# An Adaptivity Hierarchy Theorem for Property Testing

## TL;DR

This paper establishes a hierarchy in property testing showing that the power of algorithms increases smoothly with the number of adaptive rounds, with specific properties requiring more adaptivity for efficient testing.

## Contribution

The paper proves an adaptivity hierarchy theorem for property testing, demonstrating a gradual increase in testing power with more adaptive rounds, including natural graph properties.

## Key findings

- Existence of properties with exponential gaps between adaptive and non-adaptive testing
- Construction of properties requiring more adaptivity for efficient testing
- Hierarchy demonstrated for natural graph properties

## Abstract

Adaptivity is known to play a crucial role in property testing. In particular, there exist properties for which there is an exponential gap between the power of \emph{adaptive} testing algorithms, wherein each query may be determined by the answers received to prior queries, and their \emph{non-adaptive} counterparts, in which all queries are independent of answers obtained from previous queries. In this work, we investigate the role of adaptivity in property testing at a finer level. We first quantify the degree of adaptivity of a testing algorithm by considering the number of "rounds of adaptivity" it uses. More accurately, we say that a tester is $k$-(round) adaptive if it makes queries in $k+1$ rounds, where the queries in the $i$'th round may depend on the answers obtained in the previous $i-1$ rounds. Then, we ask the following question: Does the power of testing algorithms smoothly grow with the number of rounds of adaptivity? We provide a positive answer to the foregoing question by proving an adaptivity hierarchy theorem for property testing. Specifically, our main result shows that for every $n\in \mathbb{N}$ and $0 \le k \le n^{0.99}$ there exists a property $\mathcal{P}_{n,k}$ of functions for which (1) there exists a $k$-adaptive tester for $\mathcal{P}_{n,k}$ with query complexity $\tilde{O}(k)$, yet (2) any $(k-1)$-adaptive tester for $\mathcal{P}_{n,k}$ must make $\Omega(n)$ queries. In addition, we show that such a qualitative adaptivity hierarchy can be witnessed for testing natural properties of graphs.