Tootfinder

SATORI: Static Test Oracle Generation for REST APIs
Juan C. Alonso, Alberto Martin-Lopez, Sergio Segura, Gabriele Bavota, Antonio Ruiz-Cort\'es
https://arxiv.org/abs/2508.16318

SATORI: Static Test Oracle Generation for REST APIs
REST API test case generation tools are evolving rapidly, with growing capabilities for the automated generation of complex tests. However, despite their strengths in test data generation, these tools are constrained by the types of test oracles they support, often limited to crashes, regressions, and noncompliance with API specifications or design standards. This paper introduces SATORI (Static API Test ORacle Inference), a black-box approach for generating test oracles for REST APIs by analyz…

Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance
Yufei He, Ruoyu Li, Alex Chen, Yue Liu, Yulin Chen, Yuan Sui, Cheng Chen, Yi Zhu, Luca Luo, Frank Yang, Bryan Hooi
https://arxiv.org/abs/2507.17131

Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance
Large language model (LLM) agents often struggle in environments where rules and required domain knowledge frequently change, such as regulatory compliance and user risk screening. Current approaches, like offline fine-tuning and standard prompting, are insufficient because they cannot effectively adapt to new knowledge during actual operation. To address this limitation, we propose the Adaptive Reflective Interactive Agent (ARIA), an LLM agent framework designed specifically to continuously le…

CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
Tianyu Chen, Vansh Bansal, James G. Scott
https://arxiv.org/abs/2507.17030

CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
We consider the problem of validating whether a neural posterior estimate \( q(θ\mid x) \) is an accurate approximation to the true, unknown true posterior \( p(θ\mid x) \). Existing methods for evaluating the quality of an NPE estimate are largely derived from classifier-based tests or divergence measures, but these suffer from several practical drawbacks. As an alternative, we introduce the \emph{Conditional Localization Test} (CoLT), a principled method designed to detect discrepancies bet…

High-Precision Mixed Feature Fusion Network Using Hypergraph Computation for Cervical Abnormal Cell Detection
Jincheng Li, Danyang Dong, Menglin Zheng, Jingbo Zhang, Yueqin Hang, Lichi Zhang, Lili Zhao
https://arxiv.org/abs/2508.16140

High-Precision Mixed Feature Fusion Network Using Hypergraph Computation for Cervical Abnormal Cell Detection
Automatic detection of abnormal cervical cells from Thinprep Cytologic Test (TCT) images is a critical component in the development of intelligent computer-aided diagnostic systems. However, existing algorithms typically fail to effectively model the correlations of visual features, while these spatial correlation features actually contain critical diagnostic information. Furthermore, no detection algorithm has the ability to integrate inter-correlation features of cells with intra-discriminati…

AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychology
Akash Kundu, Rishika Goswami
https://arxiv.org/abs/2506.18156 https://

AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychology
We investigate whether Large Language Models (LLMs) exhibit human-like cognitive patterns under four established frameworks from psychology: Thematic Apperception Test (TAT), Framing Bias, Moral Foundations Theory (MFT), and Cognitive Dissonance. We evaluated several proprietary and open-source models using structured prompts and automated scoring. Our findings reveal that these models often produce coherent narratives, show susceptibility to positive framing, exhibit moral judgments aligned wi…

Political Ideology Shifts in Large Language Models
Pietro Bernardelle, Stefano Civelli, Leon Fr\"ohling, Riccardo Lunardi, Kevin Roitero, Gianluca Demartini
https://arxiv.org/abs/2508.16013

Political Ideology Shifts in Large Language Models
Large language models (LLMs) are increasingly deployed in politically sensitive settings, raising concerns about their potential to encode, amplify, or be steered toward specific ideologies. We investigate how adopting synthetic personas influences ideological expression in LLMs across seven models (7B-70B+ parameters) from multiple families, using the Political Compass Test as a standardized probe. Our analysis reveals four consistent patterns: (i) larger models display broader and more polari…

An omnibus goodness-of-fit test based on trigonometric moments
Alain Desgagn\'e, Fr\'ed\'eric Ouimet
https://arxiv.org/abs/2507.18591 https://a…

An omnibus goodness-of-fit test based on trigonometric moments
We present a versatile omnibus goodness-of-fit test based on the first two trigonometric moments of probability-integral-transformed data, which rectifies the covariance scaling errors made by Langholz and Kronmal [J. Amer. Statist. Assoc. 86 (1991), 1077--1084]. Once properly scaled, the quadratic-form statistic asymptotically follows a $χ_2^2$ distribution under the null hypothesis. The covariance scalings and parameter estimators are provided for $32$ null distribution families, covering he…

Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments
Hichem Cheriet, Khellat Kihel Badra, Chouraqui Samira
https://arxiv.org/abs/2508.16515

Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments
The most crucial challenges for UAVs are planning paths and avoiding obstacles in their way. In recent years, a wide variety of path-planning algorithms have been developed. These algorithms have successfully solved path-planning problems; however, they suffer from multiple challenges and limitations. To test the effectiveness and efficiency of three widely used algorithms, namely A*, RRT*, and Particle Swarm Optimization (PSO), this paper conducts extensive experiments in 3D urban city environ…

Probing Local Branching Dynamics with Stern-Gerlach Interferometers and Dual Sensing
Xing M. Wang
https://arxiv.org/abs/2508.16019 https://arxiv.org/pdf/25…

Probing Local Branching Dynamics with Stern-Gerlach Interferometers and Dual Sensing
We propose a new experimental program to empirically distinguish the Branched Hilbert Subspace Interpretation (BHSI) from the Copenhagen Interpretation (CI) and Many-Worlds Interpretations (MWI) by examining the dynamics of local quantum branching. Our approach uses Stern-Gerlach interferometers (SGIs) equipped with a novel dual sensing technique, combining non-destructive transparent sensors (TSs) and projective opaque detectors (ODs), to test foundational principles in a closed system. The fi…

On tested Bousfield-Friedlander localizations
Niall Taggart
https://arxiv.org/abs/2507.17321 https://arxiv.org/pdf/2507.17321

On tested Bousfield-Friedlander localizations
We demonstrate that a Bousfield-Friedlander localization with a set of test morphisms in the sense introduced by Bandklayder, Bergner, Griffiths, Johnson, and Santhanam can also be characterized as a left Bousfield localization at the set of test morphisms. This viewpoint enables us to establish a homogeneous model structure associated with any calculus arising from a Bousfield-Friedlander localization of this form. As a corollary, we show that homogeneous functors in discrete calculus coincide…

DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?
Francesco Marchiori, Marco Alecci, Luca Pajola, Mauro Conti
https://arxiv.org/abs/2506.18516

DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?
Adversarial examples are small and often imperceptible perturbations crafted to fool machine learning models. These attacks seriously threaten the reliability of deep neural networks, especially in security-sensitive domains. Evasion attacks, a form of adversarial attack where input is modified at test time to cause misclassification, are particularly insidious due to their transferability: adversarial examples crafted against one model often fool other models as well. This property, known as a…

Time for Quiescence: Modelling quiescent behaviour in testing via time-outs in timed automata
Laura Brand\'an Briones, Marcus Gerhold, Petra van den Bos, Mari\"elle Stoelinga
https://arxiv.org/abs/2507.18205

Time for Quiescence: Modelling quiescent behaviour in testing via time-outs in timed automata
Model-based testing (MBT) derives test suites from a behavioural specification of the system under test. In practice, engineers favour simple models, such as labelled transition systems (LTSs). However, to deal with quiescence - the absence of observable output - in practice, a time-out needs to be set to conclude observation of quiescence. Timed MBT exists, but it typically relies on the full arsenal of timed automata (TA). We present a lifting operator $χ^{\scriptstyle M}\!$ that adds timi…

Examination of Eye-Tracking, Head-Gaze, and Controller-Based Ray-casting in TMT-VR: Performance and Usability Across Adulthood
Panagiotis Kourtesis, Evgenia Giatzoglou, Panagiotis Vorias, Katerina Alkisti Gounari, Eleni Orfanidou, Chrysanthi Nega
https://arxiv.org/abs/2506.19519

Examination of Eye-Tracking, Head-Gaze, and Controller-Based Ray-casting in TMT-VR: Performance and Usability Across Adulthood
Virtual reality (VR) can enrich neuropsychological testing, yet the ergonomic trade-offs of its input modes remain under-examined. Seventy-seven healthy volunteers-young (19-29 y) and middle-aged (27-56 y)-completed a VR Trail-Making Test with three pointing methods: eye-tracking, head-gaze, and a six-degree-of-freedom hand controller. Completion time, spatial accuracy, and error counts for the simple (Trail A) and alternating (Trail B) sequences were analysed in 3 x 2 x 2 mixed-model ANOVAs; p…

