Benchmark: Stack Generation costs

Tests:

Try Catch Throw
try { throw new Error(`Err ${Date.now()}`); } catch (e) { console.log(e.stack); }
Console
try { console.log(`Hello World ${Date.now()}`); } catch (e) { console.log(`Bye ${Date.now()}`); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Try Catch Throw
Console

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the world of MeasureThat.net and understand what's being tested in this benchmark.

**What is being tested?**

MeasureThat.net provides a platform for users to create and run JavaScript microbenchmarks. The provided JSON represents two individual test cases, each containing a "Benchmark Definition" that defines how to measure certain aspects of JavaScript execution.

The first test case, "Try Catch Throw," measures the cost of generating stack traces using `try`-`catch` blocks with an `Error` object thrown inside. This includes factors like memory allocation, CPU usage, and overall performance impact on the engine.

The second test case, "Console," measures the cost of executing JavaScript code that logs messages to the console, including formatting strings with dates (`Date.now()`).

**Options compared**

In both cases, MeasureThat.net is comparing different approaches to measure these specific aspects. The options being compared include:

* Using `try`-`catch` blocks versus logging directly to the console
* Executing code that generates stack traces versus executing code that simply logs messages

These comparisons aim to identify which approach has a lower performance impact on the JavaScript engine.

**Pros and Cons**

When it comes to measuring the cost of generating stack traces, `try`-`catch` blocks are generally considered more efficient because they:

* Reuse existing memory allocations (stack frames)
* Avoid unnecessary CPU overhead for logging

However, this approach also has some limitations:
* It requires specific error handling logic
* May not be suitable for all use cases (e.g., when errors are explicitly thrown for debugging purposes)

Logging directly to the console can introduce additional overhead due to:

* Memory allocation and deallocation for log messages
* Potential string formatting and encoding operations

However, logging is often a common practice in JavaScript development, making this approach more convenient and widely applicable.

When it comes to measuring the cost of executing code that logs messages to the console, both approaches can introduce similar overhead due to:

* String formatting and encoding operations
* Potential console output buffer size limits

**Special JS feature**

In the "Try Catch Throw" test case, `Error` objects are used with template literals (the `$` syntax). This is a modern JavaScript feature that allows for easier string interpolation. In older browsers or environments, this might require additional configuration or polyfills.

**Library and its purpose**

There are no libraries explicitly mentioned in the provided benchmark code. However, the use of `console` implies the availability of the built-in global object in JavaScript engines.

**Other alternatives**

To measure similar aspects, developers can explore alternative approaches:

* Use a logging library like Log4j or Winston to abstract away console output and focus on performance measurement.
* Utilize profiling tools or benchmarking frameworks (e.g., Benchmark.js) that provide more comprehensive insights into JavaScript engine performance.
* Experiment with optimizing stack trace generation using specialized libraries or techniques, such as `stacktrace-js`.

Keep in mind that the choices of alternatives will depend on specific use cases, project requirements, and personal preferences.

Related benchmarks:

Stack Generation costs (version: 0)

Comparing performance of: Try Catch Throw vs Console

Created: 4 years ago by: Guest

Jump to the latest result

Try Catch Throw

Console

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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