Benchmark: Clean up strategy test

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

var i = 0, MAX_SIZE = 10, a;
var loop = 100
var map = new Map();

for (i = 0; i < MAX_SIZE; i++) {
    map.set(i, i);
}

Tests:

Clean by half
/*When writing async/deferred tests, use `deferred.resolve()` to mark test as done*/ for (i = MAX_SIZE; i < loop; i++) { map.set(i, i); if (map.size >= MAX_SIZE) { let count = MAX_SIZE / 2; for (const key of map.keys()) { map.delete(key); count--; if (count <= 0) { break; } } } }
Clean one by one
/*When writing async/deferred tests, use `deferred.resolve()` to mark test as done*/ for (i = MAX_SIZE; i < loop; i++) { map.set(i, i); if (map.size >= MAX_SIZE) { const firstKeyIt = map.keys().next() if(!firstKeyIt.done) { map.delete(firstKeyIt.value) } } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Clean by half
Clean one by one

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36

Browser/OS: Chrome 133 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Clean by half	185287.8 Ops/sec
Clean one by one	129700.4 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 2 months ago):

LLMs can make mistakes. Check important info.

The benchmark you provided focuses on comparing two different strategies for cleaning up entries in a JavaScript `Map` data structure. The benchmark tests are designed to analyze the performance of two specific deletion methods for entries in the `Map` and measure how many operations can be executed per second.

### Benchmark Overview
- **Test Strategies**:
  1. **Clean by half**: This strategy attempts to delete half of the entries in the map each time the number of entries meets or exceeds a maximum size.
  2. **Clean one by one**: This strategy deletes only one entry from the map when the maximum size is reached, specifically the first entry according to the insertion order.

### Pros and Cons of Each Approach

#### Clean by half
- **Pros**:
  - More efficient in terms of the number of deletions performed in each iteration since it removes multiple entries at once. This can lead to better performance, especially when a large number of entries needs to be removed.
  - Makes use of the map's inherent properties, potentially reducing the number of iterations needed in the loop.

- **Cons**:
  - May lead to more complex code, particularly in cases where the conditions surrounding deletion need to be managed carefully (e.g., keeping track of the count).
  - If the map contains many entries and only a few need to be deleted, this method may be overkill and not optimal in terms of time/space complexity.

#### Clean one by one
- **Pros**:
  - Simpler implementation, easy to understand and follow. It focuses on a single entry removal, which can be clearer from a logic standpoint.
  - Reduces the likelihood of dealing with edge cases involving multiple deletions and complex condition checks.

- **Cons**:
  - Less efficient, especially when a lot of entries need to be deleted. This method may lead to a higher execution time since it might involve multiple separate deletion operations instead of a single large batch operation.
  - Can result in slower performance as the size of the `Map` grows and if many entries above the maximum size threshold are present.

### Alternatives
- **Bulk Deletion**: Some libraries might have functions that allow bulk deletion based on certain criteria, offering a middle ground between complex manual deletion strategies and one-by-one deletes.
- **Using Arrays**: If order does not matter as much, alternatives like arrays or objects could be utilized with different cleaning algorithms, like filter-based approaches. This may provide different performance characteristics.
- **Different Data Structures**: Depending on the use case, exploring other data structures like Sets or even custom implementations may yield better performance for specific types of data management.

### Libraries and Tools
The benchmark in this context uses native JavaScript features (i.e., `Map`, `for` loops) without relying on any additional libraries. The purpose of the `Map` data structure is to provide an efficient way to store key-value pairs where both keys and values can be of any type, for quick retrieval and manipulation.

Overall, this benchmark illustrates the trade-offs between batch and individual processing strategies using JavaScript's `Map`, enabling software engineers to choose the approach that best fits their performance and complexity needs based on the specific context.

Related benchmarks:

Clean up strategy test (version: 1)

Comparing performance of: Clean by half vs Clean one by one

Created: 2 months ago by: Guest

Jump to the latest result

Clean by half

Clean one by one

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 2 months ago):