An Analytical Neighborhood Enrichment Score for Spatial Omics
Axel Andersson, Hanna Nystr\"om
https://arxiv.org/abs/2506.18692 https://

An Analytical Neighborhood Enrichment Score for Spatial Omics
The neighborhood enrichment test is used to quantify spatial enrichment and depletion between spatial points with categorical labels, which is a common data type in spatial omics. Traditionally, this test relies on a permutation-based Monte Carlo approach, which tends to be computationally expensive for large datasets. In this study, we present a modified version of the test that can be computed analytically. This analytical version showed a minimum Pearson correlation of 0.95 with the conventi…

Greybody factors of charged black holes with axion hair
Ratchaphat Nakarachinda, Petarpa Boonserm, Antonio De Felice, Shinji Tsujikawa, Pitayuth Wongjun
https://arxiv.org/abs/2506.18241

Greybody factors of charged black holes with axion hair
We study the greybody factor of charged hairy black holes (BHs) that arise due to the presence of an axion coupled to the electromagnetic field. Specifically, we consider spin-0 and spin-1 test particles propagating in the background of BHs with axion hair, where the spacetime geometry is modified compared to that of the Reissner-Nordstrom (RN) BH. In contrast to the RN solution, with a given total BH charge, the effective potential for test particles depends on the ratio of electric to magneti…

YATE: The Role of Test Repair in LLM-Based Unit Test Generation
Michael Konstantinou, Renzo Degiovanni, Jie M. Zhang, Mark Harman, Mike Papadakis
https://arxiv.org/abs/2507.18316

YATE: The Role of Test Repair in LLM-Based Unit Test Generation
Recent advances in automated test generation utilises language models to produce unit tests. While effective, language models tend to generate many incorrect tests with respect to both syntax and semantics. Although such incorrect tests can be easily detected and discarded, they constitute a "missed opportunity" -- if fixed, they are often valuable as they directly add testing value (they effectively target the underlying program logic to be tested) and indirectly form good seeds for generating…

A general randomized test for Alpha
Daniele Massacci, Lucio Sarno, Lorenzo Trapani, Pierluigi Vallarino
https://arxiv.org/abs/2507.17599 https://arxiv.org/…

A general randomized test for Alpha
We propose a methodology to construct tests for the null hypothesis that the pricing errors of a panel of asset returns are jointly equal to zero in a linear factor asset pricing model -- that is, the null of "zero alpha". We consider, as a leading example, a model with observable, tradable factors, but we also develop extensions to accommodate for non-tradable and latent factors. The test is based on equation-by-equation estimation, using a randomized version of the estimated alphas, which onl…

Environmental Effects on Galaxy Evolution
Ziqi Mu
https://arxiv.org/abs/2507.17243 https://arxiv.org/pdf/2507.17243

Environmental Effects on Galaxy Evolution
Galaxies evolve within a web-like cosmic structure, and their properties are strongly shaped by their surrounding environments. We apply a nonparametric Bayesian two-sample test based on Pólya tree priors to galaxy data from SDSS DR7 and DESI DR1 BGS to quantify the differences between galaxies in dense and sparse cosmic environments. Compared to the Kolmogorov-Smirnov test and parametric Bayesian test, our approach does not require strong assumptions about the underlying distributional form a…

Testing the heavy decaying sterile neutrino hypothesis at the DUNE near detector
Sabya Sachi Chatterjee, St\'ephane Lavignac, O. G. Miranda
https://arxiv.org/abs/2508.15888 …

Testing the heavy decaying sterile neutrino hypothesis at the DUNE near detector
One of the most convincing explanations of the LSND and MiniBooNE anomalies relies on a heavy, mostly sterile neutrino with a small muon neutrino component, which decays to an electron neutrino and an invisible light scalar field. We investigate the possibility to test this hypothesis at the near detector complex of the upcoming DUNE experiment. We find that the DUNE liquid argon near detector (ND-LAr) can probe a larger region of the parameter space than the Fermilab SBN program, and may help …

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, Alexandre R. Franco, Michael P. Milham, Aviv Dotan, Scott Makeig, Alexandre Gramfort, Jean-Remi King, Marie-Constance Corsi, Pedro A. Vald\'es-Sosa, Amit Majumdar, Alan Evans, Terrence J Sejnowski, Oren Shriki, Sylvain Chevallier, Arnaud Delorme

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-based competition comprising two challenges. First, the Transfer Challenge asks participants to build and test a model that can zero-shot decode new tasks and new subjects from their EEG data. Second, the Psychopathology factor prediction Challenge asks participants to infer subject measures of mental health from EEG da…

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Tight (Double) Exponential Bounds for Identification Problems: Locating-Dominating Set and Test C...
Dipayan Chakraborty, Florent Foucaud, Diptapriyo Majumdar, Prafullkumar Tale

A Spline-Based Stress Function Approach for the Principle of Minimum Complementary Energy
Fabian Key, Lukas Freinberger
https://arxiv.org/abs/2506.19534 ht…

A Spline-Based Stress Function Approach for the Principle of Minimum Complementary Energy
In computational engineering, ensuring the integrity and safety of structures in fields such as aerospace and civil engineering relies on accurate stress prediction. However, analytical methods are limited to simple test cases, and displacement-based finite element methods (FEMs), while commonly used, require a large number of unknowns to achieve high accuracy; stress-based numerical methods have so far failed to provide a simple and effective alternative. This work aims to develop a novel nume…

Hybrid Single-Pulse and Sawyer-Tower Method for Accurate Transistor Loss Separation in High-Frequency High-Efficiency Power Converters
Xiaoyang Tian, Mowei Lu, Florin Udrea, Stephan Goetz
https://arxiv.org/abs/2506.18635

Hybrid Single-Pulse and Sawyer-Tower Method for Accurate Transistor Loss Separation in High-Frequency High-Efficiency Power Converters
Accurate measurement of transistor parasitic capacitance and its associated energy losses is critical for evaluating device performance, particularly in high-frequency and high-efficiency power conversion systems. This paper proposes a hybrid single-pulse and Sawyer-Tower test method to analyse switching characteristics of field-effect transistors (FET), which not only eliminates overlap losses but also mitigates the effects of current backflow observed in traditional double-pulse testing. Thro…

What determines the $\gamma$-ray luminosities of classical novae?
Peter Craig, Elias Aydi, Laura Chomiuk, Ashley Stone, Jay Strader, Atticus Chong, Kwan-Lok Li, Jhih-Ling Fan, Arash Bahramian, David A. H. Buckley, Luca Izzo, Adam Kawash, Brian D. Metzger, Koji Mukai, Justin D. Linford, Marina Orio, J. L. Sokoloski, Kirill V. Sokolovsky, Evangelia Tremou, Frederick M. Walter, Joan Guarro Fl\'o, Christophe Boussin, St\'ephane Charbonne, Olivier Garde, Konstantin Belyakov, Libert …

What determines the $γ$-ray luminosities of classical novae?
Classical novae in the Milky Way have now been well-established as high-energy GeV $γ$-ray sources. In novae with main-sequence companions, this emission is believed to result from shocks internal to the nova ejecta, as a later fast wind collides with an earlier slow outflow. To test this model and constrain the $γ$-ray production mechanism, we present a systematic study of a sample of recent Galactic novae, comparing their $γ$-ray properties ($γ$-ray luminosity and duration) with their out…

Comparison of $R_h=ct$ and $\Lambda$CDM using DESI DR1 measurements
Kunj Panchal, Shantanu Desai
https://arxiv.org/abs/2506.18445 https://

Comparison of $R_h=ct$ and $Λ$CDM using DESI DR1 measurements
We use DESI DR1 BAO measurements of the ratio of tranvserse comoving distance to Hubble distance in order to test the compatibility of $R_h=ct$ over flat $Λ$CDM. For this purpose, we used Bayesian model selection to evaluate the efficacy of these models given the observed data. When we consider the BAO measurements up to redshift of 1.3, both models are equally favored. However, when we consider the Lyman-$α$ QSO measurement at redshift of 2.33, we find Bayes factors of greater than 100 for f…

A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network
Jaskirat Singh Maskeen, Sandip Lashkare
https://arxiv.org/abs/2506.19377

A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network
We develop a unified platform to evaluate Ideal, Linear, and Non-linear $\text{Pr}_{0.7}\text{Ca}_{0.3}\text{MnO}_{3}$ memristor-based synapse models, each getting progressively closer to hardware realism, alongside four STDP learning rules in a two-layer SNN with LIF neurons and adaptive thresholds for five-class MNIST classification. On MNIST with small train set and large test set, our two-layer SNN with ideal, 25-state, and 12-state nonlinear memristor synapses achieves 92.73 %, 91.07 %, an…

