Tootfinder

Computer scientists: The Turing test is a test of a machine's ability to exhibit intelligent behavior equivalent to that of a human.
Reality: The Turing test is a test of a human's ability not to be fooled by themselves that a machine is mimicking a human.
(Because the test uses a human to decide if something else is a human, it essentially explores the gullibility limit of an individual human—and says nothing about machine intelligence.)

heise | 12 zu 1: Thunderbolt-5-Dock von Ugreen im Test
Das Revodok Max U715 macht aus einem Thunderbolt-5-Anschluss zwölf unterschiedliche Ports.
https://www.heise.de/tests/12-zu-1-Thunder

Getting there with SpacemiT K1x image building in @… :
running 2 tests
test starfive::visionfive2_hdr::test_hdr ... ok
test spacemit::k1x_hdr::sign ... ok
test result: ok. 2 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s
Alright, time for some fresh air!

JS-TOD: Detecting Order-Dependent Flaky Tests in Jest
Negar Hashemi, Amjed Tahir, Shawn Rasheed, August Shi, Rachel Blagojevic
https://arxiv.org/abs/2509.00466 https://

JS-TOD: Detecting Order-Dependent Flaky Tests in Jest
We present JS-TOD (JavaScript Test Order-dependency Detector), a tool that can extract, reorder, and rerun Jest tests to reveal possible order-dependent test flakiness. Test order dependency is one of the leading causes of test flakiness. Ideally, each test should operate in isolation and yield consistent results no matter the sequence in which tests are run. However, in practice, test outcomes can vary depending on their execution order. JS-TOD employed a systematic approach to randomising tes…

At 1:09 a.m. EDT on November 2,
SpaceX launched a Falcon 9 rocket from Cape Canaveral, carrying Haven Demo and 17 other satellites,
including ones that will be operated by South Korea's Agency for Defense Development (ADD),
the Berlin-based company Exolaunch,
Turkey's Fergani Space,
and U.S. weather-forecasting outfit Tomorrow Companies,
and Starcloud, which carried an NVIDIA H100 AI chip to see if it’s possible to build an artificial intelligence-…

Elon Musk Launches Satellite To Test Systems For Private Space Station
SpaceX launched 18 satellites, including Haven Demo, a key test for the world's first private space station.

RE: https://bayerwald.social/@system/115480126050005923
Test Test Test Test ..... Zitierfunktion.

Test
test
https://www.andreas-edler.de/blog/2025/09/test/

ADVMEM: Adversarial Memory Initialization for Realistic Test-Time Adaptation via Tracklet-Based Benchmarking
Shyma Alhuwaider, Motasem Alfarra, Juan C. Perez, Merey Ramazanova, Bernard Ghanem
https://arxiv.org/abs/2509.02182

ADVMEM: Adversarial Memory Initialization for Realistic Test-Time Adaptation via Tracklet-Based Benchmarking
We introduce a novel tracklet-based dataset for benchmarking test-time adaptation (TTA) methods. The aim of this dataset is to mimic the intricate challenges encountered in real-world environments such as images captured by hand-held cameras, self-driving cars, etc. The current benchmarks for TTA focus on how models face distribution shifts, when deployed, and on violations to the customary independent-and-identically-distributed (i.i.d.) assumption in machine learning. Yet, these benchmarks fa…

Omg, there is a new Simon the Sourcerer game?
https://stadt-bremerhaven.de/simon-the-sorcerer-origins-im-test-prequel-des-klassikers-will-erneut-verzaubern/

Simon the Sorcerer Origins im Test: Prequel des Klassikers will erneut verzaubern
Um den Charakter Simon the Sorcerer zu kennen, muss man wahrscheinlich ein Kind der 1980er- oder der 1990er-Jahre sein. Das erste Spiel der ...

