RANDOM-APPROX 2013 saw a bunch of property testing talks.

**An optimal lower bound for monotonicity testing over hypergrids **(Deeparnab Chakrabarty and C. Seshadhri). I talked about a lower bound for monotonicity testing over hypergrids. Given a function \(f:[n]^d \rightarrow \mathbb{N}\), we wish to test if \(f\) is monotone with respect to the coordinate-wise partial order. We proved a adaptive, two-sided \(\Omega(\varepsilon^{-1} d\log n)\) lower bound, matching recent upper bounds.

**Testing Membership in Counter Automaton Languages** (Yonatan Goldhirsh and Michael Viderman). In a seminal result, Alon, Krivelevich, Newman, and Szegedy proved that membership in regular languages is testable in constant queries. Can we extend this to richer languages? Lachish and Newman proved that membership in languages given by a pushdown automaton with a single stack symbol (a counter automaton) is not testable with constant queries. Yonathan talked about a weaker version of counter automata, for which membership is testable in constant queries.

**Tight lower bounds for testing linear isomorphism** (Elena Grigorescu, Karl Wimmer and Ning Xie). Understanding testability of functions that exhibit symmetries (like linear invariances) is an important program in property testing. A function \(f : \{0, 1\}^n \rightarrow \{0, 1\}\) is linear isomorphic to a \(g\) if \(f = g \circ A\), for non-singular transformation \(A\). Ning talked about a lower bound of \(\Omega(n^2)\) for testing if a function is linear isomorphic to the inner product function. (This is tight, as a simple algorithm shows.) In other words, consider the property of functions linear isomorphic to the inner product. This property is *not* testable in constant queries, suggesting that symmetries themselves do not suffice for (constant) testability.

**Local reconstructors and tolerant testers for connectivity and diameter** (Andrea Campagna, Alan Guo and Ronitt Rubinfeld). Local reconstructors are like property testers on steroids. Suppose we have access to some function \(f\) that does not satisfy some property \(\mathcal{P}\). A local reconstructor provides oracle access to a function \(g \in \mathcal{P}\) that is (approximately optimally) close to \(f\), and the reconstructor requires only sublinear queries to \(f\) to output a value of \(g\). Alan talked about reconstructors for \(k\)-connectivity in the general sparse-graph model. This also leads to new tolerant testers. Pretty intricate and neat algorithms, IMHO.

**A local computation approximation scheme to maximum matching** (Yishay Mansour and Shai Vardi). If you put local reconstructors on steroids, you get a local computation algorithm. Consider a graph \(G\), where want to “locally” find a maximum matching. We want a sublinear time procedure that given an edge of \(G\) outputs whether it is part of the matching or not. All these answers must be globally consistent and represent the final matching. Shai talked about a local \(\mathop{poly}(\log n)\) algorithm for finding \((1-\epsilon)\)-approximate matchings. Another impressive local algorithm.

**Absolutely Sound Testing of Lifted Codes** (Noga Ron-Zewi, Elad Haramaty and Madhu Sudan). Elad talked about more progress on the testing of affine-invariant properties. Previous work define a “lifting operation” for an affine-invariant base code (defined as say a function \(f:\mathbb{F}^t \rightarrow \mathbb{F}\). This is a codeword in many more variables (say a function \(f:\mathbb{F}^n \rightarrow \mathbb{F}\)), whose restriction to any t-dimensional affine subspace belongs to the base code. This paper gives absolutely sound testers for the lift of any affine-invariant base code. This work is a nice way of interpreting (and generalizing) the ideas behind low-degree testing.

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