Skip to content

Category

software testing

3,195 papers

#artificial intelligence Open access Oct 2026

Beat and view aggregation rules for tricuspid regurgitant jet dimensions: simulation code and results

Code, configurations, seeds, results and figures for a Monte Carlo simulation study of composite multi-beat, multi-view transoesophageal echocardiographic measurement rules for tricuspid regurgitant jet dimensions (beat averaging, percentage beat-consistency windows, largest view mean, millimetre cross-view triggers) a...

Kardokh Kakabra · 0 citations
#software testing Review Open access Oct 2026

Programming Is a Real-Time Strategy (RTS) Game Now

Software development is moving away from writing code line by line. Instead of using AI only for simple autocomplete, developers now manage multiple coding agents across different parts of a codebase at once. While these tools make individual tasks faster, recent data shows that teams are generating far more code witho...

Vipin Singh, Susmita Singh · 0 citations
#software testing Book Open access Oct 2026

Enabling Passive Localization with a Single Moving Receiver through Periodic 5G Reference Signals

Passive Time Difference of Arrival (TDoA) localization conventionally requires multiple synchronized receivers to obtain spatially diverse observations. In this paper, we show that the periodic nature of the 5G NR downlink Positioning Reference Signals (PRS), combined with receiver motion, provides an alternative sourc...

Marco Tricco, Samuele Zanini, Giuseppe Bianchi et al. · 0 citations
#software testing Book Open access Nov 2026

DroneFuzz: Detecting Cyber-Physical Peripheral Vulnerabilities via MAVLink Fuzzing

Robotic vehicles, such as Unmanned Aerial Vehicles (UAVs), are deployed in safety-critical applications ranging from package delivery to search and rescue operations. In these cyber-physical systems, software vulnerabilities can cause physical consequences such as collisions and mission failures, giving them direct saf...

Ashwin Nambiar, Shafiq-us Saleheen, Antonio Bianchi · 0 citations
#software testing Book Open access Oct 2026

Catching Developers in the Flow: Low-Latency Agentic Program Repair at Google Scale

FlowAgent is an AI agent deployed at Google to automatically repair test failures in the pre-submit outer-loop workflow inside continuous integration systems, using a ReAct-style generate-and-validate loop and rigorous pre-execution and post-execution abstention filters to ensure high-quality suggestions under strict l...

Celal Ziftci, Spencer Greene, Raymond Liu et al. · 0 citations
#software testing Preprint Oct 2026

SIGMA: Self-Improving Alignment Generalization from a Model Spec

SIGMA is proposed, a data generation and training pipeline enabling alignment self-improvement that generalizes to out-of-distribution settings and shows that a Model Spec balancing harmlessness and helpfulness, test-time reasoning for safety deliberation, and high-quality rubrics from SIGMA's task designer agent are c...

Jing-Yu Zhang, Shruti Palaskar, Daniel Khashabi et al. · 0 citations
#software testing Review Oct 2026

A Case Study in Assuring AI-Written Software

A case study of a production healthcare platform built through coding agents and governed by an operator without formal software-engineering training, which found that tests, monitors and reviewing agents used to supervise the system were fallible.

Lindsey M. Ferris, Sierra Bonilla · 0 citations
#software testing Preprint Oct 2026

Learning from Failures: A Failure-Driven Prompt Refinement for LLM-Based Vulnerability Analysis

This work proposes Failure-Driven Prompt Refinement (FDPR), a methodology that analyzes recurring model failures to guide evidence-based prompt refinement, and shows that failure-driven refinement improves the reliability of LLM-based vulnerability analysis while yielding reusable prompt design principles.

Mandana Ghadamian, David Mohaisen · 0 citations

Universal Prenatal cfDNA-Single Gene Disorder Screening for Autosomal Dominant Conditions in a Low-Risk Cohort: A Cost-Effectiveness Analysis.

OBJECTIVE The use of cell free fetal DNA has expanded to include autosomal dominant single gene conditions (cfDNA-SGD). Our aim is to estimate the cost-effectiveness of a cfDNA-SGD panel in a general obstetric population as compared to offering this test only in the setting of anomalies. METHODS Using TreeAge softwar...

M. Bunnell, Claire Packer, Sophie Adams et al. · 0 citations
#software testing Open access Oct 2026

Association of 18F-FDG PET/CT Radiomics with Tumor Molecular Features in Breast Cancer

Objectives This study aims to investigate the potential relationship between radiomic features extracted from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of patients with breast cancer and molecular markers including estrogen receptor (ER), progesterone receptor (...

Busra Aydur Puren, Semra Usta, Y. Salihoğlu et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, existing agents remain brittle on long-horizon workflows, where they must repeatedly reconstruct program state scattered across source files, configurations, tests, depende...

Hai-Bo Jin, Xin-Jie Li, Peng Kuang et al. · 0 citations
#machine learning Preprint Oct 2026

Beyond the Leaderboard: Multi-Dimensional Evaluation of Dense and Mixture-of-Experts Models for Automated Program Repair

Automated Program Repair (APR) with language models is usually evaluated by whether a generated patch passes the test suite, which can hide differences in maintainability, security, and computational cost. We propose a Weighted Quality Index (QI), inspired by the ISO/IEC 25010 software quality model, that combines func...

Anvit Shah, B. UmamaheswaraSharma · 0 citations

From tech blogs

See all →
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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.