Normality and the Turing Test
Alexandre Kabbach
https://arxiv.org/abs/2508.21382 https://arxiv.org/pdf/2508.21382…

Normality and the Turing Test
This paper proposes to revisit the Turing test through the concept of normality. Its core argument is that the statistical interpretation of the normal--understood as the average both in the normative and mathematical sense of the term--proves useful for understanding the Turing test in at least two ways. First, in the sense that the Turing test targets normal/average rather than exceptional human intelligence, so that successfully passing the test requires building machines that "make mistakes…

🚀 Powering a path to Mars with reactor test bed
#space

Powering a path to Mars with reactor test bed
Nuclear energy is a leading option to power space exploration, but its success depends on reactors that can operate autonomously rather than relying on human operators in space.

@… Tangential but you may find it interesting: In Kent Beck’s book on Test Driven Development one of the examples is to build your own testing framework in Python, using that very same framework to test the code for the framework you are writing.
It was so much fun to do. I could imagine a parallel where you build a CI service, using the same to deploy changes to yo…

To Remember, To Adapt, To Preempt: A Stable Continual Test-Time Adaptation Framework for Remote Physiological Measurement in Dynamic Domain Shifts
Shuyang Chu, Jingang Shi, Xu Cheng, Haoyu Chen, Xin Liu, Jian Xu, Guoying Zhao
https://arxiv.org/abs/2510.01282

To Remember, To Adapt, To Preempt: A Stable Continual Test-Time Adaptation Framework for Remote Physiological Measurement in Dynamic Domain Shifts
Remote photoplethysmography (rPPG) aims to extract non-contact physiological signals from facial videos and has shown great potential. However, existing rPPG approaches struggle to bridge the gap between source and target domains. Recent test-time adaptation (TTA) solutions typically optimize rPPG model for the incoming test videos using self-training loss under an unrealistic assumption that the target domain remains stationary. However, time-varying factors like weather and lighting in dynami…

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Litu Rout, Andreas Lugmayr, Yasamin Jafarian, Srivatsan Varadharajan, Constantine Caramanis, Sanjay Shakkottai, Ira Kemelmacher-Shlizerman
https://arxiv.org/abs/2510.02291

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
We study the problem of posterior sampling using pretrained discrete diffusion foundation models, aiming to recover images from noisy measurements without retraining task-specific models. While diffusion models have achieved remarkable success in generative modeling, most advances rely on continuous Gaussian diffusion. In contrast, discrete diffusion offers a unified framework for jointly modeling categorical data such as text and images. Beyond unification, discrete diffusion provides faster i…

heise | Reale Ort in VR-Umgebungen verwandeln: "Meta Hyperscape" für Quest 3 im Test
Mit "Meta Hyperscape" lassen sich aus echten Räumen fotorealistische VR-Umgebungen erschaffen. Wir haben das in Innenräumen und im Freien ausprobiert.

Test-Time Search in Neural Graph Coarsening Procedures for the Capacitated Vehicle Routing Problem
Yoonju Sim, Hyeonah Kim, Changhyun Kwon
https://arxiv.org/abs/2510.00958 https…

Test-Time Search in Neural Graph Coarsening Procedures for the Capacitated Vehicle Routing Problem
The identification of valid inequalities, such as the rounded capacity inequalities (RCIs), is a key component of cutting plane methods for the Capacitated Vehicle Routing Problem (CVRP). While a deep learning-based separation method can learn to find high-quality cuts, our analysis reveals that the model produces fewer cuts than expected because it is insufficiently sensitive to generate a diverse set of generated subsets. This paper proposes an alternative: enhancing the performance of a trai…

«if you have to choose a “pedia” to trust, you might choose the one assembled by a bunch of pedantic nerds saying “well, ACTUALLY” to each other until the heat death of the universe, over the one assembled by an LLM controlled by an insecure Nazi salute-throwing billionaire»
A Review of Grokipedia, Using Myself as Test Subject | Whatever
https://whatever.scalzi.com/2025/10/30/a-review-of-grokipedia-using-myself-as-test-subject/

Pete Carroll vs. Mike Vrabel: Raiders Face Brutal Week 1 Test In Foxborough https://raiderramble.com/2025/09/01/pete-carroll-vs-mike-vrabel-raiders-face-brutal-week-1-test-in-foxborough/

