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We consider two closely related problems: anomaly detection in sensor networks and testing for infections in human populations. In both problems, we have $n$ nodes (sensors, humans), and each node exhibits an event of interest (anomaly,…

Information Theory · Computer Science 2020-12-01 Melih Bastopcu , Sennur Ulukus

In this paper, an information theoretic analysis on non-adaptive group testing schemes based on sparse pooling graphs is presented. The binary status of the objects to be tested are modeled by i.i.d. Bernoulli random variables with…

Information Theory · Computer Science 2013-04-29 Tadashi Wadayama

Group-formation experiments, in which experimental units are randomly assigned to groups, are a powerful tool for studying peer effects in the social sciences. Existing design and analysis approaches allow researchers to draw inference from…

Methodology · Statistics 2021-03-02 Hui Xu , Guillaume Basse

Industry practitioners care about small improvements in malware detection accuracy because their models are deployed to hundreds of millions of machines, meaning a 0.1\% change can cause an overwhelming number of false positives. However,…

Machine Learning · Computer Science 2023-12-27 Tirth Patel , Fred Lu , Edward Raff , Charles Nicholas , Cynthia Matuszek , James Holt

In this paper, we derive mutual information based upper and lower bounds on the number of nonadaptive group tests required to identify a given number of "non defective" items from a large population containing a small number of "defective"…

Information Theory · Computer Science 2016-03-01 Abhay Sharma , Chandra R. Murthy

Positive and negative likelihood ratios are parameters which are used to assess and compare the effectiveness of binary diagnostic tests. Both parameters only depend on the sensitivity and specificity of the diagnostic test and are…

Other Statistics · Statistics 2024-09-02 Jose Antonio Roldan-Nofuentes , Saad Bouh Sidaty-Regad

Software testing is aimed to improve the delivered reliability of the users. Delivered reliability is the reliability of using the software after it is delivered to the users. Usually the software consists of many modules. Thus, the…

Software Engineering · Computer Science 2017-01-17 Ping Cao , Zhao Dong , Ke Liu , Kai-Yuan Cai

In software testing, the large size of the input domain makes exhaustively testing the inputs a daunting and often impossible task. Pair-wise testing is a popular approach to combinatorial testing problems. This paper reviews Pair-wise…

Software Engineering · Computer Science 2016-06-02 Jimi Sanchez

A class of two-bit bit flipping algorithms for decoding low-density parity-check codes over the binary symmetric channel was proposed in [1]. Initial results showed that decoders which employ a group of these algorithms operating in…

Information Theory · Computer Science 2012-05-22 Dung Viet Nguyen , Bane Vasic , Michael W. Marcellin

One of the prerequisites of any organization is an unvarying sustainability in the dynamic and competitive industrial environment. Development of high quality software is therefore an inevitable constraint of any software industry. Defect…

Software Engineering · Computer Science 2012-04-03 T. R. Gopalakrishnan Nair , V. Suma , Pranesh Kumar Tiwari

Product metrics, such as size or complexity, are often used to identify defect-prone parts or to focus quality assurance activities. In contrast, quality information that is available early, such as information provided by inspections, is…

Software Engineering · Computer Science 2013-12-04 Frank Elberzhager , Stephan Kremer , Jürgen Münch , Danilo Assmann

Separability for groups refers to the question which subsets of a group can be detected in its finite quotients. Classically, separability is studied in terms of which classes have a certain separability property, and this question is…

Group Theory · Mathematics 2022-02-01 Jonas Deré , Michal Ferov , Mark Pengitore

Compositionality supports the manipulation of large systems by working on their components. For model-based testing, this means that large systems can be tested by modelling and testing their components: passing tests for all components…

Software Engineering · Computer Science 2025-08-01 Gijs van Cuyck , Lars van Arragon , Jan Tretmans

This paper considers the problem of Quantitative Group Testing (QGT) where there are some defective items among a large population of $N$ items. We consider the scenario in which each item is defective with probability $K/N$, independently…

Information Theory · Computer Science 2019-10-16 Esmaeil Karimi , Fatemeh Kazemi , Anoosheh Heidarzadeh , Krishna R. Narayanan , Alex Sprintson

In the search for genetic factors that are associated with complex heritable human traits, considerable attention is now being focused on rare variants that individually have small effects. In response, numerous recent papers have proposed…

Methodology · Statistics 2014-09-10 Andriy Derkach , Jerry F. Lawless , Lei Sun

Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive)and type II (false negative) errors. In this work, we develop a statistical model to study how medical…

Applications · Statistics 2025-10-21 Lucas Böttcher , Maria R. D'Orsogna , Tom Chou

We consider the problem of non-adaptive noiseless group testing of $N$ items of which $K$ are defective. We describe four detection algorithms: the COMP algorithm of Chan et al.; two new algorithms, DD and SCOMP, which require stronger…

Information Theory · Computer Science 2014-05-20 Matthew Aldridge , Leonardo Baldassini , Oliver Johnson

A long noted difficulty when assessing the reliability (or calibration) of forecasting systems is that reliability, in general, is a hypothesis not about a finite dimensional parameter but about an entire functional relationship. A…

Data Analysis, Statistics and Probability · Physics 2020-12-09 Jochen Bröcker

Multiple heterogeneous data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we develop a unified framework of the test-and-pool approach to…

Methodology · Statistics 2023-05-30 Chenyin Gao , Shu Yang

Many biomedical experiments are carried out by pooling individual biological samples. However, pooling samples can potentially hide biological variance and give false confidence concerning the data significance. In the context of microarray…

Quantitative Methods · Quantitative Biology 2008-06-02 Shu-Dong Zhang , Timothy W. Gant
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