From Local to Robust Testing via Agreement Testing

Authors Irit Dinur, Prahladh Harsha, Tali Kaufman, Noga Ron-Zewi



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Author Details

Irit Dinur
  • Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel
Prahladh Harsha
  • Tata Institute of Fundamental Research, India
Tali Kaufman
  • Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel
Noga Ron-Zewi
  • Department of Computer Science, University of Haifa, Haifa, Israel

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Irit Dinur, Prahladh Harsha, Tali Kaufman, and Noga Ron-Zewi. From Local to Robust Testing via Agreement Testing. In 10th Innovations in Theoretical Computer Science Conference (ITCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 124, pp. 29:1-29:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.ITCS.2019.29

Abstract

A local tester for an error-correcting code is a probabilistic procedure that queries a small subset of coordinates, accepts codewords with probability one, and rejects non-codewords with probability proportional to their distance from the code. The local tester is robust if for non-codewords it satisfies the stronger property that the average distance of local views from accepting views is proportional to the distance from the code. Robust testing is an important component in constructions of locally testable codes and probabilistically checkable proofs as it allows for composition of local tests.
In this work we show that for certain codes, any (natural) local tester can be converted to a roubst tester with roughly the same number of queries. Our result holds for the class of affine-invariant lifted codes which is a broad class of codes that includes Reed-Muller codes, as well as recent constructions of high-rate locally testable codes (Guo, Kopparty, and Sudan, ITCS 2013). Instantiating this with known local testing results for lifted codes gives a more direct proof that improves some of the parameters of the main result of Guo, Haramaty, and Sudan (FOCS 2015), showing robustness of lifted codes.
To obtain the above transformation we relate the notions of local testing and robust testing to the notion of agreement testing that attempts to find out whether valid partial assignments can be stitched together to a global codeword. We first show that agreement testing implies robust testing, and then show that local testing implies agreement testing. Our proof is combinatorial, and is based on expansion / sampling properties of the collection of local views of local testers. Thus, it immediately applies to local testers of lifted codes that query random affine subspaces in F_q^m, and moreover seems amenable to extension to other families of locally testable codes with expanding families of local views.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational complexity and cryptography
Keywords
  • Local testing
  • Robust testing
  • Agreement testing
  • Affine-invariant codes
  • Lifted codes