Test your NFL knowledge with our Connections: Sports Edition team-themed games https://www.nytimes.com/athletic/6592714/2025/09/03/connections-sports-edition-nfl-team-games/

Just posted a public test build of OmniDiskSweeper 1.16:
https://omnistaging.omnigroup.com/omnidisksweeper/
• Accessible Sizes — Each file now provides an accessibility title (e.g. “Desktop"), an accessibility value describing its size (e.g. “need permission to fully…

Sources: Apple plans an AI search tool, World Knowledge Answers, for spring 2026 as part of a Siri revamp; Apple and Google plan to test a Google model for Siri (Mark Gurman/Bloomberg)
https://www.bloomberg.com/news/articles/20

Licht und Dashcam am Rad
https://www.spiegel.de/tests/fahrrad-zubehoer/dashcam-garmin-varia-vue-und-varia-rct716-im-test-das-taugt-der-videobeweis-fuer-fahrraeder-a…

Garmin-Leuchten mit Dashcam im Test: Das taugt der Videobeweis für Fahrräder
Garmin kombiniert Fahrradlampen mit Videokameras und Radar. Das soll für mehr Sicherheit sorgen und nach einem Unfall helfen, die Schuldfrage zu klären. Im Test mussten dafür Fahrräder zu Boden gehen.

My non-exhaustive test of @… triggered through @ap.brid.gy bridge between Bluesky and Fediverse has these results:
Bluesky reply to Fediverse post = no joy

Test time training enhances in-context learning of nonlinear functions
Kento Kuwataka, Taiji Suzuki
https://arxiv.org/abs/2509.25741 https://arxiv.org/pdf/…

Test time training enhances in-context learning of nonlinear functions
Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test data. While TTT has demonstrated considerable empirical success, its theoretical underpinnings remain limited, particularly for nonlinear models. In this paper, we investigate the combination of TTT with in-context learning (ICL), where the model is given a few examples from the target distribution at inference time. We analyze this framework in the sett…

Improving Electroencephalogram-Based Deception Detection in Concealed Information Test under Low Stimulus Heterogeneity
Suhye Kim, Jaehoon Cheon, Taehee Kim, Seok Chan Kim, Chang-Hwan Im
https://arxiv.org/abs/2509.02234

Improving Electroencephalogram-Based Deception Detection in Concealed Information Test under Low Stimulus Heterogeneity
The concealed information test (CIT) is widely used for detecting deception in criminal investigations, primarily leveraging the P300 component of electroencephalogram (EEG) signals. However, the traditional bootstrapped amplitude difference (BAD) method struggles to accurately differentiate deceptive individuals from innocent ones when irrelevant stimuli carry familiarity or inherent meaning, thus limiting its practical applicability in real-world investigations. This study aimed to enhance th…

Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition
Jiahang Cao, Yize Huang, Hanzhong Guo, Rui Zhang, Mu Nan, Weijian Mai, Jiaxu Wang, Hao Cheng, Jingkai Sun, Gang Han, Wen Zhao, Qiang Zhang, Yijie Guo, Qihao Zheng, Chunfeng Song, Xiao Li, Ping Luo, Andrew F. Luo
https://

Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition
Diffusion-based models for robotic control, including vision-language-action (VLA) and vision-action (VA) policies, have demonstrated significant capabilities. Yet their advancement is constrained by the high cost of acquiring large-scale interaction datasets. This work introduces an alternative paradigm for enhancing policy performance without additional model training. Perhaps surprisingly, we demonstrate that the composed policies can exceed the performance of either parent policy. Our contr…

Bayesian Estimation and Regularization Techniques in Categorical Data Analysis
Jan Kalina
https://arxiv.org/abs/2509.02222 https://arxiv.org/pdf/2509.02222…

Bayesian Estimation and Regularization Techniques in Categorical Data Analysis
This paper explores Bayesian estimation for categorical data, focusing on simple yet effective models that provide a foundation for applying more advanced methods accurately and reliably in real-world applications. We begin by revisiting Bayesian estimators for the binomial distribution and investigating their properties. Next, we develop hypothesis tests for categorical data (sign test, homogeneity test, symmetry test) based on regularized maximum likelihood estimates of the probabilities. Fin…

Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang, Dong Wang, Jianyi Zhou, Junjie Chen
https://arxiv.org/abs/2510.01994 https:/…

Clarifying Semantics of In-Context Examples for Unit Test Generation
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context examples significantly influences the effectiveness of generated tests-poorly structured or semantically unclear test examples often lead to suboptimal outputs. In this paper, we propose CLAST, a novel technique that systematically refines unit tests to improve their semantic clarity, thereby enhancing their utility as i…

Progress! Got the STM32H750 test board to the point of being able to light up some LEDs on GPIOs before jumping into an infinite loop.
Next step will be all of the RCC and PWR config to get it operational at the desired VOS and clock configuration, at which point I can start thinking about bringing up a UART.
But that will probably have to wait till tomorrow given that it's 1 in the morning and I have work tomorrow.

from my link log —
R0ML’s ratio bozo test: Is your volume discount a good deal? Who nose!
https://blog.glyph.im/2025/08/r0mls-ratio.html
saved 2025-08-10

SynthGenNet: a self-supervised approach for test-time generalization using synthetic multi-source domain mixing of street view images
Pushpendra Dhakara, Prachi Chachodhia, Vaibhav Kumar
https://arxiv.org/abs/2509.02287

SynthGenNet: a self-supervised approach for test-time generalization using synthetic multi-source domain mixing of street view images
Unstructured urban environments present unique challenges for scene understanding and generalization due to their complex and diverse layouts. We introduce SynthGenNet, a self-supervised student-teacher architecture designed to enable robust test-time domain generalization using synthetic multi-source imagery. Our contributions include the novel ClassMix++ algorithm, which blends labeled data from various synthetic sources while maintaining semantic integrity, enhancing model adaptability. We f…

Beam test results of the Intermediate Silicon Tracker for sPHENIX
C. W. Shih, G. Nukazuka, Y. Sugiyama, Y. Akiba, H. En'yo, T. Hachiya, S. Hasegawa, M. Hata, H. Imai, C. M. Kuo, M. Morita, I. Nakagawa, Y. Nakamura, G. Nakano, Y. Namimoto, R. Nouicer, M. Shibata, M. Shimomura, R. Takahama, K. Toho, M. Tsuruta, M. Watanabe
https://arxiv.…

Beam test results of the Intermediate Silicon Tracker for sPHENIX
The Intermediate Silicon Tracker (INTT), a two-layer barrel silicon strip tracker, is a key component of the tracking system for sPHENIX at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. The INTT is designed to enable the association of reconstructed tracks with individual RHIC bunch crossings. To evaluate the performance of preproduction INTT ladders and the readout chain, a beam test was conducted at the Research Center for Accelerator and Radioisotope Science, …

"In Deutschland stehen alle wild lebenden #Tiere unter dem allgemeinen Schutz des Bundesnaturschutzgesetzes. Das Töten ohne vernünftigen Grund ist verboten. Bei Lästlingen wie #Stubenfliegen, #Stechmücken

35-year-old former U.S. Army sergeant, Bajun “Baji” Mavalwalla II,
faces up to six years in prison
for protesting against ICE deportations
in what legal experts are calling a test case for the
Trump administration’s attempts to criminalize and punish dissent.
Mavalwalla was arrested and charged with “conspiracy to impede or injure officers”
after he was identified in a video taken at the protest and shared on Instagram.
Mavalwalla, who survived a ro…

Army Vet Charged with “Conspiracy” for ICE Protest as Trump Expands War on Dissent
A 35-year-old former U.S. Army sergeant, Bajun “Baji” Mavalwalla II, faces up to six years in prison for protesting against ICE deportations in what legal experts are calling a test case for the Trump administration’s attempts to criminalize and punish dissent. Mavalwalla was arrested and charged with “conspiracy to impede or injure officers” after he was identified in a video taken at the protest and shared on Instagram. Mavalwalla, who survived a roadside bomb blast while serving in…

I was amused that on a recent episode of Gen V that a lab-test animal (that gets turned into a blob of blood and gore) is named "Elon Musk" in order to reduce sympathy for its fate.

