Benchmark: IndexOfAll - Reduce vs For

HTML Preparation code:

<html>
  <head>
  	<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/3.10.1/lodash.min.js"></script>
  </head>
  <body>
  </body>
</html>

Script Preparation code:

var xpath = "sdf[ewr[dasdfdsaf]asdfasdf]gh[asdfasdf]adsdasd[asdasd]asdasdsa[asd[[[[[asdasdasd]]]]]asd]"

Tests:

Reduce
var result = _.reduce(xpath, function(accumulator, element, index) { if (element === '[') { accumulator.push({start: index}); } if (element === ']') { _.set(_.findLast(accumulator, (obj) => !obj.end), "end", index); } return accumulator; }, []);
For
var predicateMarkStack = []; var predicateMarkIndexRange = []; for (var i = 0; i < xpath.length; i++) { if (xpath.charAt(i) === "[") { predicateMarkStack.push(i); } if (xpath.charAt(i) === "]") { var index = predicateMarkStack.pop(); // if (predicateMarkStack.length === 0) { predicateMarkIndexRange.push({init: index, end: i}); // } } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce
For

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its components.

**Benchmark Overview**

The benchmark measures the performance of two approaches to find all occurrences of square brackets (`[]`) in a given string, specifically the `xpath` variable. The two approaches are:

1. Using Lodash's `reduce()` method.
2. Using a simple iterative approach (loop) without any additional library.

**Options Compared**

The benchmark compares the performance of two options:

1. **Lodash's `reduce()` method**: This option uses the `reduce()` function to iterate over the string and accumulate the indices of square brackets.
2. **Simple Iterative Approach**: This option uses a loop to manually iterate over the string, pushing indices onto an array whenever a square bracket is encountered.

**Pros and Cons**

**Lodash's `reduce()` method:**

Pros:

* Concise and readable code
* Efficient use of JavaScript's built-in data structures (arrays)

Cons:

* Requires Lodash library, which may not be included in all browsers or environments.
* May have overhead due to the creation of a new array and repeated calls to `findLast()`.

**Simple Iterative Approach:**

Pros:

* Does not require any additional libraries
* Can be more intuitive for developers familiar with JavaScript loops

Cons:

* Code can become verbose and less readable as the loop iterates over larger strings.
* May have performance overhead due to the creation of local variables and repeated function calls.

**Library Used: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for data manipulation, functional programming, and more. In this case, the `reduce()` method is used to accumulate indices in an array. The `_` variable refers to the Lodash root namespace, which contains all its functions.

**Special JS Feature/Syntax**

The benchmark does not explicitly use any special JavaScript features or syntax, such as async/await, Promises, or Generators. However, it relies on the `findLast()` function from Lodash, which may be a relatively new feature in older browsers.

**Alternative Approaches**

Other possible approaches to solve this problem could include:

* Using regular expressions (regex) with the `exec()` method to find all occurrences of square brackets.
* Utilizing a streaming approach that processes the string one character at a time.
* Implementing a hybrid approach that combines elements of both methods.

Keep in mind that each alternative approach would likely have its own pros and cons, and may require additional considerations for performance, code readability, and compatibility across different browsers and environments.

Related benchmarks:

IndexOfAll - Reduce vs For (version: 0)

Test

Comparing performance of: Reduce vs For

Created: 7 years ago by: Guest

Jump to the latest result

Reduce

For

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):