Location Information Sharing Using Software Defined Radio in Multi-UAV Systems
Mehmet Kaan Erol, Eyup Emre Ulku
https://arxiv.org/abs/2506.17678 https://…

Location Information Sharing Using Software Defined Radio in Multi-UAV Systems
SDR (Software Defined Radio) provides flexible, reproducible, and longer-lasting radio tools for military and civilian wireless communications infrastructure. SDR is a radio communication system whose components are implemented as software. This study aims to establish multi-channel wireless communication with FANET between two SDRs to share location information and examine it in a realistic test environment. We used multi-channel token circulation as a channel access protocol and GNU Radio pla…

Stability of universal properties against perturbations of the Markov Chain Monte Carlo algorithm
Matteo Bacci, Claudio Bonati
https://arxiv.org/abs/2506.18561

Stability of universal properties against perturbations of the Markov Chain Monte Carlo algorithm
We numerically investigate the stability of universal properties at continuous phase transitions against perturbations of the Markov Chain Monte Carlo algorithm used to simulate the system. We consider the three dimensional XY model as test bed, and both local (single site Metropolis) and global (single cluster) updates, introducing deterministic truncation-like perturbations and stochastic perturbations in the acceptance probabilities. In (almost) all the cases we find a remarkable stability o…

Increasing Efficiency of the Chain of Contagion Task
Lars OM Rothkegel, Jakob Fink-Lamotte
https://arxiv.org/abs/2506.19314 https://a…

Increasing Efficiency of the Chain of Contagion Task
The chain of contagion task (CCT) is a pychological test to measure the amount of contagious beliefs in individuals. Contagious beliefs thereby refer to the perception that certain objects, people, or substances can transmit contamination through mere contact or proximity (Rozin et al., 1986). In the CCT, a neutral object (usually a pen) is rubbed against an inherently disgusting object (e.g. a toilet paper with feces) and participants are asked how contaminated this pen is on a scale from 0 (n…

Tuning chiral anomaly signature in a Dirac semimetal via fast-ion implantation
Manasi Mandal, Eunbi Rha, Abhijatmedhi Chotrattanapituk, Denisse C\'ordova Carrizales, Alexander Lygo, Kevin B. Woller, Mouyang Cheng, Ryotaro Okabe, Guomin Zhu, Kiran Mak, Chu-Liang Fu, Chuhang Liu, Lijun Wu, Yimei Zhu, Susanne Stemmer, Mingda Li
https://ar…

Tuning chiral anomaly signature in a Dirac semimetal via fast-ion implantation
Cd$_3$As$_2$ is a prototypical Dirac semimetal that hosts a chiral anomaly and thereby functions as a platform to test high-energy physics hypotheses and to realize energy efficient applications. Here we use a combination of accelerator-based fast ion implantation and theory-driven planning to enhance the negative longitudinal magnetoresistance (NLMR)--a signature of a chiral anomaly--in Nb-doped Cd$_3$As$_2$ thin films. High-energy ion implantation is commonly used to investigate semiconductor…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Bootstrap-based tests for the total time on test and the excess wealth orders
Tommaso Lando, Sirio Legramanti

CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts
Olaf D\"unkel, Artur Jesslen, Jiahao Xie, Christian Theobalt, Christian Rupprecht, Adam Kortylewski
https://arxiv.org/abs/2507.17651

CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts
An important challenge when using computer vision models in the real world is to evaluate their performance in potential out-of-distribution (OOD) scenarios. While simple synthetic corruptions are commonly applied to test OOD robustness, they often fail to capture nuisance shifts that occur in the real world. Recently, diffusion models have been applied to generate realistic images for benchmarking, but they are restricted to binary nuisance shifts. In this work, we introduce CNS-Bench, a Conti…

Helium recovery system at IB3A
D. Porwisiak (Fermi National Accelerator Laboratory, Wroclaw University of Science and Technology), M. J. White (Fermi National Accelerator Laboratory), B. J. Hansen (Fermi National Accelerator Laboratory)
https://arxiv.org/abs/2507.17538

Helium recovery system at IB3A
The growing demand for sustainable cryogenic operations at Fermilab has underscored the need to improve helium management, particularly at the Industrial Building 3A (IB3A) test facility. IB3A characterizes and tests superconductors, cables, and coils for projects such as the HL-LHC AUP and Mu2e, yet currently relies on 500 L Dewars whose boil-off is vented to atmosphere, wasting a critical, non-renewable resource and increasing the cost of testing. A project is therefore under way to link IB3A…

Bayesian Social Deduction with Graph-Informed Language Models
Shahab Rahimirad, Guven Gergerli, Lucia Romero, Angela Qian, Matthew Lyle Olson, Simon Stepputtis, Joseph Campbell
https://arxiv.org/abs/2506.17788

Bayesian Social Deduction with Graph-Informed Language Models
Social reasoning - inferring unobservable beliefs and intentions from partial observations of other agents - remains a challenging task for large language models (LLMs). We evaluate the limits of current reasoning language models in the social deduction game Avalon and find that while the largest models demonstrate strong performance, they require extensive test-time inference and degrade sharply when distilled to smaller, real-time-capable variants. To address this, we introduce a hybrid reaso…

Orthogonal Wavelet Bases on Generalized Vilenkin Groups
M. Babushkin, M. Skopina
https://arxiv.org/abs/2506.17677 https://arxiv.org/p…

Orthogonal Wavelet Bases on Generalized Vilenkin Groups
Wavelet systems on the generalized Vilenkin groups are considered. An algorithmic method for the construction of orthogonal wavelet bases is presented. These bases consist of compactly supported test functions (i.e. functions whose Fourier transform is also compactly supported).

Normal modes and shockwaves in cold atoms
Francisco Raposo, Hugo Ter\c{c}as
https://arxiv.org/abs/2506.17404 https://arxiv.org/pdf/25…

Normal modes and shockwaves in cold atoms
Numerical methods are developed to simulate the dynamics of atoms in a Magneto-Optic Trap (MOT), based on the fluid description of ultracold gases under laser cooling and magnetic trapping forces. With this model, equilibrium hydrostatic profiles and normal modes are calculated, and numerical results are validated against theoretical predictions. As a test case, shock wave formation due to rapid gas expansion and contraction of the ultracold gas is simulated. The latter is caused by a sudden ch…

A Jarque-Bera test for skew normal data
Diam Ba, Gorgui Gning, Gandasor Bonyiri Onesiphore Da, Oumar Foly Sow, Gane Samb Lo
https://arxiv.org/abs/2507.18032 https://

A Jarque-Bera test for skew normal data
The skew normal law has been introduced in Azzalin (1985) as an alternative to adjusting asymmetric data that share important patterns with the normal law. It has been extensively studied. However, there is so much to do in order to catch the diversity and the richness of the investigation of its normal counterpart. The General Jarque-Berra Test (GJBT) has been devised by Lo et al. (2015), Da et al. (2023) for arbitrary laws with at least finite first eight moments, as a generalization of the J…

Self-selection of Information and Belief Update: An Experiment on COVID-19 Vaccine Information Acquisition
ChienHsun Lin, Hans H. Tung
https://arxiv.org/abs/2506.19056

Self-selection of Information and Belief Update: An Experiment on COVID-19 Vaccine Information Acquisition
Rational information acquisition theory predicts that people select the more informative information. Thus, people's beliefs will be more persuaded by the information they select. We test the prediction in a critical real-world context -- information about COVID-19 vaccines. We conducted an online experiment in Taiwan where the subjects selected information about COVID-19 vaccines, and then the subjects updated their beliefs about vaccine effectiveness and references to vaccines. As our design …

Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
Ahmadreza Saboor Yaraghi, Golnaz Gharachorlu, Sakina Fatima, Lionel C. Briand, Ruiyuan Wan, Ruifeng Gao
https://arxiv.org/abs/2506.19045

Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
Fault localization (FL) is a critical step in debugging which typically relies on repeated executions to pinpoint faulty code regions. However, repeated executions can be impractical in the presence of non-deterministic failures or high execution costs. While recent efforts have leveraged Large Language Models (LLMs) to aid execution-free FL, these have primarily focused on identifying faults in the system under test (SUT) rather than in the often complex system test code. However, the latter i…

The surprising strength of weak classifiers for validating neural posterior estimates
Vansh Bansal, Tianyu Chen, James G. Scott
https://arxiv.org/abs/2507.17026

The surprising strength of weak classifiers for validating neural posterior estimates
Neural Posterior Estimation (NPE) has emerged as a powerful approach for amortized Bayesian inference when the true posterior $p(θ\mid y)$ is intractable or difficult to sample. But evaluating the accuracy of neural posterior estimates remains challenging, with existing methods suffering from major limitations. One appealing and widely used method is the classifier two-sample test (C2ST), where a classifier is trained to distinguish samples from the true posterior $p(θ\mid y)$ versus the lear…

Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances
Chase Stokes, Kylie Lin, Cindy Xiong Bearfield
https://arxiv.org/abs/2507.17024 https://

Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances
A growing body of work on visualization affordances highlights how specific design choices shape reader takeaways from information visualizations. However, mapping the relationship between design choices and reader conclusions often requires labor-intensive crowdsourced studies, generating large corpora of free-response text for analysis. To address this challenge, we explored alternative scalable research methodologies to assess chart affordances. We test four elicitation methods from human-su…

Proportional Sensitivity in Generative Adversarial Network (GAN)-Augmented Brain Tumor Classification Using Convolutional Neural Network
Mahin Montasir Afif, Abdullah Al Noman, K. M. Tahsin Kabir, Md. Mortuza Ahmmed, Md. Mostafizur Rahman, Mufti Mahmud, Md. Ashraful Babu
https://arxiv.org/abs/2506.17165

Proportional Sensitivity in Generative Adversarial Network (GAN)-Augmented Brain Tumor Classification Using Convolutional Neural Network
Generative Adversarial Networks (GAN) have shown potential in expanding limited medical imaging datasets. This study explores how different ratios of GAN-generated and real brain tumor MRI images impact the performance of a CNN in classifying healthy vs. tumorous scans. A DCGAN was used to create synthetic images which were mixed with real ones at various ratios to train a custom CNN. The CNN was then evaluated on a separate real-world test set. Our results indicate that the model maintains hig…

Rigidity and positivity of Hawking quasi-local energy on area-constrained critical surfaces
Alejandro Pe\~nuela Diaz
https://arxiv.org/abs/2507.16588 https…

Rigidity and positivity of Hawking quasi-local energy on area-constrained critical surfaces
A key test for any quasi-local energy in general relativity is that it be nonnegative and satisfy a rigidity property; if it vanishes, the region enclosed is flat. We show that the Hawking energy, when evaluated on its natural area-constrained critical surfaces, henceforth called "Hawking surfaces", satisfies both properties under the dominant energy condition. In the time-symmetric case, where Hawking surfaces coincide with area-constrained Willmore surfaces, we extend positivity and rigidity …

Parametric Resonance in the Non-Autonomous Sine-Gordon Model
Tomasz Dobrowolski, Jacek Gatlik, Zofia Bry{\l}owska, Panayotis G. Kevrekidis
https://arxiv.org/abs/2507.17837 https…

Parametric Resonance in the Non-Autonomous Sine-Gordon Model
The sine-Gordon model is studied with model parameters that depend on both space and time. An effective model with one degree of freedom is constructed, allowing the description of the kink movement in both a temporally non-autonomous and spatially inhomogeneous setting. As a highly demanding test of the reduced model, the case of a temporal drive leading to a parametric instability is considered. Here, the boundaries of the instability region in the form of Arnold tongues were examined in both…

Magnetic braking and dynamo evolution of $\beta$ Hydri
A. R. G. Santos, T. S. Metcalfe, O. Kochukhov, T. R. Ayres, R. Gafeira, T. L. Campante
https://arxiv.org/abs/2506.17049

Magnetic braking and dynamo evolution of $β$ Hydri
The evolution of magnetic braking and dynamo processes in subgiant stars is essential for understanding how these stars lose angular momentum. We investigate the magnetic braking and dynamo evolution of $β$ Hydri, a G-type subgiant, to test the hypothesis of weakened magnetic braking and the potential rejuvenation of large-scale magnetic fields. We analyze spectropolarimetric observations from HARPS (HARPSpol; polarimetric mode of High Accuracy Radial velocity Planet Searcher), and combine the…

Updated constraints on modified gravity from binary pulsars
S. Bussieres, M. Caldarola, S. Nesseris
https://arxiv.org/abs/2507.18188 https://arxiv.org/pdf/…

Updated constraints on modified gravity from binary pulsars
Binary pulsars offer a unique natural laboratory to test General Relativity (GR) and probe for deviations from its paradigm, as predicted by alternative theories of gravity. In this paper, we study two such possible deviations: a time variation of Newton's constant $G$ and the emission of dipolar gravitational radiation. We use updated data for some well-known pulsars, namely PSR J1738+0333, PSR J1012+5307, and PSR J1713+0747, to extract the Keplerian and post-Keplerian parameters that characte…

A Numerical Study on Gauge Symmetry of Electroweak Amplitudes
Wang-Fa Li, Junmou Chen, Qian-Jiu Wang, Zhao-Huan Yu
https://arxiv.org/abs/2507.17429 https:/…

A Numerical Study on Gauge Symmetry of Electroweak Amplitudes
Electroweak (EW) amplitudes in the gauge-Goldstone 5-component formalism have a distinctive property: gauge symmetry is imprinted in the amplitudes, manifested as the massive Ward identity (MWI) $k^M\mathcal M_M=0$. In this paper, we use the HELAS package to numerically study gauge symmetry in EW amplitudes. First, we directly test gauge symmetry by examining the MWI of amplitudes. Second, we modify the couplings within a vertex and of vertices to check if and how the MWI changes. Third, we tes…

Seed&Steer: Guiding Large Language Models with Compilable Prefix and Branch Signals for Unit Test Generation
Shuaiyu Zhou, Zhengran Zeng, Xiaoling Zhou, Rui Xie, Shikun Zhang, Wei Ye
https://arxiv.org/abs/2507.17271

Seed&Steer: Guiding Large Language Models with Compilable Prefix and Branch Signals for Unit Test Generation
Unit tests play a vital role in the software development lifecycle. Recent advances in Large Language Model (LLM)-based approaches have significantly improved automated test generation, garnering attention from both academia and industry. We revisit LLM-based unit test generation from a novel perspective by decoupling prefix generation and assertion generation. To characterize their respective challenges, we define Initialization Complexity and adopt Cyclomatic Complexity to measure the difficu…

A detailed simulation model for fifth generation district heating and cooling networks with seasonal latent storage evaluated on field data
Manuel Kollmar, Adrian B\"urger, Markus Bohlayer, Angelika Altmann-Dieses, Marco Braun, Moritz Diehl
https://arxiv.org/abs/2506.18528

A detailed simulation model for fifth generation district heating and cooling networks with seasonal latent storage evaluated on field data
Fifth generation district heating and cooling (5GDHC) networks accelerate the use of renewable energies in the heating sector and enable flexible, efficient and future-proof heating and cooling supply via a single network. Due to their low temperature level and high integration of renewables, 5GDHC systems pose new challenges for the modeling of these networks in order to simulate and test operational strategies. A particular feature is the use of uninsulated pipes, which allow energy exchange …

GW231123: a product of successive mergers from $\sim 10 $ stellar-mass black holes
Yin-Jie Li, Shan-Peng Tang, Ling-Qin Xue, Yi-Zhong Fan
https://arxiv.org/abs/2507.17551 https:…

GW231123: a product of successive mergers from $\sim 10 $ stellar-mass black holes
GW231123 is an exceptionally massive binary black hole (BBH) merger with unusually high component spins. Such extreme properties challenge conventional stellar evolution models predicting a black hole mass gap due to pair-instability supernovae. We analyze GW231123 using population-informed priors on BH mass and spin distributions to test possible formation scenarios: first-generation stellar collapse, hierarchical (multi-generation) mergers, and primordial origin. Our analysis strongly prefers…

Implications of the recent neutron decay measurements on the properties of compact objects -- a dark star with nucleonic shell ?
M. Veselsk\'y, V. Petousis, Ch. C. Moustakidis, M. Vikiaris
https://arxiv.org/abs/2507.17340

Implications of the recent neutron decay measurements on the properties of compact objects -- a dark star with nucleonic shell ?
Recent experimental observation suggests that neutron decay is always accompanied by emission of electron while in 1% of cases proton is not emitted. We develop a scenario kinematically compatible with experimental observation, where neutron decay results in production of two dark matter particles of about half the mass of neutron and test properties of neutron stars with admixture of such particles. Constraints on mass and coupling to vector dark boson are obtained. The structure of the compac…

Software Model Checking via Summary-Guided Search (Extended Version)
Ruijie Fang, Zachary Kincaid, Thomas Reps
https://arxiv.org/abs/2508.15137 https://arx…

Software Model Checking via Summary-Guided Search (Extended Version)
In this work, we describe a new software model-checking algorithm called GPS. GPS treats the task of model checking a program as a directed search of the program states, guided by a compositional, summary-based static analysis. The summaries produced by static analysis are used both to prune away infeasible paths and to drive test generation to reach new, unexplored program states. GPS can find both proofs of safety and counter-examples to safety (i.e., inputs that trigger bugs), and features a…

