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SCIENCE

The science behind HackerEarth Assessments

The developer recruitment process involves both technical and non-technical folks, so a lot gets lost in translation. That’s why our coding tests are designed to be accurate, valid, reliable, fair and exhaustive.

Valid

Valid

We curate highly accurate skill-wise assessments for each job role

Exhaustive

Exhaustive

Our tests assess each and every skill relevant to the job role

Reliable

Reliable

ML-backed reliability models ensure that our tests are accurate

Fair

Fair

We guarantee bias-free evaluation with purely skill-based assessments

Hire developers the scientifically sound way

We believe that all our users should have complete visibility and control over the tests created on our platform. That’s why we ensure that all our users have the freedom to tune their tests to exactly the configuration they need. Here is how we achieve this.

Test reliability scores

Every test that you create comes with a reliability score. This score is a result of our question library and tests being validated by 3 separate groups: the Reference Group, the Sample Group, and the Target Group.

Reliability scores
Test difficulty indicators

Test difficulty indicators

Our platform gives you the ability to rank questions against a global benchmark. In other words, we help you understand how difficult your test is, in comparison to the tests created by everyone else that uses the platform.

Exhaustive coding tests

Thanks to our question bank of 13,000+ validated questions, you can be sure that a HackerEarth coding test is well and truly holistic. In other words, our tests cover all bases and ensure a holistic evaluation of every candidate.

Exhaustive coding tests
Drill-down performance analytics

Drill-down performance analytics

Our test engine gives you a look at the more granular details of a candidate’s abilities by letting you analyze the finer aspects of their performance, such as individual questions or code quality, and comparing it to other candidates that take similar tests.

Biased towards being unbiased

An adverse impact study of HackerEarth assessments revealed that our tests do not carry any implicit biases. The test revealed that there were no statistically significant differences in test performances between test takers of different genders, ages, pedigree or ethnicity.

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