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Average-case complexity

About: Average-case complexity is a research topic. Over the lifetime, 1749 publications have been published within this topic receiving 44972 citations.


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Proceedings ArticleDOI
01 Oct 2015

17 citations

Book ChapterDOI
27 May 1991
TL;DR: A new protocol implementing such operations for the case of a single-reader and one writer per variable is given, which uses time-stamps that may take values as large as the number of operations performed.
Abstract: Let X1, ..., X c be variables shared by a number of processes which operate in a totally asynchronous and wait-free manner. An operation by a process is either a write on one of the variables or a read of the values of all variables. All operations are assumed to be atomic, i.e. an execution of any number of them (including reads) must be serializable in a way compatible with the values returned by the reads. We give a new protocol implementing such operations for the case of a single-reader and one writer per variable. Our construction uses time-stamps that may take values as large as the number of operations performed. The advantagesof our construction over previous (bounded time-stamps) solutions are: (i) It has very simple semantics. (ii) The time complexity of an operation (i.e. the number of its sub-operations) and the space complexity of the construction (i.e. the number of subregisters used) are equal to the number of processes involved.

17 citations

Journal ArticleDOI
TL;DR: For the 2n-periodic periodic binary sequence with linear complexity 2n − 1 and k = 2,3, the number of sequences with given k-error linear complexity and the expected k- error linear complexity are provided.
Abstract: Linear complexity and k-error linear complexity of the stream cipher are two important standards to scale the randomicity of keystreams. For the 2n-periodic periodic binary sequence with linear complexity 2n − 1 and k = 2,3, the number of sequences with given k-error linear complexity and the expected k-error linear complexity are provided. Moreover, the proportion of the sequences whose k-error linear complexity is bigger than the expected value is analyzed.

17 citations

Book ChapterDOI
25 Feb 1993
TL;DR: A new definition is given for the average growth of a function f: Σ* → IN with respect to a probability measure μ on Σ*.
Abstract: A new definition is given for the average growth of a function f: Σ* → IN with respect to a probability measure μ on Σ*. This allows us to define meaningful average case distributional complexity classes for arbitrary time bounds (previously, one could only distinguish between polynomial and superpolynomial growth). It is shown that basically only the ranking of the inputs by decreasing probabilities are of importance.

17 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
20216
202010
20199
201810
201732