We consider the fundamental question of understanding the relative power of two important computational models: property testing and data streaming. We present a novel framework closely linking these areas in the setting of general graphs in the context of constant-query complexity testing and constant-space streaming. Our main result is a generic transformation of a one-sided error property tester in the random-neighbor model with constant query complexity into a one-sided error property tester in the streaming model with constant space complexity. Previously such a generic transformation was only known for bounded-degree graphs.
@InProceedings{czumaj_et_al:LIPIcs.APPROX/RANDOM.2020.16, author = {Czumaj, Artur and Fichtenberger, Hendrik and Peng, Pan and Sohler, Christian}, title = {{Testable Properties in General Graphs and Random Order Streaming}}, booktitle = {Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)}, pages = {16:1--16:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-164-1}, ISSN = {1868-8969}, year = {2020}, volume = {176}, editor = {Byrka, Jaros{\l}aw and Meka, Raghu}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2020.16}, URN = {urn:nbn:de:0030-drops-126190}, doi = {10.4230/LIPIcs.APPROX/RANDOM.2020.16}, annote = {Keywords: Graph property testing, sublinear algorithms, graph streaming algorithms} }
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