Publication

Derandomization and Group Testing

2010
Conference Papers

Abstract

The rapid development of derandomization theory, which is a fundamental area in theoretical computer science, has recently led to many surprising applications outside its initial intention. We will review some recent such developments related to combinatorial group testing. In its most basic setting, the aim of group testing is to identify a set of "positive" individuals in a population of items by taking groups of items and asking whether there is a positive in each group. In particular, we will discuss explicit constructions of optimal or nearly-optimal group testing schemes using "randomness-conducting" functions. Among such developments are constructions of error-correcting group testing schemes using randomness extractors and condensers, as well as threshold group testing schemes from lossless condensers.

Official source

https://infoscience.epfl.ch/entities/publication/5c5ac3a1-e095-4ce2-8896-6a67a30effe7

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2010
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/5c5ac3a1-e095-4ce2-8896-6a67a30effe7

About this result

Related concepts (32)

Randomization

Randomization is the process of making something random. Randomization is not haphazard; instead, a random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. For example, a random sample of individuals from a population refers to a sample where every individual has a known probability of being sampled. This would be contrasted with nonprobability sampling where arbitrary individuals are selected.

Unit testing

In computer programming, unit testing is a software testing method by which individual units of source code—sets of one or more computer program modules together with associated control data, usage procedures, and operating procedures—are tested to determine whether they are fit for use. It is a standard step in development and implementation approaches such as Agile. Before unit testing, capture and replay testing tools were the norm. In 1997, Kent Beck and Erich Gamma developed and released JUnit, a unit test framework that became popular with Java developers.

Randomness extractor

A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weak entropy source, together with a short, uniformly random seed, generates a highly random output that appears independent from the source and uniformly distributed. Examples of weakly random sources include radioactive decay or thermal noise; the only restriction on possible sources is that there is no way they can be fully controlled, calculated or predicted, and that a lower bound on their entropy rate can be established.

Related publications (3)

Derandomization and Group Testing

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