When simple TRUE / FALSE is not enough. Analyzing test results using a specialized language R
Evlampiy is responsible for testing in the company. And today, he has dropped 60% of all tests.
Onufriy is a performance specialist 90% of his tests ceased to comply with the SLA, and the overall system began to behave abnormally.
Their tests covered almost all critical cases. And they are annoyed that the tests began to return a negative result, and this can be seen on the beautiful dashboard, which shows only red circles and numbers. The dashboard doesn't show them cause and effect.
Now they need to manually examine gigabytes of data to get to the bottom of the truth that the developers did nothing.
We will consider the R language as an additional tool for analyzing big data in a simple manner. Let's run a demo of the main functions.
Let's show the capabilities of the language:
- to create complex visualizations
- to create simple APIs
- to create web applications
The audience will be able to see that understanding specialized languages is not as difficult as it seems. They will also see that creating a complex data analysis program is not more complicated than "Hello world." In the end, we will demonstrate the ability of the language to create complex web applications for data analysis using the example of analyzing the results of load tests for JMeter's logs.
- An expert in performance testing
- Creates performance tests and build processes for finding performance issues
- Mykyta helps companies to understand why their programs work slowly
- Keeps human interaction with tests to a minimum and provide developers with the fastest possible feedback after their commits
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