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software testing

2,999 papers

#software testing Open access Sep 2026

Effect of diode laser and hyaluronic acid on occlusion of dentinal tubules: an in-vitro study on human dentin

The combination of hyaluronic acid and diode laser demonstrated the most pronounced occluding effect, indicating enhanced efficacy compared with the individual treatments, but given the surface-based and laboratory nature of the assessment, further in vivo studies are required to confirm the clinical relevance and long...

Riham Hisham Mahmoud, Basma Mohamed, R. Safy et al. · 0 citations
#software testing Open access Sep 2026

Arnold's Bifurcation Principle Applied to Optical Network Soft-Failure Early Warning

Optical transport networks– the fiber links carrying telecom and data-center traffic– can develop “soft failures”: a slowly aging amplifier, a worn connector, or a degrading splice that gradually weakens the signal long before it fails outright. Today’s protection mechanism only reacts once the signal quality has alrea...

PRAKASH VAITHYANATHAN · 0 citations
#software testing Open access Sep 2026

OpenOmicsBench

Compact, traceable transcriptomics objects for software testing, teaching and method development.

Vivaan Patni · 0 citations
#software testing Open access Sep 2026

Reproducibility Package for "The Potential of the THESEUS Mission for Studies of Young Stellar Objects"

This Zenodo record contains the reproducibility package accompanying the manuscript “The Potential of the THESEUS Mission for Studies of Young Stellar Objects” by Juhasz et al. The archive includes the Python/PyXspec scripts, selected public input data, machine-readable numerical outputs, and documentation required to...

Á. L. Juhász · 0 citations
#software testing Dataset Open access Sep 2026

CANARY: Jenkins Plugin Security-Advisory Forecasting — Dataset and Model Artifacts (v0.1.17)

Labeled plugin-month datasets, trained model artifacts, and evaluation outputs for CANARY, a public-data-first framework for forecasting security advisories in the Jenkins plugin ecosystem. The master dataset covers 2,053 plugins as monthly observations (2018-01 to 2026-06 in this version); each row carries features co...

Timothy Brennan · 0 citations
#software testing Open access Sep 2026

The Early Evolution of Deep Space Navigation

An existing series of papers has described the evolution of deep space navigation over the time interval 1962 to 2021. This paper complements the series by examining a broad range of prior or contemporaneous events, starting in the post-war years, that contributed to the successful navigation of NASA’s planetary missio...

L. Wood · 0 citations
#software testing Open access Sep 2026

Mathematical Materiality: a status report

MATHEMATICAL MATERIALITY (NUMERI) Physics from a different starting point Ugo Lanciano | Deposit 2.27 | English presentation - version 6 MM invites readers to explore a possibility: space, time and mass could arise from more elementary relationships. The challenge is to follow this hypothesis through to its verifiable...

Ugo Lanciano · 0 citations
#software testing Open access Sep 2026

Reproducibility package for Leakage-Conscious Machine Learning for Supplied Injury-Risk Label Classification and Longitudinal Injury Forecasting: A Multi-Dataset Evaluation

This record provides the reproducibility materials associated with the study “Leakage-Conscious Machine Learning for Supplied Injury-Risk Label Classification and Longitudinal Injury Forecasting: A Multi-Dataset Evaluation”. The materials include the executed and clean primary-analysis notebooks, Python scripts, fixed...

Abdülkadir Enes GÖRGÜLÜ, Eray Dursun, Serdar Solak · 0 citations
#software testing Open access Sep 2026

Execution Governance for Physical AI

Execution Governance for Physical AI v1.1.0 presents a cumulative EG1–EG6 research profile for governing consequential physical effects produced by robots, autonomous machines, smart spaces, vehicles, drones, industrial automation, and other cyber-physical systems. Physical AI moves AI-mediated decisions across a bound...

Ho Wa Ku · 0 citations
#software testing Open access Sep 2026

Reproducibility Scripts for "The Naive–Power Law Blend as a Robust Baseline for Bitcoin Price Forecasting"

Reproducibility scripts and data for the paper "The Naive–Power Law Blend as a Robust Baseline for Bitcoin Price Forecasting" by Carlos Baquero and Daniel Tinoco. This package contains all evaluation scripts, Bitcoin price data, and on-chain activity signals needed to reproduce the paper's results, including: the multi...

Carlos Baquero · 0 citations
#software testing Open access Sep 2026

AIRFOIL DESIGN OPTIMIZATION USING MULTI FIDELITY AT LOW REYNOLDS NUMBER FOR FIXED WING UAV

A methodology is given to choose an airfoil for a fixed wing UAV, and evaluate based on the mission constraints, and to efficiently optimize the airfoil by using multi-fidelity software such as XFLR5 and ANSYS FLUENT. The analysis solvers are validated for the wind tunnel test data of E387 and CAL2463m airfoil. Then, t...

Preety Kumari, Ashok Kuppusamy, Arnob Das Rudra · 0 citations
#software testing Open access Sep 2026

CAD machine-learning selection stability: analysis code

Code-only archive for the manuscript on the stability of machine-learning algorithm, feature and hyperparameter selection across random training-test splits in a coronary artery disease cohort. The archive contains selected analysis sources, recorded environment requirements, English-directory path-adaptation and prove...

Meng Li, Xiuze Zhang, Juan Bai et al. · 0 citations

From tech blogs

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Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

MIT News · Artificial Intelligence Oct 2, 2026

Documenting the tech worker movement

Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.

MIT News · Artificial Intelligence Oct 2, 2026

Documenting the tech worker movement

Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.

GPT-Lab Sep 23, 2026

Requirements Don’t Live in Isolation: What We’re Exploring with Req-Space

Requirements in large systems rarely exist in isolation. Their meaning depends on the wider project context - other requirements, policies, decisions, tests, and implementation details. That becomes especially important when AI is used for review, because spotting a possible conflict or gap is only the beginning. ReqSpace explores how AI, visualisation, and connected project context can help reviewers understand those findings, trace the relationships behind them, and focus on the questions that…

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