Benchmark: testot - MeasureThat.net

Tests:

func1
function func1(level = 25) { const BaseATK = 30 let UpdateATK if (level >= 0 && level <= 2) { UpdateATK = BaseATK + (level * 5); } else if (level >= 3 && level <= 7) { UpdateATK = (BaseATK - 1) + (level * 5); } else if (level >= 8 && level <= 12) { UpdateATK = (BaseATK - 2) + (level * 5); } else if (level >= 13 && level <= 17) { UpdateATK = (BaseATK - 3) + (level * 5); } else if (level >= 18 && level <= 22) { UpdateATK = (BaseATK - 4) + (level * 5); } else if (level >= 23 && level <= 25) { UpdateATK = (BaseATK - 5) + (level * 5) } return UpdateATK }
func2
function func2(level = 25, rank = 0) { const BaseATK = 30 + rank * 2; const offset = Math.floor(level / 5); return BaseATK - offset + level * 5; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
func1
func2

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Android

View result in a separate tab

Test name	Executions per second
func1	40473596.0 Ops/sec
func2	40919312.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):

LLMs can make mistakes. Check important info.

The benchmark outlined tests two different functions, `func1` and `func2`, both of which calculate an updated attack power based on character level, with `func2` additionally considering a rank parameter. The primary focus of this benchmark is to compare the performance of two distinct approaches to achieving the same goal.

### Function Analyses

1. **func1**
   - **Implementation**: The function checks the provided `level` argument against a series of ranges to determine the appropriate value for `UpdateATK`. This is accomplished through multiple conditional checks (if-else statements).
   - **Performance Consideration**: The use of multiple conditional checks may lead to an increased execution time when the function is called with various level values, as the function's complexity is linear relative to the number of conditions checked.
   - **Pros**: Simple and straightforward, easy to follow and understand, explicitly maps various ranges to specific updates.
   - **Cons**: Performance may degrade with many level values, and the logic could become cumbersome if more ranges are added; it might be prone to errors in maintenance and readability due to its verbosity.

2. **func2**
   - **Implementation**: This function utilizes arithmetic calculations instead of conditional checks. It calculates `BaseATK` in relation to the `rank`, and derives an offset based on the `level` divided by five, combining these in a single arithmetic return statement.
   - **Performance Consideration**: The computational complexity is constant (O(1)), meaning it executes in the same time regardless of the input level as it relies solely on arithmetic operations.
   - **Pros**: More efficient with fewer lines of code, more maintainable and easily extendable for future modifications, clearer logic that relies on mathematical relationships rather than multiple branching conditions.
   - **Cons**: Slightly less explicit than `func1` about how the values are determined, which may affect readability for less experienced developers.

### Benchmark Findings

From the provided results, `func2` exhibits a higher performance than `func1`, with `40919312` executions per second compared to `40473596` for `func1`. This difference indicates that the arithmetic-based approach in `func2` is more efficient than the conditional-based approach in `func1`.

### Alternatives

1. **Switch Statement Implementation**: One alternative to function `func1` could be a `switch` statement instead of multiple `if-else` conditions. While still conditional, `switch` can simplify some logic and improve readability.

2. **Lookup Tables**: For cases like `func1`, using a lookup table (an array or object mapping levels to attack values) could enhance performance and simplify the conditional logic by eliminating branching entirely.

3. **Dynamic Calculations**: Instead of hardcoding certain values like base attack increases for specific ranges, an alternative design could leverage more dynamic approaches with formulas to compute these values based on user-defined inputs.

### Conclusion

In summary, the benchmark results indicate that, for this specific problem, utilizing arithmetic operations (as seen in `func2`) yields a more performant solution than using conditional logic (as seen in `func1`). Developers must weigh the priorities of clarity and maintainability against execution speed, particularly in scenarios where performance may significantly impact overall application efficiency.

Related benchmarks:

testot (version: 1)

Comparing performance of: func1 vs func2

Created: one month ago by: Registered User

Jump to the latest result

func1

func2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):