Cosmic Distance Duality Relation with DESI DR2 and Transparency
Xuwei Zhang, Xiaofeng Yang, Yunliang Ren, Shuangnan Chen, Yangjun Shi, Cheng Cheng, Xiaolong He
https://arxiv.org/abs/2506.17926

Cosmic Distance Duality Relation with DESI DR2 and Transparency
The Cosmic Distance Duality Relation (CDDR), a fundamental assumption in modern cosmology, posits a direct link between angular diameter distance and luminosity distance. This study presents a comprehensive, model-independent, and data-driven test of the CDDR using a combination of cosmological observations, including Supernovae (SN), Baryon Acoustic Oscillations (BAO), and Hubble parameter ($H(z)$) measurements. We employ both Gaussian Process Regression (GPR) and a novel Compressed Point (CPI…

High-Speed Boulders and the Debris Field in DART Ejecta
Tony L. Farnham (University of Maryland, Department of Astronomy), Jessica M. Sunshine (University of Maryland, Department of Astronomy, University of Maryland, Department of Geology), Masatoshi Hirabayashi (Daniel Guggenheim School of Aerospace Engineering, Georgia Institute of Technology), Carolyn M. Ernst (Johns Hopkins University Applied Physics Laboratory), R. Terik Daly (Johns Hopkins University Applied Physics Laboratory), …

High-Speed Boulders and the Debris Field in DART Ejecta
On 26 September 2022 the Double Asteroid Redirection Test (DART) spacecraft collided with Dimorphos, the moon of the near-Earth asteroid 65803 Didymos, in a full-scale demonstration of a kinetic impactor concept. The companion LICIACube spacecraft documented the aftermath, capturing images of the expansion and evolution of the ejecta from 29 to 243 s after the impact. We present results from our analyses of these observations, including an improved reduction of the data and new absolute calibra…

The completeness of the open cluster census towards the Galactic anticentre
Emily L. Hunt, Tristan Cantat-Gaudin, Friedrich Anders, Lorenzo Spina, Lorenzo Cavallo, Alfred Castro-Ginard, Vasily Belokurov, Anthony G. A. Brown, Andrew R. Casey, Ronald Drimmel, Morgan Fouesneau, Sabine Reffert
https://arxiv.org/abs/2506.18708…

The completeness of the open cluster census towards the Galactic anticentre
Open clusters have long been used as tracers of Galactic structure. However, without a selection function to describe the completeness of the cluster census, it is difficult to quantitatively interpret their distribution. We create a method to empirically determine the selection function of a Galactic cluster catalogue. We test it by investigating the completeness of the cluster census in the outer Milky Way, where old and young clusters exhibit different spatial distributions. We develop a met…

Likelihood Ratio test for Poisson graph
Chen Shuyan, Liu Xin, Wang Shaoli
https://arxiv.org/abs/2506.18778 https://arxiv.org/pdf/2506…

Likelihood Ratio test for Poisson graph
Directed acyclic graphs are widely used to describe the causal effects among random variables, and the inference of those causal effects has become an popular topic in statistics and machine learning, and has wide applications in neuroinformatics, bioinformatics and so on. However, most studies focus on the estimation or inference of the directional relations among continuous random variables, those among discrete random variables have not gained much attentions. In this article we focus on the…

Characterization of Lateral Amorphous Selenium Photodetectors for Low-Photon and VUV Detection at Cryogenic Temperatures
M. Rooks, S. Abbaszadeh, J. Asaadi, V. A. Chirayath, M. Febbraro, M. \'A. Garc\'ia-Peris, E. Gramellini, K. Hellier, B. Sudarsan, I. Tzoka
https://arxiv.org/abs/2507.18497

Characterization of Lateral Amorphous Selenium Photodetectors for Low-Photon and VUV Detection at Cryogenic Temperatures
The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, …

Use Property-Based Testing to Bridge LLM Code Generation and Validation
Lehan He, Zeren Chen, Zhe Zhang, Jing Shao, Xiang Gao, Lu Sheng
https://arxiv.org/abs/2506.18315

Use Property-Based Testing to Bridge LLM Code Generation and Validation
Large Language Models (LLMs) excel at code generation, but ensuring their outputs to be functionally correct, especially in complex programming tasks, is a persistent challenge. While traditional Test-Driven Development (TDD) offers a path for code refinement, its efficacy with LLMs is often undermined by the scarcity of high-quality test cases or the pitfalls of automated test generation, including biased tests or inaccurate output predictions that can misdirect the correction process. This pa…

Greybody factors in Horndeski gravity and beyond
Georgios Antoniou, Thomas D. Pappas, Panagiota Kanti
https://arxiv.org/abs/2507.17329 https://arxiv.org/pd…

Greybody factors in Horndeski gravity and beyond
In the framework of the beyond Horndeski action, we consider three sub-theories, that support scalarised black-hole solutions, and look for modified characteristics compared to GR. We first study the propagation of massless scalar and vector test fields in the fixed background of an analytical spherically-symmetric black hole derived in the context of a parity-symmetric beyond Horndeski theory, and show that the profiles of the effective gravitational potentials, greybody factors, absorption cr…

Quantifying the Impact of 2D and 3D BAO Measurements on the Cosmic Distance Duality Relation with HII Galaxy observation
Jie Zheng (HNAS), Da-Chun Qiang (HNAS), Zhi-Qiang You (HNAS), Darshan Kumar (HNAS)
https://arxiv.org/abs/2507.17113

Quantifying the Impact of 2D and 3D BAO Measurements on the Cosmic Distance Duality Relation with HII Galaxy observation
The cosmic distance duality relation (CDDR) is a fundamental and practical condition in observational cosmology that connects the luminosity distance and angular diameter distance. Testing its validity offers a powerful tool to probe new physics beyond the standard cosmological model. In this work, for the first time, we present a novel consistency test of CDDR by combining HII galaxy data with a comprehensive set of Baryon Acoustic Oscillations (BAO) measurements. The BAO measurements include …

Testing Against Tree Ordered Alternatives in One-way ANOVA
Subha Halder, Anjana Mondal, Somesh Kumar
https://arxiv.org/abs/2507.17229 https://arxiv.org/pdf…

Testing Against Tree Ordered Alternatives in One-way ANOVA
The likelihood ratio test against a tree ordered alternative in one-way heteroscedastic ANOVA is considered for the first time. Bootstrap is used to implement this and two multiple comparisons based tests and shown to have very good size and power performance. In this paper, the problem of testing the homogeneity of mean effects against the tree ordered alternative is considered in the heteroscedastic one-way ANOVA model. The likelihood ratio test and two multiple comparison-based tests - nam…

A Fisher's exact test justification of the TF-IDF term-weighting scheme
Paul Sheridan, Zeyad Ahmed, Aitazaz A. Farooque
https://arxiv.org/abs/2507.15742

A Fisher's exact test justification of the TF-IDF term-weighting scheme
Term frequency-inverse document frequency, or TF-IDF for short, is arguably the most celebrated mathematical expression in the history of information retrieval. Conceived as a simple heuristic quantifying the extent to which a given term's occurrences are concentrated in any one given document out of many, TF-IDF and its many variants are routinely used as term-weighting schemes in diverse text analysis applications. There is a growing body of scholarship dedicated to placing TF-IDF on a sound …

Bar properties as a function of wavelength in Illustris TNG50: analysis of mock images
Gustavo F. Gon\c{c}alves, Rubens E. G. Machado, Kar\'in Men\'endez-Delmestre, Thiago Bueno-Dalpiaz
https://arxiv.org/abs/2506.19373

Bar properties as a function of wavelength in Illustris TNG50: analysis of mock images
Recent studies used Illustris TNG50 galaxies to study bar formation, evolution, and properties like length, strength, and pattern speed. In simulations, these are typically derived from particle positions and mass distribution, neglecting stellar light and extinction effects. However, observational studies indicate that bar appearance depends on wavelength. To test whether this dependence exists in TNG50 at $z \sim 0$, we analysed 50 strongly barred galaxies using mock images from SKIRT radiati…

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
Youjia Zhang, Youngeun Kim, Young-Geun Choi, Hongyeob Kim, Huiling Liu, Sungeun Hong
https://arxiv.org/abs/2508.15568

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
Test-time adaptation (TTA) enhances the zero-shot robustness under distribution shifts by leveraging unlabeled test data during inference. Despite notable advances, several challenges still limit its broader applicability. First, most methods rely on backpropagation or iterative optimization, which limits scalability and hinders real-time deployment. Second, they lack explicit modeling of class-conditional feature distributions. This modeling is crucial for producing reliable decision boundarie…

Three-component Phase Separation for Ultramassive White Dwarf Models
Matias Castro-Tapia, Andrew Cumming
https://arxiv.org/abs/2506.16529 https://

Three-component Phase Separation for Ultramassive White Dwarf Models
We investigate phase separation in oxygen-neon (O/Ne) ultramassive white dwarfs (UMWDs). Current stellar evolution codes, such as MESA, only account for $\mathrm{^{16}O/^{20}Ne}$ separation and do not include other minor species. To improve this, we implement ternary phase diagrams into MESA. We construct UMWD models with O/Ne/sodium (Na) and O/Ne/magnesium (Mg) cores to test our implementation. We also assess the effect of including $\mathrm{^{22}Ne}$ in the current two-species framework. Our …

Black Hole Entropy Bounded by the Specific Heat
Kai-Peng Lu, H. Lu
https://arxiv.org/abs/2507.17812 https://arxiv.org/pdf/2507.17812

Black Hole Entropy Bounded by the Specific Heat
We propose new bounds on black hole entropy in terms of the specific heat at fixed charges. For special spherically-symmetric and static black holes ($g_{tt} g_{rr}=-1$), we prove the bounds with suitable sufficient energy conditions. For more general static and rotating black holes, we test the bounds with a variety of examples. This work extends the previously-known algebraic inequalities of the black hole thermodynamic variables such as the Penrose inequality, to include their derivatives.

