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Mutation testing is a means to assess the effectiveness of a test suite and its outcome is considered more meaningful than code coverage metrics. However, despite several optimizations, mutation testing requires a significant computational…

Software Engineering · Computer Science 2019-03-14 Rainer Niedermayr , Stefan Wagner

We initiate the study of \emph{inverse} problems in approximate uniform generation, focusing on uniform generation of satisfying assignments of various types of Boolean functions. In such an inverse problem, the algorithm is given uniform…

Computational Complexity · Computer Science 2012-11-09 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

We present an improvement on Thurley's recent randomized approximation scheme for #k-SAT where the task is to count the number of satisfying truth assignments of a Boolean function {\Phi} given as an n-variable k-CNF. We introduce a novel…

Data Structures and Algorithms · Computer Science 2014-06-06 Manuel Schmitt , Rolf Wanka

A number of biomedical problems require performing many hypothesis tests, with an attendant need to apply stringent thresholds. Often the data take the form of a series of predictor vectors, each of which must be compared with a single…

Methodology · Statistics 2014-05-13 Yi-Hui Zhou , Fred Wright

Given two testable properties $\mathcal{P}_{1}$ and $\mathcal{P}_{2}$, under what conditions are the union, intersection or set-difference of these two properties also testable? We initiate a systematic study of these basic set-theoretic…

Data Structures and Algorithms · Computer Science 2010-10-26 Victor Chen , Madhu Sudan , Ning Xie

For any Boolean function $f:\{0,1\}^n \to \{0,1\}$ with a complexity measure having value $k \ll n$, is it possible to restrict the function $f$ to $\Theta(k)$ variables while keeping the complexity preserved at $\Theta(k)$? This question,…

Computational Complexity · Computer Science 2026-05-22 Chandrima Kayal , Rajat Mittal , Sai Soumya Nalli , Manaswi Paraashar , Karthikeya Polisetty , Jayalal Sarma , Nitin Saurabh

We develop a new permutation test for inference on a subvector of coefficients in linear models. The test is exact when the regressors and the error terms are independent. Then, we show that the test is asymptotically of correct level,…

Econometrics · Economics 2023-09-13 Xavier D'Haultfœuille , Purevdorj Tuvaandorj

We revisit the Raz-Safra plane-vs.-plane test and study the closely related cube vs. cube test. In this test the tester has access to a "cubes table" which assigns to every cube a low degree polynomial. The tester randomly selects two cubes…

Computational Complexity · Computer Science 2016-12-23 Amey Bhangale , Irit Dinur , Inbal Livni Navon

We revisit the Stochastic Score Classification (SSC) problem introduced by Gkenosis et al. (ESA 2018): We are given $n$ tests. Each test $j$ can be conducted at cost $c_j$, and it succeeds independently with probability $p_j$. Further, a…

Data Structures and Algorithms · Computer Science 2024-01-23 Benedikt M. Plank , Kevin Schewior

The Consolidated Standards of Reporting Trials statement is the global benchmark for transparent and high-quality reporting of randomized controlled trials. Manual verification of CONSORT adherence is a laborious, time-intensive process…

Computation and Language · Computer Science 2025-11-18 Zhichao He , Mouxiao Bian , Jianhong Zhu , Jiayuan Chen , Yunqiu Wang , Wenxia Zhao , Tianbin Li , Bing Han , Jie Xu , Junyan Wu

Generalized linear mixed models (GLMM) are commonly used to analyze clustered data, but when the number of clusters is small to moderate, standard statistical tests may produce elevated type I error rates. Small-sample corrections have been…

Methodology · Statistics 2023-11-07 Hongxiang Qiu , Andrea J. Cook , Jennifer F. Bobb

This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to $1/2$. Our contributions include the following: i) An analysis of the…

Computational Complexity · Computer Science 2023-10-24 Supartha Podder , Penghui Yao , Zekun Ye

In traditional k-fold cross-validation, each instance is used ($k-1$) times for training and once for testing, leading to redundancy that lets many instances disproportionately influence the learning phase. We introduce Irredundant $k$-fold…

Machine Learning · Computer Science 2025-08-29 Jesus S. Aguilar-Ruiz

Let $\mathscr{F}_{n,d}$ be the class of all functions $f:\{-1,1\}^n\to[-1,1]$ on the $n$-dimensional discrete hypercube of degree at most $d$. In the first part of this paper, we prove that any (deterministic or randomized) algorithm which…

Machine Learning · Computer Science 2024-10-23 Alexandros Eskenazis , Paata Ivanisvili , Lauritz Streck

When data analysts train a classifier and check if its accuracy is significantly different from chance, they are implicitly performing a two-sample test. We investigate the statistical properties of this flexible approach in the…

Machine Learning · Computer Science 2020-02-18 Ilmun Kim , Aaditya Ramdas , Aarti Singh , Larry Wasserman

Simultaneously testing $K$ hypotheses while controlling the family-wise error rate is a fundamental problem in statistics. Existing procedures (Bonferroni, Holm, Hochberg, Hommel) provide valid control but sacrifice power, increasingly so…

Methodology · Statistics 2026-04-14 Prasanjit Dubey , Xiaoming Huo

The $\epsilon$-approximate degree of a Boolean function $f: \{-1, 1\}^n \to \{-1, 1\}$ is the minimum degree of a real polynomial that approximates $f$ to within $\epsilon$ in the $\ell_\infty$ norm. We prove several lower bounds on this…

Computational Complexity · Computer Science 2014-03-25 Mark Bun , Justin Thaler

Automated tests play an important role in software evolution because they can rapidly detect faults introduced during changes. In practice, code-coverage metrics are often used as criteria to evaluate the effectiveness of test suites with…

Software Engineering · Computer Science 2016-11-23 Rainer Niedermayr , Elmar Juergens , Stefan Wagner

A Risk-Limiting Audit (RLA) is a statistical election tabulation audit with a rigorous error guarantee. We present ballot polling RLA PROVIDENCE, an audit with the efficiency of MINERVA and flexibility of BRAVO. We prove that PROVIDENCE is…

Cryptography and Security · Computer Science 2022-10-18 Oliver Broadrick , Poorvi L. Vora , Filip Zagórski

When $k$ factors each taking one of $v$ levels may affect the correctness or performance of a complex system, a test is selected by setting each factor to one of its levels and determining whether the system functions as expected (passes…

Combinatorics · Mathematics 2021-01-06 Charles J. Colbourn , Bingli Fan , Daniel Horsley
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