Benchmark Overview

The benchmark titled "Checking array equality" is designed to evaluate the performance of two functions that check whether two arrays of random strings are equal or not. The tests focus on comparing different array sizes and configurations to understand how the implementation performs under varying conditions.

Benchmark Processes and Options

1. Random String Generation:
   The benchmark begins by generating arrays of random strings using the generateRandomStrings function. This function creates an array of a specified length, generating strings of a specified length composed of alphanumeric characters.

   • Parameters:
     • count: Number of strings to generate.
     • length: Length of each string.
   • Library Used: Lodash is included in the benchmark via a script link. It provides utility functions, one of which used here is _.isEqual for deep comparison, and _.sortBy for sorting the arrays.

2. Array Comparison:
   The method arraysEqualBySorting checks whether two arrays are equal by:

   • Sorting both arrays and then comparing them.
   • Utilizing Lodash's _.isEqual to determine equality after sorting.
   • This approach entails two primary operations:
     • Sorting the arrays, which has a time complexity of O(n log n).
     • Comparing the arrays element-wise, which has a time complexity of O(n).

Test Cases

The benchmark runs the following scenarios:

1. With 10000:
   Compares two arrays of 10,000 random strings of 32 characters each.

   • Pros: Suitable for a basic performance comparison.
   • Cons: Smaller datasets may not highlight scalability issues.

2. With 100000 and same arrays:
   Compares two identical arrays of 100,000 random strings, both 32 characters long.

   • Pros: Testing with identical arrays rapidly checks equality without the need for sorting the second array.
   • Cons: Does not expose performance issues that arise from differences in array contents.

3. With 100000:
   Similar to the first test, but working with 100,000 random strings to evaluate the function's performance on larger datasets.

   • Pros: Helps reveal the scalability of the sorting and comparison operation.
   • Cons: Like the previous tests, could be affected by JS engine optimizations for certain patterns.

4. With 100000 and 128 strings:
   This tests the performance of comparing two arrays of 100,000 strings where each string is 128 characters long.

   • Pros: More complex data structure, simulating real-world scenarios with potentially larger string data.
   • Cons: Increased string length may change performance characteristics compared to shorter strings.

Results

The benchmark results yield ExecutionsPerSecond metrics for each case, presenting a clear picture of how performance scales based on data size and complexity:

• Comparing 10,000 strings yielded the best performance, with nearly 27 executions per second.
• The case with 100,000 identical arrays performed decently, indicating that solid equal checks were done efficiently for identical arrays.
• The direct comparisons of 100,000 random strings and the longer 128-character strings saw significant drops in performance, illustrating the impact of the extra computations required for sorting longer strings.

Pros & Cons of the Approach

Pros:

• Clarity: The benchmark offers a straightforward way to measure how array size and string length affect performance.
• Flexibility: Various scenarios allow understanding of performance under different conditions.

Cons:

• Non-Inclusive: Only one method of equality (sorting) is tested; alternatives such as hash-based comparisons could differ in performance.
• Library Dependence: Usage of Lodash adds overhead and could skew pure JS performance measurements.

Alternatives

Other potential approaches to comparing array equality include:

• Hashing Method: Creating checksums or hashes of the arrays and comparing these values can be more efficient for larger datasets.
• Direct Comparison: A simple loop that checks the content of each element without sorting would have linear complexity O(n) but may assume arrays are ordered identically.
• Typed Arrays: If dealing with specific data types, using Typed Arrays for performance-sensitive applications might yield better results.

In conclusion, this benchmark serves as an effective tool for understanding some common performance pitfalls in array comparisons in JavaScript, offering insights into how algorithmic complexity can affect runtime efficiency.