Benchmark: Tenary vs dictionary

Script Preparation code:

var random = Math.floor(Math.random() * 20);

Tests:

Tenary
const status = random === 0 ? -Math.PI: random === 1 ? Math.EPSILON: random === 1 ? Math.EPSILON: random === 2 ? 1: random === 3 ? 1: random === 4 ? 1: random === 5 ? 1: random === 6 ? 1: random === 7 ? 1: random === 8 ? 1: random === 9 ? 1: random === 18 ? 5: random === 19 ? 28: random === 20 ? 0: -1;
Dictionary
const test = { 0: -Math.PI, 1: Math.EPSILON, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1, 18: 5, 19: 28, 20: 0, }; random = test[random] || -1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Tenary
Dictionary

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases, explaining what's being tested, compared, and the pros/cons of each approach.

**Benchmark Definition**

The benchmark definition is a JSON object that contains metadata about the benchmark. In this case:

* `Name`: The name of the benchmark, which is "Tenary vs dictionary".
* `Description`: No description is provided.
* `Script Preparation Code`:
	+ This code snippet prepares the script environment by generating a random number between 0 and 20 using `Math.floor(Math.random() * 20)`.
	+ This code is executed before running each test case.
* `Html Preparation Code`: No HTML preparation code is provided.

**Individual Test Cases**

There are two test cases:

1. **Tenary**
	* The benchmark definition is a JavaScript expression that uses the ternary operator (`?:`) to evaluate the value of `random`. Depending on its value, it returns one of several pre-defined values.
2. **Dictionary**
	* The benchmark definition is an object literal (`{ ... }`) that maps the randomly generated number `random` to a specific value from another object. If `random` is not found in the dictionary, it defaults to `-1`.
3. **Test Name**: Each test case has a corresponding name: "Tenary" and "Dictionary".

**What's being tested?**

Both test cases aim to measure the performance difference between using the ternary operator (`?:`) and accessing values from an object (`dictionary`).

**Options compared**

* **Ternary Operator (?:)**:
	+ Pros:
		- Simple and concise syntax.
		- Fast execution, as it only requires a single evaluation of the expression.
	+ Cons:
		- May lead to slower performance due to the overhead of evaluating multiple conditions.
* **Object Lookup (`dictionary`)**:
	+ Pros:
		- Can be faster for large numbers of values in the dictionary, as lookup operations are optimized.
	+ Cons:
		- Requires additional memory allocation and indexing to store the dictionary, which can lead to slower performance if not used efficiently.

**Library and purpose**

The `Math.EPSILON` constant is a built-in JavaScript value that represents a small positive or negative number, close to but less than 1. In this benchmark, it's likely used as a sentinel value to differentiate between two cases.

There are no external libraries mentioned in the benchmark definition.

**Special JS features and syntax**

The ternary operator (`?:`) is a standard JavaScript feature that allows for concise expression evaluation. However, its performance can be affected by the number of conditions being evaluated.

No special JavaScript features or syntax (e.g., ES6+ features) are used in this benchmark.

**Other alternatives**

To compare the performance of these two approaches, you could consider the following alternatives:

* **Switch statement**: Instead of using an object lookup, you could use a switch statement to evaluate the `random` value. This would require more code and might lead to slower performance due to the overhead of branching.
* **Array indexing**: If the values in the dictionary are stored in an array, you could use array indexing to access them instead of object lookups. This would require additional memory allocation and indexing but might be faster for large arrays.

Keep in mind that these alternatives can introduce additional complexity and may not accurately reflect real-world performance scenarios.

Related benchmarks:

Tenary vs dictionary (version: 0)

Comparing performance of: Tenary vs Dictionary

Created: 3 years ago by: Guest

Jump to the latest result

Tenary

Dictionary

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):