Benchmark: blackList vs regexp

Script Preparation code:

var blackList = ["cazzo","madonna","stronzo","puttana","troia","porca","dio"]
 var regexp = /^(cazzo|madonna|stronzo|puttana|troia|porca|dio)$/

Tests:

array search
var result1 = blackList.indexOf("stronzo") >= -1; var result2 = blackList.indexOf("dio") >= -1; var result3 = blackList.indexOf("Marco") >= -1;
regexp
var result1 = "stronzo".match(regexp); var result2 = "dio".match(regexp); var result3 = "Marco".match(regexp);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array search
regexp

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**What is being tested?**

The provided JSON represents two test cases: "array search" and "regexp". These test cases compare the performance of JavaScript arrays and regular expressions (regexps) in searching for specific values.

**Options compared**

In the "array search" test case, there are three operations:

1. `blackList.indexOf("stronzo") >= -1`: This operation checks if the string "stronzo" is present in the array `blackList`. If it is, the result will be a positive integer indicating the index of the element; otherwise, it will return `-1`.
2. `blackList.indexOf("dio") >= -1`
3. `blackList.indexOf("Marco") >= -1`

These operations are likely executed sequentially to find all occurrences of "stronzo" and "dio" in the array.

In the "regexp" test case, there are three operations:

1. `"stronzo".match(regexp)`: This operation checks if the string "stronzo" matches the regexp pattern defined in `regexp`.
2. `"dio".match(regexp)`
3. `"Marco".match(regexp)`

These operations are also likely executed sequentially to find all occurrences of "stro-xyz" strings matching the regexp.

**Pros and cons**

Using arrays for search:

* Pros:
	+ Fast and efficient for small datasets.
	+ Can be optimized for specific use cases (e.g., binary search).
* Cons:
	+ May not perform well for large datasets or dynamic data structures.
	+ Can be slow if the dataset is not properly indexed.

Using regexps:

* Pros:
	+ Highly flexible and powerful for pattern matching.
	+ Can handle complex regular expressions with capture groups, anchors, and more.
* Cons:
	+ Generally slower than arrays for simple searches.
	+ Can be computationally expensive due to the complexity of regexps.

**Library usage**

In this benchmark, `RegExp` is used as a library. The `RegExp` constructor is used to create the regexp pattern `regexp`. This library provides a way to define regular expression patterns and execute them against strings.

**Special JS features or syntax**

There are no special JS features or syntax mentioned in the benchmark that would require additional explanation beyond the regular expressions used.

**Other alternatives**

Some alternative approaches for searching data could include:

1. Using a `Set` data structure instead of an array, which provides faster lookup times.
2. Implementing a custom search algorithm tailored to specific use cases (e.g., binary search).
3. Using a database or external data storage solution for large datasets.

However, these alternatives would likely require significant modifications to the benchmark and might not be as straightforward to compare with arrays and regexps using MeasureThat.net.

I hope this explanation helps!

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:99.0) Gecko/20100101 Firefox/99.0

Browser/OS: Firefox 99 on Ubuntu

View result in a separate tab

Test name	Executions per second
array search	6610101.5 Ops/sec
regexp	5825087.0 Ops/sec

Related benchmarks:

blackList vs regexp (version: 0)

Comparing performance of: array search vs regexp

Created: 2 years ago by: Guest

Jump to the latest result

array search

regexp

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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