Benchmark: gfhg hgfh hgfdhgf gfdh hfdghgh

Tests:

obj
let obj={} for(let i=0;i<5000;i++){ obj[i]=i }
map
let map=new Map(); for(let i=0;i<5000;i++){ map.set(i,i) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
obj
map

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 113 on Android 6.0

View result in a separate tab

Test name	Executions per second
obj	24644.5 Ops/sec
map	6596.9 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what's being tested on MeasureThat.net.

**Benchmark Definition**

The benchmark definition is not actually defined in this case, as it was omitted from the provided code snippet. However, based on the two test cases that follow, we can infer what's being measured.

Two types of data structures are compared:

1. **Objects**: The first test case measures the performance of creating and populating an object with 5000 properties using a simple loop.
2. **Maps**: The second test case measures the performance of creating and populating a Map with 5000 key-value pairs using a similar approach.

**Options Compared**

The benchmark compares two approaches:

1. **Objects**: A traditional JavaScript object is used to store data, which may lead to slower execution due to overheads like property lookup, coercion, and potential caching issues.
2. **Maps**: A Map is used instead of an object, which provides faster lookups, insertion, and deletion operations. Maps are designed for key-value pairs, making them a good choice for this type of benchmark.

**Pros and Cons**

**Objects:**

Pros:

* Familiarity and ease of use
* Wide adoption and compatibility

Cons:

* Potential performance overhead due to property lookup, coercion, and caching issues

**Maps:**

Pros:

* Faster lookups, insertion, and deletion operations
* Optimized for key-value pairs

Cons:

* Smaller browser support ( older browsers might not support Maps)
* Might be less familiar to some developers

**Other Considerations**

When choosing between objects and maps, consider the specific use case and requirements. If you need fast lookups, insertion, or deletion operations, a map is likely a better choice. However, if you're working with complex data structures that require more control over property access or manipulation, an object might be more suitable.

**Libraries Used**

None are explicitly mentioned in the provided code snippets.

**Special JS Features/Syntax**

There doesn't appear to be any special JavaScript features or syntax used in these benchmarks. The tests only rely on basic JavaScript constructs like loops and data structures.

**Alternatives**

Other alternatives for measuring performance comparisons include:

1. **Array**: Using arrays instead of objects or maps could provide similar results, but might not accurately represent real-world scenarios.
2. **Sets**: Similar to Maps, Sets can be used for fast lookups and insertion operations, making them a potential alternative.
3. **Custom data structures**: Depending on the specific requirements, custom data structures like binary search trees or hash tables might be more suitable than objects or maps.

Keep in mind that the choice of benchmarking library or framework ultimately depends on the specific use case and goals of the project.

Related benchmarks:

gfhg hgfh hgfdhgf gfdh hfdghgh (version: 0)

Comparing performance of: obj vs map

Created: one year ago by: Guest

Jump to the latest result

obj

map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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