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Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on correctly specified models. We study robust sequential experimental design under model…

Machine Learning · Statistics 2026-05-14 Qianglin Wen , Xiangkun Wu , Chengchun Shi , Ting Li , Niansheng Tang , Yingying Zhang , Hongtu Zhu

Crossover designs are an extremely useful tool to investigators, whilst group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have…

Methodology · Statistics 2017-10-11 Michael Grayling , James Wason , Adrian Mander

Context: The complexity of modern safety-critical systems in industries keep on increasing due to the rising number of features and functionalities. This calls for formal methods in order to entrust confidence in such systems. Nevertheless,…

Software Engineering · Computer Science 2021-08-17 Arut Prakash Kaleeswaran , Arne Nordmann , Thomas Vogel , Lars Grunske

Given a fixed-sample-size test that controls the error probabilities under two specific, but arbitrary, distributions, a 3-stage and two 4-stage tests are proposed and analyzed. For each of them, a novel, concrete, non-asymptotic,…

Statistics Theory · Mathematics 2022-06-27 Yiming Xing , Georgios Fellouris

The goal of the group testing problem is to identify a set of defective items within a larger set of items, using suitably-designed tests whose outcomes indicate whether any defective item is present. In this paper, we study how the number…

Information Theory · Computer Science 2023-01-18 Ivan Lau , Jonathan Scarlett , Yang Sun

The conventional model of disjunctive group testing assumes that there are several defective elements (or defectives) among a large population, and a group test yields the positive response if and only if the testing group contains at least…

Information Theory · Computer Science 2019-08-20 A. G. D'yachkov , N. A. Polyanskii , V. Yu. Shchukin , I. V. Vorobyev

Tech companies (e.g., Google or Facebook) often use randomized online experiments and/or A/B testing primarily based on the average treatment effects to compare their new product with an old one. However, it is also critically important to…

Methodology · Statistics 2021-11-09 Chengchun Shi , Shikai Luo , Hongtu Zhu , Rui Song

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of tests, and is relevant in applications such as medical testing, communication protocols, pattern matching, and…

Information Theory · Computer Science 2019-01-30 Jonathan Scarlett , Volkan Cevher

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

When changes are performed on an automated production system (aPS), new faults can be accidentally introduced in the system, which are called regressions. A common method for finding these faults is regression testing. In most cases, this…

Software Engineering · Computer Science 2022-12-13 Sebastian Ulewicz , Birgit Vogel-Heuser

Group testing is a useful method that has broad applications in medicine, engineering, and even in airport security control. Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to…

Other Statistics · Statistics 2017-04-17 Yaakov Malinovsky

Non-adaptive group testing involves grouping arbitrary subsets of $n$ items into different pools. Each pool is then tested and defective items are identified. A fundamental question involves minimizing the number of pools required to…

Discrete Mathematics · Computer Science 2011-07-26 Mahdi Cheraghchi , Amin Karbasi , Soheil Mohajer , Venkatesh Saligrama

In probabilistic nonadaptive group testing (PGT), we aim to characterize the number of pooled tests necessary to identify a random $k$-sparse vector of defectives with high probability. Recent work has shown that $n$ tests are necessary…

Information Theory · Computer Science 2021-06-15 Larkin Flodin , Arya Mazumdar

Group sequential designs drive innovation in clinical, industrial, and corporate settings. Early stopping for failure in sequential designs conserves experimental resources, whereas early stopping for success accelerates access to improved…

Methodology · Statistics 2025-11-27 Luke Hagar , Shirin Golchi , Marina B. Klein

Recent papers initiated the study of a generalization of group testing where the potentially contaminated sets are the members of a given hypergraph F=(V,E). This generalization finds application in contexts where contaminations can be…

Data Structures and Algorithms · Computer Science 2024-07-02 Annalisa De Bonis

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an…

Software Engineering · Computer Science 2011-12-20 Hara Gopal Mani Pakala , Dr. Plh Varaprasad , Dr. Raju Kvsvn , Dr. Ibrahim Khan

Non-adaptive group testing refers to the problem of inferring a sparse set of defectives from a larger population using the minimum number of simultaneous pooled tests. Recent positive results for noiseless group testing have motivated the…

Information Theory · Computer Science 2021-07-16 Gabriel Arpino , Nicolò Grometto , Afonso S. Bandeira

We consider the nonadaptive group testing with N items, of which $K = \Theta(N^\theta)$ are defective. We study a test design in which each item appears in nearly the same number of tests. For each item, we independently pick L tests…

Information Theory · Computer Science 2018-09-26 Oliver Johnson , Matthew Aldridge , Jonathan Scarlett

This article reviews a class of adaptive group testing procedures that operate under a probabilistic model assumption as follows. Consider a set of $N$ items, where item $i$ has the probability $p$ ($p_i$ in the generalized group testing)…

Methodology · Statistics 2021-02-19 Yaakov Malinovsky , Paul S. Albert

Executing various sequences of system functions in a system under test represents one of the primary techniques in software testing. The natural way to create effective, consistent and efficient test sequences is to model the system under…

Software Engineering · Computer Science 2019-12-05 Miroslav Bures , Bestoun S. Ahmed
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