EMO-TTA: Improving Test-Time Adaptation of Audio-Language Models for Speech Emotion Recognition
Jiacheng Shi, Hongfei Du, Y. Alicia Hong, Ye Gao
https://arxiv.org/abs/2509.25495

EMO-TTA: Improving Test-Time Adaptation of Audio-Language Models for Speech Emotion Recognition
Speech emotion recognition (SER) with audio-language models (ALMs) remains vulnerable to distribution shifts at test time, leading to performance degradation in out-of-domain scenarios. Test-time adaptation (TTA) provides a promising solution but often relies on gradient-based updates or prompt tuning, limiting flexibility and practicality. We propose Emo-TTA, a lightweight, training-free adaptation framework that incrementally updates class-conditional statistics via an Expectation-Maximizatio…

Igår körde jag ett 5km-test. Uppvärmning 5km nerjogg. Alltihop tog 46 minuter, men halvmilen gick på facila 35:51. Pulsen höll sig stadig och låg.
Utan klockan hade jag inte kunnat hålla ordning på hur många varv jag sprungit, jag blir tankspridd när jag springer.
Det var ett väldigt trevligt besked, att jag kan tuffa runt på en idrottsplats i 7:10/km i snitt och bli tankspridd. Då går jag inte på max.
Trevligt att veta, Jönköping 10km går av stapeln den 18 oktober. Då …

alpha test period extended
👍
#FreeBSD

"Let us return to 2000: a few days before Joel Spolsky published his Test, Mark Lucovsky gave a talk titled “Windows: A Software-Engineering Odyssey” at the 4th USENIX Windows System Symposium in Seattle, Washington. He was a member of the original Windows NT team from 1988 to the mid-2000s. The PowerPoint slides of the talk are still available online, and I seriously recommend you take a look at them.
Because part of the “odyssey” was, you guessed it, source control."
…

Twenty Years Is Nothing
In a previous edition of this magazine, we argued that English was so pervasive in our industry, nobody even questioned its use anymore. The same can be said of Git. It is difficult to imagine that merely twenty years ago, the landscape of source control tools was more diverse, and the choice of one such tool was much more complicated than today. Actually, Git was not even on the map yet. Before debating whether the hegemony of Git is good or bad, let us go back in time for a little while.

Just to hammer this home a bit more, I knew a guy who joined the army. I met him after he went AWOL. When he went into the recruiter's office, they asked him if he had any open warrants out for his arrest because they couldn't recruit anyone with a criminal record. He said he did, then they said, "oh, actually, we can help you with all that, don't get caught before we ship you out."
He was just trying to keep himself out of jail. That's not supposed to happen, but it does. IIRC it was on a drug charge, which, also, they're not supposed to take anyone who tests positive for weed... but they also just tell you how to prepare for a drug test.
Another friend joined because she wanted to be part Army Corps of Engineers. A good chunk of the folks I went to school with joined the military after graduation because the other choices were working at the saw mill or working at the canary. If you join the military, you get to go to college. (Or you get to stay out of jail... as long as you don't go AWOL.)

🤾⛹️‍♂️🏃‍♂️ #DHB verlor das zweite Testspiel gegen Island vor der EM knapp und zeigte noch Schwächen – im Angriff oft zu unpräzise, in der Defensive anfällig. Das war vor zwei Tagen besser. Zehn Wochen vor dem Turnierstart in Dänemark, Schweden und Norwegen gilt: Grundordnung stärken Stabilität finden.
#Handball

Test-Time Search in Neural Graph Coarsening Procedures for the Capacitated Vehicle Routing Problem
Yoonju Sim, Hyeonah Kim, Changhyun Kwon
https://arxiv.org/abs/2510.00958 https…

