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arXiv 1004.4601cs.ITmath.IT
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码字测试的数据流算法

Data Stream Algorithms for Codeword Testing

Atri Rudra, Steve Uurtamo

摘要:

受存储系统和性能测试应用的启发,我们研究了用于代码的局部测试和容错测试的数据流算法。理想情况下,我们想知道是否存在渐近好的代码,可以用一次通过,多对数空间数据流算法进行本地/容错测试。我们发现,对于错误检测问题(因此,本地测试问题),存在一个一遍,对数空间数据流算法的广泛的一类渐近良好的代码,包括里德-所罗门(RS)码和扩展码。在我们的技术上更涉及的结果,我们给一个一遍,$O(e\log^2{n})$空间算法的RS(和相关)码的尺寸$k$和块长度$n$,可以区分的情况下,当收到的字和代码之间的汉明距离最多为$e$和至少为$a\cdot e$的一些绝对常数$a>1$。对于具有随机误差的RS码,我们可以得到$e\le O(n/k)$。对于折叠RS码,我们得到了类似的结果,最坏情况下的错误,只要$e\le (n/k)^{1-\eps}$的任何常数$\eps>0$。这些结果遵循减少容错测试问题的错误检测问题,使用组测试和列表的代码的可解码性的结果。我们还表明,使用我们的技术,空间需求和上限的$e\le O(n/k)$不能提高超过对数因子。

英文摘要:

Motivated by applications in storage systems and property testing, we study data stream algorithms for local testing and tolerant testing of codes. Ideally, we would like to know whether there exist asymptotically good codes that can be local/tolerant tested with one-pass, poly-log space data stream algorithms. We show that for the error detection problem (and hence, the local testing problem), there exists a one-pass, log-space data stream algorithm for a broad class of asymptotically good codes, including the Reed-Solomon (RS) code and expander codes. In our technically more involved result, we give a one-pass, $O(e\log^2{n})$-space algorithm for RS (and related) codes with dimension $k$ and block length $n$ that can distinguish between the cases when the Hamming distance between the received word and the code is at most $e$ and at least $a\cdot e$ for some absolute constant $a>1$. For RS codes with random errors, we can obtain $e\le O(n/k)$. For folded RS codes, we obtain similar results for worst-case errors as long as $e\le (n/k)^{1-\eps}$ for any constant $\eps>0$. These results follow by reducing the tolerant testing problem to the error detection problem using results from group testing and the list decodability of the code. We also show that using our techniques, the space requirement and the upper bound of $e\le O(n/k)$ cannot be improved by more than logarithmic factors.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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