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Proceedings ArticleDOI

Algebraic property testing: the role of invariance

TLDR
This work considers (F-)linear properties that are invariant under linear transformations of the domain and proves that an O(1)-local "characterization" is a necessary and sufficient condition for O( 1)-local testability, and shows that local formal characterizations essentially imply local testability.
Abstract
We argue that the symmetries of a property being tested play a central role in property testing. We support this assertion in the context of algebraic functions, by examining properties of functions mapping a vector space Kn over a field K to a subfield F. We consider (F-)linear properties that are invariant under linear transformations of the domain and prove that an O(1)-local "characterization" is a necessary and sufficient condition for O(1)-local testability. when |K| = O(1). (A local characterization of a property is a definition of a property in terms of local constraints satisfied by functions exhibiting a property.) For the subclass of properties that are invariant under affine transformations of the domain, we prove that the existence of a single O(1)-local constraint implies O(1)-local testability. These results generalize and extend the class of algebraic properties, most notably linearity and low-degree-ness, that were previously known to be testable. In particular, the extensions include properties satisfied by functions of degree linear in n that turn out to be O(1)-locally testable. Our results are proved by introducing a new notion that we term "formal characterizations". Roughly this corresponds to characterizations that are given by a single local constraint and its permutations under linear transformations of the domain. Our main testing result shows that local formal characterizations essentially imply local testability. We then investigate properties that are linear-invariant and attempt to understand their local formal characterizability. Our results here give coarse upper and lower bounds on the locality of constraints and characterizations for linear-invariant properties in terms of some structural parameters of the property we introduce. The lower bounds rule out any characterization, while the upper bounds give formal characterizations. Combining the two gives a test for all linear-invariant properties with local characterizations. We believe that invariance of properties is a very interesting notion to study in the context of property testing in general and merits a systematic study. In particular, the class of linear-invariant and affine-invariant properties exhibits a rich variety among algebraic properties and offer better intuition about algebraic properties than the more limited class of low-degree functions.

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Citations
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Book

Introduction to Property Testing

TL;DR: In this article, a wide range of algorithmic techniques for the design and analysis of tests for algebraic properties, properties of Boolean functions, graph properties, and properties of distributions are presented.
Book

Algorithmic and Analysis Techniques in Property Testing

TL;DR: This monograph surveys results in property testing, where the emphasis is on common analysis and algorithmic techniques.
Book ChapterDOI

Cube Testers and Key Recovery Attacks on Reduced-Round MD6 and Trivium

TL;DR: In this paper, a new class of attacks called cube testers, based on efficient property-testing algorithms, and applied to MD6 and to the stream cipher Trivium, were presented.

Sublinear time algorithms

TL;DR: In this article, the authors discuss the sorts of answers that one might be able to achieve in this new setting, where an algorithm must give some sort of an answer after inspecting only a very small portion of the input.
Journal ArticleDOI

Sublinear Time Algorithms

TL;DR: Sublinear time algorithms represent a new paradigm in computing, where an algorithm must give some sort of an answer after inspecting only a very small portion of the input as mentioned in this paper, and discuss the types of answers that one can hope to achieve in this setting.
References
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Journal ArticleDOI

Property testing and its connection to learning and approximation

TL;DR: This paper considers the question of determining whether a function f has property P or is ε-far from any function with property P, and devise algorithms to test whether the underlying graph has properties such as being bipartite, k-Colorable, or having a clique of density p-Clique with respect to the vertex set.
Journal ArticleDOI

Robust Characterizations of Polynomials withApplications to Program Testing

TL;DR: The characterizations provide results in the area of coding theory by giving extremely fast and efficient error-detecting schemes for some well-known codes and play a crucial role in subsequent results on the hardness of approximating some NP-optimization problems.
Proceedings ArticleDOI

Self-testing/correcting with applications to numerical problems

TL;DR: This work presents general techniques for constructing simple to program self-testing/correcting pairs for a variety of numerical functions, including integer multiplication, modular multiplication, matrix multiplication, inverting matrices, computing the determinant of a matrix, Computing the rank of a Matrix, integer division, modular exponentiation, and polynomial multiplication.
Journal Article

Property Testing and its connection to Learning and Approximation

TL;DR: In this paper, the authors consider the question of determining whether a function f has property P or is e-far from any function with property P. In some cases, it is also allowed to query f on instances of its choice.
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