Lower bounds for sampling algorithms for estimating the average
Information Processing Letters
Property testing and its connection to learning and approximation
Journal of the ACM (JACM)
Robust Characterizations of Polynomials withApplications to Program Testing
SIAM Journal on Computing
Three theorems regarding testing graph properties
Random Structures & Algorithms
On the strength of comparisons in property testing
Information and Computation
Lower Bounds for Testing Bipartiteness in Dense Graphs
CCC '04 Proceedings of the 19th IEEE Annual Conference on Computational Complexity
Some 3CNF Properties Are Hard to Test
SIAM Journal on Computing
A combinatorial characterization of the testable graph properties: it's all about regularity
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
A Characterization of Easily Testable Induced Subgraphs
Combinatorics, Probability and Computing
Efficient Testing of Bipartite Graphs for Forbidden Induced Subgraphs
SIAM Journal on Computing
On the Benefits of Adaptivity in Property Testing of Dense Graphs
APPROX '07/RANDOM '07 Proceedings of the 10th International Workshop on Approximation and the 11th International Workshop on Randomization, and Combinatorial Optimization. Algorithms and Techniques
On proximity oblivious testing
Proceedings of the forty-first annual ACM symposium on Theory of computing
Testing juntas: a brief survey
Property testing
Testing juntas: a brief survey
Property testing
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In this paper we consider two basic questions regarding the query complexity of testing graph properties in the adjacency matrix model. The first question refers to the relation between adaptive and non-adaptive testers, whereas the second question refers to testability within complexity that is inversely proportional to the proximity parameter, denoted *** . The study of these questions reveals the importance of algorithmic design (also) in this model. The highlights of our study are: A gap between the complexity of adaptive and non-adaptive testers. Specifically, there exists a (natural) graph property that can be tested using ${\widetilde{O}}(\epsilon^{-1})$ adaptive queries, but cannot be tested using o (*** *** 3/2) non-adaptive queries. In contrast, there exist natural graph properties that can be tested using ${\widetilde{O}}(\epsilon^{-1})$ non-adaptive queries, whereas ***(*** *** 1) queries are required even in the adaptive case. We mention that the properties used in the foregoing conflicting results have a similar flavor, although they are of course different.