On the Feasibility of Quantum Unit Testing
Andriy Miranskyy, Jos\'e Campos, Anila Mjeda, Lei Zhang, Ignacio Garc\'ia Rodr\'iguez de Guzm\'an
https://arxiv.org/abs/2507.17235

On the Feasibility of Quantum Unit Testing
The increasing complexity of quantum software presents significant challenges for software verification and validation, particularly in the context of unit testing. This work presents a comprehensive study on quantum-centric unit tests, comparing traditional statistical approaches with tests specifically designed for quantum circuits. These include tests that run only on a classical computer, such as the Statevector test, as well as those executable on quantum hardware, such as the Swap test an…

Identifying Heterogeneity in Distributed Learning
Zelin Xiao, Jia Gu, Song Xi Chen
https://arxiv.org/abs/2506.16394 https://arxiv.org…

Identifying Heterogeneity in Distributed Learning
We study methods for identifying heterogeneous parameter components in distributed M-estimation with minimal data transmission. One is based on a re-normalized Wald test, which is shown to be consistent as long as the number of distributed data blocks $K$ is of a smaller order of the minimum block sample size {and the level of heterogeneity is dense}. The second one is an extreme contrast test (ECT) based on the difference between the largest and smallest component-wise estimated parameters amo…

Tuning Random Generators: Property-Based Testing as Probabilistic Programming
Ryan Tjoa, Poorva Garg, Harrison Goldstein, Todd Millstein, Benjamin Pierce, Guy Van den Broeck
https://arxiv.org/abs/2508.14394

Tuning Random Generators: Property-Based Testing as Probabilistic Programming
Property-based testing validates software against an executable specification by evaluating it on randomly generated inputs. The standard way that PBT users generate test inputs is via generators that describe how to sample test inputs through random choices. To achieve a good distribution over test inputs, users must tune their generators, i.e., decide on the weights of these individual random choices. Unfortunately, it is very difficult to understand how to choose individual generator weights…

Precision over Noise: Tailoring S3 Public Access Detection to Reduce False Positives in Cloud Security Platforms
Dikshant, Geetika Verma
https://arxiv.org/abs/2508.14402 https:/…

Precision over Noise: Tailoring S3 Public Access Detection to Reduce False Positives in Cloud Security Platforms
Excessive and spurious alert generation by cloud security solutions is a root cause of analyst fatigue and operational inefficiencies. In this study, the long-standing issue of false positives from publicly accessible alerts in Amazon S3, as generated by a licensed cloud-native security solution, is examined. In a simulated production test environment, which consisted of over 1,000 Amazon S3 buckets with diverse access configurations, it was discovered that over 80\% of the alerts generated by …

Dynamics of tidal spiral arms: Machine learning-assisted identification of equations and application to the Milky Way
Marcel Bernet, Pau Ramos, Teresa Antoja, Adrian Price-Whelan, Steven L. Brunton, Tetsuro Asano, Alexandra Gir\'on-Soto
https://arxiv.org/abs/2506.17383

Dynamics of tidal spiral arms: Machine learning-assisted identification of equations and application to the Milky Way
Understanding the spiral arms of the Milky Way (MW) remains a key open question in galactic dynamics. Tidal perturbations, such as the recent passage of the Sagittarius dwarf galaxy (Sgr), could play a significant role in exciting them. We aim to analytically characterize the dynamics of tidally induced spiral arms, including their phase-space signatures. We ran idealized test-particle simulations resembling impulsive satellite impacts, and used the Sparse Identification of Non-linear Dynamics …

Exact, Nonparametric Sensitivity Analysis for Observational Studies of Contingency Tables
Elaine K. Chiu, Hyunseung Kang
https://arxiv.org/abs/2507.17207 https://

Exact, Nonparametric Sensitivity Analysis for Observational Studies of Contingency Tables
In observational studies, contingency tables provide a simple and intuitive approach to study associations between categorical variables. However, any test of association in contingency tables may be biased due to unmeasured confounders. Existing sensitivity analyses that assess the impact of unmeasured confounding on association tests typically assume a binary treatment variable or impose strong parametric assumptions on the non-binary treatment variable. We overcome these limitations with an …

GRB 241105A: A test case for GRB classification and rapid r-process nucleosynthesis channels
Dimple, B. P. Gompertz, A. J. Levan, D. B. Malesani, T. Laskar, S. Bala, A. A. Chrimes, K. Heintz, L. Izzo, G. P. Lamb, D. O'Neill, J. T. Palmerio, A. Saccardi, G. E. Anderson, C. De Barra, Y. Huang, A. Kumar, H. Li, S. McBreen, O. Mukherjee, S. R. Oates, U. Pathak, Y. Qiu, O. J. Roberts, R. Sonawane, P. Veres, K. Ackley, X. Han, Y. Julakanti, J. Wang, P. D'Avanzo, A. Martin-Carrillo, M…

GRB 241105A: A test case for GRB classification and rapid r-process nucleosynthesis channels
Gamma-ray bursts (GRBs) offer a powerful window to probe the progenitor systems responsible for the formation of heavy elements through the rapid neutron capture (r-) process, thanks to their exceptional luminosity, which allows them to be observed across vast cosmic distances. GRB 241105A, observed at a redshift of z = 2.681, features a short initial spike (1.5 s) and a prolonged weak emission lasting about 64 s, positioning it as a candidate for a compact binary merger and potentially marking…

Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection
Shuang Song, Yang Tang, Rongjun Qin
https://arxiv.org/abs/2507.16657

Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection
Deep learning has significantly advanced building segmentation in remote sensing, yet models struggle to generalize on data of diverse geographic regions due to variations in city layouts and the distribution of building types, sizes and locations. However, the amount of time-consuming annotated data for capturing worldwide diversity may never catch up with the demands of increasingly data-hungry models. Thus, we propose a novel approach: re-training models at test time using synthetic data tai…

Breaking Barriers in Software Testing: The Power of AI-Driven Automation
Saba Naqvi, Mohammad Baqar
https://arxiv.org/abs/2508.16025 https://arxiv.org/pdf/…

Breaking Barriers in Software Testing: The Power of AI-Driven Automation
Software testing remains critical for ensuring reliability, yet traditional approaches are slow, costly, and prone to gaps in coverage. This paper presents an AI-driven framework that automates test case generation and validation using natural language processing (NLP), reinforcement learning (RL), and predictive models, embedded within a policy-driven trust and fairness model. The approach translates natural language requirements into executable tests, continuously optimizes them through learn…

Theoretical modeling of QCD radiation in off-shell Higgs production through gluon fusion
Rafael Coelho Lopes de S\'a, Martina Javurkova, Matteo Lazzeretti, Raoul R\"ontsch
https://arxiv.org/abs/2506.17022

Theoretical modeling of QCD radiation in off-shell Higgs production through gluon fusion
The measurement of the Higgs boson width is a critical test of the Standard Model, with significant implications for understanding electroweak symmetry breaking. Direct measurements are limited by detector resolution, but it can be measured with greater precision through a combined analysis of on-shell and off-shell Higgs boson production. While results for on-shell production have been computed to a very high accuracy, theoretical predictions for off-shell Higgs boson production are not as wel…

NiceWebRL: a Python library for human subject experiments with reinforcement learning environments
Wilka Carvalho, Vikram Goddla, Ishaan Sinha, Hoon Shin, Kunal Jha
https://arxiv.org/abs/2508.15693