Test-Time Search in Neural Graph Coarsening Procedures for the Capacitated Vehicle Routing Problem
The identification of valid inequalities, such as the rounded capacity inequalities (RCIs), is a key component of cutting plane methods for the Capacitated Vehicle Routing Problem (CVRP). While a deep learning-based separation method can learn to find high-quality cuts, our analysis reveals that the model produces fewer cuts than expected because it is insufficiently sensitive to generate a diverse set of generated subsets. This paper proposes an alternative: enhancing the performance of a trai…

nix-unit looks like a nice way to test your #nix libraries https://clan.lol/blog/nix-unit/

CodeChemist: Functional Knowledge Transfer for Low-Resource Code Generation via Test-Time Scaling
Kaixin Wang, Tianlin Li, Xiaoyu Zhang, Aishan Liu, Xianglong Liu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, and Bin Shi
https://arxiv.org/abs/2510.00501

CodeChemist: Functional Knowledge Transfer for Low-Resource Code Generation via Test-Time Scaling
Code Large Language Models (CodeLLMs) are increasingly used in code generation tasks across a wide range of applications. However, their performance is often inconsistent across different programming languages (PLs), with low-resource PLs suffering the most due to limited training data. In this paper, we present CodeChemist, a novel and efficient framework for test-time scaling that enables functional knowledge transfer from high-resource to low-resource PLs using generated test cases. CodeChem…

Test particle sampling and particle acceleration in a 2D coronal plasmoid-mediated reconnecting current sheet
Eilif S. {\O}yre, Boris V. Gudiksen, Lyndsay Fletcher
https://arxiv.org/abs/2509.25447

Test particle sampling and particle acceleration in a 2D coronal plasmoid-mediated reconnecting current sheet
Context: Solar flares accelerate electrons, creating non-thermal energy distributions. However, the acceleration sites and dominant acceleration mechanisms remain largely unknown. Aims: We study the characteristics of electron acceleration and subsequent non-thermal energy distribution in a 2D coronal plasmoid-mediated reconnecting current sheet. Methods: We used test particles and the guiding centre approximation to transport electrons in a static coronal 2D fan-spine topology magnetohydro…

Güterverkehr: Autonomer Elektro-Truck überschreitet selbstständig Grenze
Einride will den grenzüberschreitenden autonomen Güterverkehr voranbringen. In einem ersten Test zwischen Schweden und Norwegen hat das geklappt.

This Week in Sports Trivia: October 2, 2025 https://www.nytimes.com/athletic/6680446/2025/10/02/this-week-in-sports-trivia-october-2-2025/

Temu und Shein - Gefähr­liche Schnäpp­chen:
Stiftung Warentest: "Unsicheres Spielzeug, giftige Schwer­metalle in Schmuck, zu heiße Ladegeräte: Wir haben 162 Produkte von Temu und Shein getestet. 110 erfüllten nicht die EU-Stan­dards."
https://www.test.de/Temu-und-Shein-Gefaehr

Gefährliche Waren bei Temu und Shein
Die Stiftung Warentest hat bei Spielzeug, Schmuck und Elektrogeräte von Temu und Shein viele Sicherheitsmängel gefunden.

In 1934, Dorothy Thompson, wife of Sinclair Lewis, became first journalist expelled from #Hitler's Germany, after interviewing him and finding him "the very prototype of the little man "
By 1941, she'd written an influential WWII era essay that has stood the test of time, on who amongst us makes a likely #Nazi

With newly approved maps in Texas, GOP puts its gains with Latinos to the test (Claudia Grisales/NPR)
https://www.npr.org/2025/08/29/nx-s1-5512661/a-newly-approved-redistricting-plan-will-test-the-texas-gops-reach-with-latinos
http://www.memeorandum.com/250830/p4#a250830p4

Astounded to discover someone unaware that there's a UK national alert test scheduled for Sunday. Which indicates what kind of weird bubble I live in.

