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**Harvard**

Damaschke, P. (2016) *Adaptive group testing with a constrained number of positive responses improved *.

** BibTeX **

@article{

Damaschke2016,

author={Damaschke, Peter},

title={Adaptive group testing with a constrained number of positive responses improved },

journal={Discrete Applied Mathematics},

issn={0166-218X},

volume={205},

pages={208-212},

abstract={Group testing aims at identifying the defective elements of a set by testing selected subsets called pools. A test gives a positive response if the tested pool contains some defective elements. Adaptive strategies test the pools one
by one. Assuming that only a tiny minority of elements are defective, the main objective of group testing strategies is to minimize the number of tests. De Bonis introduced in COCOA 2014 a problem variant where one also wants to limit the number of positive tests, as they have undesirable side effects in some applications. A strategy was given with asymptotically optimal test complexity, subject to a constant factor. In the present paper we reduce the
test complexity, making also the constant factor optimal in the limit. This is accomplished by a routine that searches for a single defective element and uses pools of decreasing sizes even after negative responses. An additional
observation is that randomization saves a further
considerable fraction of tests compared to the deterministic worst case, if the number of permitted
positive responses per defective element is small.},

year={2016},

keywords={group testing, positive test, adaptive strategy, randomized strategy},

}

** RefWorks **

RT Journal Article

SR Print

ID 235269

A1 Damaschke, Peter

T1 Adaptive group testing with a constrained number of positive responses improved

YR 2016

JF Discrete Applied Mathematics

SN 0166-218X

VO 205

SP 208

OP 212

AB Group testing aims at identifying the defective elements of a set by testing selected subsets called pools. A test gives a positive response if the tested pool contains some defective elements. Adaptive strategies test the pools one
by one. Assuming that only a tiny minority of elements are defective, the main objective of group testing strategies is to minimize the number of tests. De Bonis introduced in COCOA 2014 a problem variant where one also wants to limit the number of positive tests, as they have undesirable side effects in some applications. A strategy was given with asymptotically optimal test complexity, subject to a constant factor. In the present paper we reduce the
test complexity, making also the constant factor optimal in the limit. This is accomplished by a routine that searches for a single defective element and uses pools of decreasing sizes even after negative responses. An additional
observation is that randomization saves a further
considerable fraction of tests compared to the deterministic worst case, if the number of permitted
positive responses per defective element is small.

LA eng

DO 10.1016/j.dam.2016.01.010

OL 30