NiceWebRL: a Python library for human subject experiments with reinforcement learning environments
We present NiceWebRL, a research tool that enables researchers to use machine reinforcement learning (RL) environments for online human subject experiments. NiceWebRL is a Python library that allows any Jax-based environment to be transformed into an online interface, supporting both single-agent and multi-agent environments. As such, NiceWebRL enables AI researchers to compare their algorithms to human performance, cognitive scientists to test ML algorithms as theories for human cognition, and…

From simulations to observations. Methodology and data release of mock TNG50 galaxies at 0.3 < z < 0.7 for WEAVE-StePS
A. Ikhsanova, L. Costantin, A. Pizzella, E. M. Corsini, L. Morelli, F. R. Ditrani, A. Ferr\'e-Mateu, L. Gabarra, M. Gullieuszik, C. P. Haines, A. Iovino, M. Longhetti, A. Mercurio, R. Ragusa, P. S\'anchez-Bl\'azquez, C. Tortora, B. Vulcani, S. Zhou, E. Gafton, F. Pistis

From simulations to observations. Methodology and data release of mock TNG50 galaxies at 0.3 < z < 0.7 for WEAVE-StePS
The new generation of optical spectrographs (i.e., WEAVE, 4MOST, DESI, and WST) offer unprecedented opportunities for statistically studying the star formation histories of galaxies. However, these observations are not easily comparable to predictions from cosmological simulations. Our goal is to build a reference framework for comparing spectroscopic observations with simulations and test tools for deriving stellar population properties of galaxies. We focus on the observational strategy of th…

Generating and Understanding Tests via Path-Aware Symbolic Execution with LLMs
Yaoxuan Wu, Xiaojie Zhou, Ahmad Humayun, Muhammad Ali Gulzar, Miryung Kim
https://arxiv.org/abs/2506.19287

Generating and Understanding Tests via Path-Aware Symbolic Execution with LLMs
Symbolic execution is a widely used technique for test generation, offering systematic exploration of program paths through constraint solving. However, it is fundamentally constrained by the capability to model the target code including library functions in terms of symbolic constraint and the capability of underlying constraint solvers. As a result, many paths involving complex features remain unanalyzed or insufficiently modeled. Recent advances in large language models (LLMs) have shown pro…

DialogueForge: LLM Simulation of Human-Chatbot Dialogue
Ruizhe Zhu, Hao Zhu, Yaxuan Li, Syang Zhou, Shijing Cai, Malgorzata Lazuka, Elliott Ash
https://arxiv.org/abs/2507.15752

DialogueForge: LLM Simulation of Human-Chatbot Dialogue
Collecting human-chatbot dialogues typically demands substantial manual effort and is time-consuming, which limits and poses challenges for research on conversational AI. In this work, we propose DialogueForge - a framework for generating AI-simulated conversations in human-chatbot style. To initialize each generated conversation, DialogueForge uses seed prompts extracted from real human-chatbot interactions. We test a variety of LLMs to simulate the human chatbot user, ranging from state-of-th…

Test beam measurements and computer simulations of the ATLAS ITk R2 silicon strip detector
Jan-Hendrik Arling, Pavol Federic, Yajun He, Cole Michael Helling, Nigel Hessey, Lennart Huth, Geetika Jain, Callan Jessiman, Sebastian Manson, Luise Poley, John Stakely Keller, Jiri Kroll, Jiri Kvasnicka, Radek Privara, Peter Speers, Pavel Tuma
https://…

Test beam measurements and computer simulations of the ATLAS ITk R2 silicon strip detector
The ATLAS Inner Tracker, the future innermost part of the ATLAS detector, is an all-silicon tracker composed of pixel and strip modules, designed to cope with the extreme conditions expected during High-Luminosity LHC runs. Thorough testing of modules during the individual phases of their development is critical to ensure the required performance level of the whole tracker. This document presents results obtained from electron beam measurements of the ATLAS ITk R2 end-cap strip module. Key perf…

An Empirical Study of Complexity, Heterogeneity, and Compliance of GitHub Actions Workflows
Edward Abrokwah, Taher A. Ghaleb
https://arxiv.org/abs/2507.18062 https://

An Empirical Study of Complexity, Heterogeneity, and Compliance of GitHub Actions Workflows
Continuous Integration (CI) has evolved from a tooling strategy to a fundamental mindset in modern CI engineering. It enables teams to develop, test, and deliver software rapidly and collaboratively. Among CI services, GitHub Actions (GHA) has emerged as a dominant service due to its deep integration with GitHub and a vast ecosystem of reusable workflow actions. Although GHA provides official documentation and community-supported best practices, there appears to be limited empirical understandi…

GenAI for Automotive Software Development: From Requirements to Wheels
Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari, Krzysztof Lebioda, Andre Schamschurko, Alois Knoll
https://arxiv.org/abs/2507.18223

GenAI for Automotive Software Development: From Requirements to Wheels
This paper introduces a GenAI-empowered approach to automated development of automotive software, with emphasis on autonomous and Advanced Driver Assistance Systems (ADAS) capabilities. The process starts with requirements as input, while the main generated outputs are test scenario code for simulation environment, together with implementation of desired ADAS capabilities targeting hardware platform of the vehicle connected to testbench. Moreover, we introduce additional steps for requirements …

Can GRB Empirical Correlations Be Used for Population Studies?
Emre S. Yorgancioglu, Yun-Fei Du, Shu-Xu Yi, Shuang-Nan Zhang
https://arxiv.org/abs/2507.16192

Can GRB Empirical Correlations Be Used for Population Studies?
Only a small fraction of Gamma-ray bursts (GRBs) have independent redshift measurements, which are essential for understanding their intrinsic properties. For this reason, empirical correlations of GRBs have often been touted as useful distance indicators, for both individual GRBs as well as population studies. Building upon our previous work, we test the ability of the Yonetoku, 3D Dainotti, and the L-T-E correlation to adequately constrain the GRB rate, $Ψ_{GRB}$. Our analysis demonstrates t…

Metamorphic Coverage
Jinsheng Ba, Yuancheng Jiang, Manuel Rigger
https://arxiv.org/abs/2508.16307 https://arxiv.org/pdf/2508.16307

Metamorphic Coverage
Metamorphic testing is a widely used methodology that examines an expected relation between pairs of executions to automatically find bugs, such as correctness bugs. We found that code coverage cannot accurately measure the extent to which code is validated and mutation testing is computationally expensive for evaluating metamorphic testing methods. In this work, we propose Metamorphic Coverage (MC), a coverage metric that examines the distinct code executed by pairs of test inputs within metam…

Forecast constraints on null tests of the $\Lambda$CDM model with SPHEREx
Alejandro Mata Rom\'an, Indira Ocampo, Savvas Nesseris
https://arxiv.org/abs/2507.16604

Forecast constraints on null tests of the $Λ$CDM model with SPHEREx
In this work we quantify the ability of the upcoming SPHEREx survey to constrain cosmological observables and test the internal consistency of the cosmological constant and cold dark matter ($Λ$CDM) model. Using Fisher matrix forecasting, we assess the expected precision on Baryon Acoustic Oscillations (BAO) observables, such as the angular diameter distance $D_\mathrm{A}(z)$ and the Hubble parameter $H(z)$. We further explore SPHEREx's potential to probe some of the fundamental assumptions of…

AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
Zihan Wang, Jiaze Chen, Zhicheng Liu, Markus Mak, Yidi Du, Geonsik Moon, Luoqi Xu, Aaron Tua, Kunshuo Peng, Jiayi Lu, Mingfei Xia, Boqian Zou, Chenyang Ran, Guang Tian, Shoutai Zhu, Yeheng Duan, Zhenghui Kang, Zhenxing Lin, Shangshu Li, Qiang Luo, Qingshen Long, Zhiyong Chen, Yihan Xiao, Yurong Wu, Daoguang Zan, Yuyi Fu, Mingxuan Wang, Ming Ding

AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on existing benchmarks, we argue that current evaluations overstate model proficiency, masking a substantial gap between LLMs and elite human programmers. This gap arises from two key limitations: insufficient difficulty and scope of benchmark problems, and evaluation bias from low-quality test cases. To address these short…

DINOv3 with Test-Time Training for Medical Image Registration
Shansong Wang, Mojtaba Safari, Mingzhe Hu, Qiang Li, Chih-Wei Chang, Richard LJ Qiu, Xiaofeng Yang
https://arxiv.org/abs/2508.14809

DINOv3 with Test-Time Training for Medical Image Registration
Prior medical image registration approaches, particularly learning-based methods, often require large amounts of training data, which constrains clinical adoption. To overcome this limitation, we propose a training-free pipeline that relies on a frozen DINOv3 encoder and test-time optimization of the deformation field in feature space. Across two representative benchmarks, the method is accurate and yields regular deformations. On Abdomen MR-CT, it attained the best mean Dice score (DSC) of 0.7…

