Our algorithm can also be modified slightly to obtain a fully adaptive algorithm with sample complexity O˜(log log n).

The paper provides Proof of Claim using concentration inequality.

Acknowledgments of the research in Equivalence Testing.

The paper considered the problem of equivalence testing of two distributions (over [n]) in the conditional sampling model.

The paper provides a technical analysis of the correctness and complexity of EquivTester using COND model and equivalent distributions.

The article takes an example of an EquivTester algorithm and how to convert it into a one-round algorithm, using the COND model.

This part presents an O(log log n)-query fully adaptive algorithm. The algorithm is a one-round adaptive tester for the equivalence testing problem in the COND

This article dives into the SAMP model and the COND model in equivalence testing to find out which is the most optimal for the problem.

The research provides an affirmative answer to the challenge of equivalence testing.

The research provides an affirmative answer to the challenge of equivalence testing.