution next day" is simpler to understand but has a higher time complexity, while the "Solution on interview" is more complex to implement but has a lower time complexity.

**Libraries Used**

The benchmark uses the following library:

* None (built-in JavaScript functions and data structures)

**Special JS Features or Syntax**

There are no special JS features or syntax used in this benchmark.

**Alternatives**

If you need to find the unique string in an array, there are other approaches you can take. Some alternatives include:

1. **Using a map**: You can create a map where each key is a hash of the string and the value is the original string. This approach has a time complexity of O(n) but requires more memory.
2. **Using a trie**: A trie is a data structure that allows you to efficiently search for strings. You can use a trie to find the unique string in an array with a time complexity of O(m), where m is the length of the longest string.
3. **Using a hash table**: Similar to using a map, you can create a hash table to store the strings and then iterate through it to find the unique string.

These alternatives may offer better performance or more efficient memory usage, but they also require more expertise in JavaScript data structures and algorithms.

hgftyguhijokpl[;] (version: 0)

Comparing performance of: `Solution next day vs Solution on interview`

Created: one year ago by: Guest

Go to the latest result

Solution next day

Solution on interview

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

hgftyguhijokpl[;] (version: 0)

Comparing performance of: Solution next day vs Solution on interview

Created: one year ago by: Guest

Go to the latest result

Solution next day

Solution on interview

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Comparing performance of: `Solution next day vs Solution on interview`