Observational Constraints on Scalar Field--Matter Interaction in Weyl Integrable Spacetime
Andronikos Paliathanasis
https://arxiv.org/abs/2506.16223 https:…

Observational Constraints on Scalar Field--Matter Interaction in Weyl Integrable Spacetime
We test an analytic cosmological solution within the framework of Weyl Integrable Spacetime using current observational data. In this model, dark energy is described by a pressureless fluid, while a scalar field arises naturally through the definition of the connection. This gravitational theory reveals a Chameleon Mechanism leading to a nonzero interaction between the scalar field and the matter sector. This model extends the standard $Λ$CDM cosmology by introducing one additional degree of f…

Improving Compiler Bug Isolation by Leveraging Large Language Models
Yixian Qi, Jiajun Jiang, Fengjie Li, Bowen Chen, Hongyu Zhang, Junjie Chen
https://arxiv.org/abs/2506.17647

Improving Compiler Bug Isolation by Leveraging Large Language Models
Compilers play a foundational role in building reliable software systems, and bugs within them can lead to catastrophic consequences. The compilation process typically involves hundreds of files, making traditional automated bug isolation techniques inapplicable due to scalability or effectiveness issues. Current mainstream compiler bug localization techniques have limitations in test program mutation and resource consumption. Inspired by the recent advances of pre-trained Large Language Models…

Testing gravitational physics by combining DESI DR1 and weak lensing datasets using the E_G estimator
S. J. Rauhut, C. Blake, U. Andrade, H. E. Noriega, J. Aguilar, S. Ahlen, S. BenZvi, D. Bianchi, D. Brooks, T. Claybaugh, A. Cuceu, A. de la Macorra, J. DeRose, P. Doel, N. Emas, S. Ferraro, J. E. Forero-Romero, C. Garcia-Quintero, E. Gazta\~naga, G. Gutierrez, S. Heydenreich, K. Honscheid, C. Howlett, D. Huterer, M. Ishak, S. Joudaki, R. Joyce, E. Jullo, R. Kehoe, D. Kirkby, A. Kremin,…

Testing gravitational physics by combining DESI DR1 and weak lensing datasets using the E_G estimator
The action of gravitational physics across space-time creates observable signatures in the behaviour of light and matter. We perform combined-probe studies using data from the Baryon Oscillation Spectroscopic Survey (BOSS) and Dark Energy Spectroscopic Instrument survey Data Release 1 (DESI-DR1), in combination with three existing weak lensing surveys, to test and constrain General Relativity (GR) in the context of the standard model of cosmology (LCDM). We focus on measuring the gravitational …

One Membrane to Love them all: Tidal deformations of compact objects from the membrane paradigm
Michela Silvestrini, Elisa Maggio, Sumanta Chakraborty, Paolo Pani
https://arxiv.org/abs/2506.16516

One Membrane to Love them all: Tidal deformations of compact objects from the membrane paradigm
The tidal deformability is a key observable to test the nature of compact objects in a binary coalescence. Within vacuum General Relativity, the tidal Love numbers of a four-dimensional black hole are strictly zero, while they are non-zero and model-dependent for material objects, matter distributions around black holes, or in alternative theories of gravity. Here, we develop a model-agnostic framework based on the membrane paradigm, where the tidal properties of a spherically symmetric object …

Leveraging Optimal Transport for Distributed Two-Sample Testing: An Integrated Transportation Distance-based Framework
Zhengqi Lin, Yan Chen
https://arxiv.org/abs/2506.16047

Leveraging Optimal Transport for Distributed Two-Sample Testing: An Integrated Transportation Distance-based Framework
This paper introduces a novel framework for distributed two-sample testing using the Integrated Transportation Distance (ITD), an extension of the Optimal Transport distance. The approach addresses the challenges of detecting distributional changes in decentralized learning or federated learning environments, where data privacy and heterogeneity are significant concerns. We provide theoretical foundations for the ITD, including convergence properties and asymptotic behavior. A permutation test …

Testing Quantum-Corrected Black Holes with QPOs Observations: A Study of Particle Dynamics and Accretion Flow
G. Mustafa, Sushant G. Ghosh, Orhan Donmez, S. K. Maurya, Shakhzod Orzuev, Farruh Atamurotov
https://arxiv.org/abs/2506.16405

Testing Quantum-Corrected Black Holes with QPOs Observations: A Study of Particle Dynamics and Accretion Flow
We study the epicyclic oscillations of test particles around rotating quantum-corrected black holes (QCBHs), characterized by mass $M$, spin $a$, and quantum deformation parameter $b$. By deriving the radial ($Ω_r$) and vertical ($Ω_θ$) oscillation frequencies, we explore their dependence on spacetime parameters and show that quantum corrections ($b \neq 0$) significantly modify the dynamics compared to the classical Kerr case. Through numerical modelling of accretion around QCBHs, we furthe…

An exact test for the mixed membership stochastic block model
Sourav Majumdar
https://arxiv.org/abs/2507.14464 https://arxiv.org/pdf/…

An exact test for the mixed membership stochastic block model
We present the first finite-sample goodness-of-fit test for the mixed membership stochastic block model (MMSBM). Using algebraic statistics theory, we derive a Markov basis that lets a Metropolis-Hastings sampler explore exactly the set of networks compatible with a fitted MMSBM. The resulting exact $p$-value, based on a partial conjunction statistic, requires no asymptotic approximations. Simulations show nominal size and strong power against misspecified block numbers and connection patterns.

Quasi-normal modes and shadows of scale-dependent regular black holes
Benjamin Koch, Gonzalo J. Olmo, Ali Riahinia, \'Angel Rinc\'on, Diego Rubiera-Garcia
https://arxiv.org/abs/2506.15944

Quasi-normal modes and shadows of scale-dependent regular black holes
In this paper we investigate how a regular scale-dependent black hole, characterized by a single extra parameter $ε$, behaves under perturbations by a test field (quasi-normal modes) and under light imaging (shadows) in a four-dimensional space-time background. On the quasi-normal modes side, we study how it responds to scalar and Dirac perturbations. To do this, we implement the well known WKB semi-analytic method of 6th order for obtaining the quasi-normal frequencies. We discuss the behavio…

Constraining parameters of spinor field dark energy: An alternative to $\Lambda$CDM model under the spherically symmetric FLRW space-time
Bijan Saha, Mahendra Goray
https://arxiv.org/abs/2506.16323

Constraining parameters of spinor field dark energy: An alternative to $Λ$CDM model under the spherically symmetric FLRW space-time
This study constrains the cosmological parameters within the scope of a spherically symmetric FLRW cosmological model, the role of a nonlinear spinor field in the universe's evolution. To test this approach, we incorporate the recent Cosmic chronometers, Supernova, and Sloan Digital Sky Survey data. It is found that if spherical coordinates give the FLRW model, the energy-momentum tensor (EMT) of the spinor field possesses nontrivial non-diagonal components. These non-diagonal components of EMT…

Behavior Driven Development for 3D Games
Fernando Pastor Ric\'os, Beatriz Mar\'in, I. S. W. B. Prasetya, Tanja E. J. Vos, Joseph Davidson, Karel Hovorka
https://arxiv.org/abs/2506.17057

Behavior Driven Development for 3D Games
Computer 3D games are complex software environments that require novel testing processes to ensure high-quality standards. The Intelligent Verification/Validation for Extended Reality Based Systems (iv4XR) framework addresses this need by enabling the implementation of autonomous agents to automate game testing scenarios. This framework facilitates the automation of regression test cases for complex 3D games like Space Engineers. Nevertheless, the technical expertise required to define test scr…

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Robin Lee, Youngho Nam
https://arxiv.org/abs/2507.14687

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Modified Condition/Decision Coverage (MC/DC) is a mandatory structural coverage criterion for ensuring the reliability and safety of critical systems. While its strictest form, Unique-Cause MC/DC, offers the highest assurance, research on its efficient test generation has been lacking. This gap is particularly significant, as an analysis of large-scale avionics systems shows that 99.7% of all conditional decisions are, in fact, Singular Boolean Expressions (SBEs) the ideal structure for applyin…

Input Reduction Enhanced LLM-based Program Repair
Boyang Yang, Luyao Ren, Xin Yin, Jiadong Ren, Haoye Tian, Shunfu Jin
https://arxiv.org/abs/2507.15251 htt…

Input Reduction Enhanced LLM-based Program Repair
Large Language Models (LLMs) have shown great potential in Automated Program Repair (APR). Test inputs, being crucial for reasoning the root cause of failures, are always included in the prompt for LLM-based APR. Unfortunately, LLMs struggle to retain key information in long prompts. When the test inputs are extensive in the prompt, this may trigger the "lost-in-the-middle" issue, compromising repair performance. To address this, we propose ReduceFix, an LLM-based APR approach with a built-in c…