Benchmark: Nested tenary vs dictionary 2

Script Preparation code:

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

Tests:

Tenary
const status_ = random === 0 ? -Math.PI: 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, }; const status2_ = 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

Autogenerated LLM Summary (model llama3.1:latest, generated one month ago):

LLMs can make mistakes. Check important info.

Let's dive into the details of this benchmark test.

**Benchmark Definition**

The benchmark is called "Nested tenary vs dictionary 2". It compares two approaches to determine the value of `status_` based on a randomly generated number between 0 and 20. The goal is to see which approach performs better in terms of execution speed.

**Test Cases**

There are two test cases:

1. **Ternary Operator ("Tenary")**: This test uses the ternary operator (also known as the conditional expression) to assign a value to `status_` based on the random number.
2. **Dictionary Lookup ("Dictionary")**: This test uses an object (`test`) to map numbers to their corresponding values, and then looks up the value in this object using the random number as the key.

**Script Preparation Code**

The script preparation code is a JavaScript snippet that generates a random number between 0 and 20. This number will be used to determine which value to assign to `status_` in each test case.

**Library/Feature Used**

No external libraries or special JavaScript features are used in this benchmark.

**What's Being Tested**

The main difference between the two approaches is how they determine the value of `status_`. The ternary operator approach uses a chain of conditional expressions, while the dictionary lookup approach uses an object to map numbers to values. This benchmark measures which approach is faster when executed repeatedly.

**Pros and Cons**

* **Ternary Operator**: Pros:
	+ Easy to read and write.
	+ No overhead from creating an object.
*   Con: Can become cumbersome for large numbers of conditions.
* **Dictionary Lookup**: Pros:
	+ Efficient lookup times for large datasets.
	+ Easy to add or remove values without changing the existing code.
*   Con: Creates an extra object in memory.

**Other Considerations**

* **Cache Performance**: The dictionary lookup approach may benefit from cache performance, as the object is likely to be cached by the browser.
* **Overhead of Object Creation**: While the dictionary lookup approach creates an object, this overhead is minimal compared to the benefits of fast lookups for large datasets.

**Alternatives**

Other alternatives could be:

1. **Switch Statement**: A switch statement can be used instead of a ternary operator or dictionary lookup, especially when dealing with a small number of cases.
2. **Function Lookup**: Instead of using an object, you could create functions that return the corresponding values based on the input.

Keep in mind that the best approach depends on your specific use case and requirements.

Now, let's summarize the benchmark results:

* The dictionary lookup approach ("Dictionary") performed better than the ternary operator approach ("Tenary") in this test.
* The "Dictionary" test had an execution speed of approximately 2.5 million executions per second.
* The "Ternary" test had an execution speed of around 1.14 million executions per second.

This result suggests that using a dictionary lookup can lead to faster execution times, especially when dealing with large datasets or complex conditional logic. However, the best approach ultimately depends on your specific use case and requirements.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36

Browser/OS: Chrome 108 on Windows

View result in a separate tab

Test name	Executions per second
Tenary	1142082.2 Ops/sec
Dictionary	2788641.8 Ops/sec

Related benchmarks:

Nested tenary vs dictionary 2 (version: 0)

Comparing performance of: Tenary vs Dictionary

Created: one year ago by: Guest

Jump to the latest result

Tenary

Dictionary

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.1:latest, generated one month ago):