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AI coding benchmark set (with scoring scripts)

Problem set · scoring scripts · regression comparison

Approach

Buckets by ability (strings, collections, edge cases, performance); each problem gets visible and hidden cases. The scorer reports pass rate, runtime and a distribution of failure reasons.

Implementation

Failures are classified by assertion type, which separates misunderstanding from bad implementation; results go to JSON so repeated runs can be compared as trends.

One set compares across models and versions; in regressions, look at the failure spread before the total.

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