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References

  1. Sanjeev Arora. Probabilistic checking of proofs and hardness of approximation problems. PhD thesis, Princeton University, 1994. Google Scholar
  2. Sanjeev Arora, Carsten Lund, Rajeev Motwani, Madhu Sudan, and Mario Szegedy. Proof verification and the hardness of approximation problems. Journal of the ACM, 45(3):501-555, May 1998. Google Scholar
  3. Sanjeev Arora and Shmuel Safra. Probabilistic Checking of Proofs: A New Characterization of NP. Journal of the ACM, 45(1):70-122, January 1998. Google Scholar
  4. Sanjeev Arora and Madhu Sudan. Improved Low Degree Testing and its Applications. Combinatorica, 23(3):365-426, 2003. Google Scholar
  5. Eli Ben-Sasson, Oded Goldreich, Prahladh Harsha, Madhu Sudan, and Salil P. Vadhan. Robust PCPs of Proximity, Shorter PCPs, and Applications to Coding. SIAM J. Comput, 36(4):889-974, 2006. Google Scholar
  6. Eli Ben-Sasson, Prahladh Harsha, and Sofya Raskhodnikova. Some 3CNF Properties Are Hard to Test. SICOMP: SIAM Journal on Computing, 35, 2005. Google Scholar
  7. Eli Ben-Sasson, Ghid Maatouk, Amir Shpilka, and Madhu Sudan. Symmetric LDPC Codes are not Necessarily Locally Testable. In IEEE Conference on Computational Complexity, pages 55-65. IEEE Computer Society, 2011. URL: http://dx.doi.org/10.1109/CCC.2011.14.
  8. Eli Ben-Sasson and Madhu Sudan. Robust locally testable codes and products of codes. Random Struct. Algorithms, 28(4):387-402, 2006. URL: http://dx.doi.org/10.1002/rsa.20120.
  9. Eli Ben-Sasson and Michael Viderman. Composition of semi-LTCs by two-wise tensor products. Computational Complexity, 24(3):601-643, 2015. URL: http://dx.doi.org/10.1007/s00037-013-0074-8.
  10. Manuel Blum, Michael Luby, and Ronitt Rubinfeld. Self-Testing/Correcting with Applications to Numerical Problems. In STOC, pages 73-83. ACM, 1990. Google Scholar
  11. A. E. Brouwer, A. M. Cohen, and A. Neumaier. Distance-Regular Graphs. Springer Verlag, 1989. Google Scholar
  12. Irit Dinur and Elazar Goldenberg. Locally Testing Direct Product in the Low Error Range. In FOCS, pages 613-622. IEEE Computer Society, 2008. URL: http://dx.doi.org/10.1109/FOCS.2008.26.
  13. Irit Dinur and Tali Kaufman. High Dimensional Expanders Imply Agreement Expanders. In Chris Umans, editor, FOCS, pages 974-985. IEEE Computer Society, 2017. URL: http://dx.doi.org/10.1109/FOCS.2017.94.
  14. Irit Dinur and Inbal Livni-Navon. Exponentially Small Soundness for the Direct Product Z-Test. In Ryan O'Donnell, editor, Computational Complexity Conference, volume 79 of LIPIcs, pages 29:1-29:50. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2017. URL: http://dx.doi.org/10.4230/LIPIcs.CCC.2017.29.
  15. Irit Dinur and Omer Reingold. Assignment Testers: Towards a Combinatorial Proof of the PCP Theorem. SIAM J. Comput, 36(4):975-1024, 2006. URL: http://dx.doi.org/10.1137/S0097539705446962.
  16. Irit Dinur and David Steurer. Direct Product Testing. In IEEE Conference on Computational Complexity, pages 188-196. IEEE Computer Society, 2014. URL: http://dx.doi.org/10.1109/CCC.2014.27.
  17. Peter Gemmell, Richard J. Lipton, Ronitt Rubinfeld, Madhu Sudan, and Avi Wigderson. Self-Testing/Correcting for Polynomials and for Approximate Functions. In Cris Koutsougeras and Jeffrey Scott Vitter, editors, STOC, pages 32-42. ACM, 1991. URL: http://dx.doi.org/10.1145/103418.103429.
  18. Goldreich and Safra. A Combinatorial Consistency Lemma with Application to Proving the PCP Theorem. SICOMP: SIAM Journal on Computing, 29, 1999. Google Scholar
  19. Alan Guo, Elad Haramaty, and Madhu Sudan. Robust Testing of Lifted Codes with Applications to Low-Degree Testing. In Venkatesan Guruswami, editor, FOCS, pages 825-844. IEEE Computer Society, 2015. URL: http://dx.doi.org/10.1109/FOCS.2015.56.
  20. Alan Guo, Swastik Kopparty, and Madhu Sudan. New affine-invariant codes from lifting. In ITCS, pages 529-540, 2013. Google Scholar
  21. Elad Haramaty, Noga Ron-Zewi, and Madhu Sudan. Absolutely Sound Testing of Lifted Codes. Theory of Computing, 11:299-338, 2015. URL: http://dx.doi.org/10.4086/toc.2015.v011a012.
  22. Russell Impagliazzo, Valentine Kabanets, and Avi Wigderson. New Direct-Product Testers and 2-Query PCPs. SIAM J. Comput, 41(6):1722-1768, 2012. URL: http://dx.doi.org/10.1137/09077299X.
  23. Tali Kaufman and Madhu Sudan. Algebraic property testing: the role of invariance. In STOC, pages 403-412. ACM, 2008. URL: http://dx.doi.org/10.1145/1374376.1374434.
  24. Swastik Kopparty, Or Meir, Noga Ron-Zewi, and Shubhangi Saraf. High-Rate Locally Correctable and Locally Testable Codes with Sub-Polynomial Query Complexity. Journal of ACM, 64(2):11:1-11:42, 2017. URL: http://dx.doi.org/10.1145/3051093.
  25. Ran Raz and Shmuel Safra. A Sub-Constant Error-Probability Low-Degree Test, and a Sub-Constant Error-Probability PCP Characterization of NP. In STOC, pages 475-484. ACM, 1997. URL: http://dx.doi.org/10.1145/258533.258641.
  26. Ronitt Rubinfeld and Madhu Sudan. Robust characterizations of polynomials with applications to program testing. SIAM Journal on Computing, 25(2):252-271, April 1996. Google Scholar
  27. Michael Viderman. A combination of testability and decodability by tensor products. Random Struct. Algorithms, 46(3):572-598, 2015. Google Scholar
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