SK Hynix and ASML say they assembled the industry's first Twinscan NXE:5200B High-NA EUV lithography system at SK's M16 fab, initially to test next-gen tech (Anton Shilov/Tom's Hardware)
https://www.tomshard…

ASML and SK hynix assemble industry-first 'commercial' High-NA EUV system at fab in South Korea
Initially for R&D use, until later this decade where it will transition to production

This fediverse post is designed to test a bot running on Bluesky that can add alt text to images.
This post will have 2 replies, one from the fediverse and one from Bluesky, trying to trigger the bot.
This image in this post does not have alt text included with it by design.
#testing

Panic, Terror, and Near Drowning: Ban the Forced Swim Test #AnimalRights

Panic, Terror, and Near Drowning: Ban the Forced Swim Test
Pharma giant Novartis supports putting mice and rats in water-filled containers from which they desperately try to escape.

heise | Bildaufhübscher: Elgato Facecam 4K im Test
Mit Wechselfiltern und hoher Bildqualität will Elgatos Facecam 4K Streamer überzeugen. Wie schlägt sie sich gegenüber der Konkurrenz?
https://www.

8 coax lanes, DC - 70 GHz, solderless compression fit... *drool*
https://www.hubersuhner.com/en/newsroom/blog-and-literature/blog/introducing-mxpd70-the-next-step-in-multicoax-test-solut…

Searching for Difficult-to-Translate Test Examples at Scale
Wenda Xu, Vil\'em Zouhar, Parker Riley, Mara Finkelstein, Markus Freitag, Daniel Deutsch
https://arxiv.org/abs/2509.26619

Searching for Difficult-to-Translate Test Examples at Scale
NLP models require test data that are sufficiently challenging. The difficulty of an example is linked to the topic it originates from (''seed topic''). The relationship between the topic and the difficulty of its instances is stochastic in nature: an example about a difficult topic can happen to be easy, and vice versa. At the scale of the Internet, there are tens of thousands of potential topics, and finding the most difficult one by drawing and evaluating a large number of examples across al…

from my link log —
Golang cryptographic assembly mutation testing.
https://words.filippo.io/assembly-mutation/
saved 2025-07-31 http…

Go Assembly Mutation Testing
Test coverage of delicate Go cryptographic assembly through a new mutation testing framework.

DriveQA: Passing the Driving Knowledge Test
Maolin Wei, Wanzhou Liu, Eshed Ohn-Bar
https://arxiv.org/abs/2508.21824 https://arxiv.org/pdf/2508.21824…

DriveQA: Passing the Driving Knowledge Test
If a Large Language Model (LLM) were to take a driving knowledge test today, would it pass? Beyond standard spatial and visual question-answering (QA) tasks on current autonomous driving benchmarks, driving knowledge tests require a complete understanding of all traffic rules, signage, and right-of-way principles. To pass this test, human drivers must discern various edge cases that rarely appear in real-world datasets. In this work, we present DriveQA, an extensive open-source text and vision-…

Methodology for Test Case Allocation based on a Formalized ODD
Martin Skoglund, Fredrik Warg, Anders Thoren, Sasikumar Punnekkat, Hans Hansson
https://arxiv.org/abs/2509.02311 h…

Methodology for Test Case Allocation based on a Formalized ODD
The emergence of Connected, Cooperative, and Automated Mobility (CCAM) systems has significantly transformed the safety assessment landscape. Because they integrate automated vehicle functions beyond those managed by a human driver, new methods are required to evaluate their safety. Approaches that compile evidence from multiple test environments have been proposed for type-approval and similar evaluations, emphasizing scenario coverage within the systems Operational Design Domain (ODD). Howeve…

heise | Heizlüfter mit Bitcoin-Miner: Ofen 2 im Test
Bitcoins schürfen und damit kostengünstig die Wohnung heizen: Das verspricht der Bitcoin-Heizlüfter Ofen 2 von 21energy. Wir testen, ob er sich rechnet.
https://www.

Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
Connor T. Jerzak, Adel Daoud
https://arxiv.org/abs/2510.00128

Remote Auditing: Design-based Tests of Randomization, Selection, and Missingness with Broadly Accessible Satellite Imagery
Randomized controlled trials (RCTs) are the benchmark for causal inference, yet field implementation can deviate. We here present a remote audit - a design-based, preregistrable diagnostic that uses only pre-treatment satellite imagery to test whether assignment is independent of local conditions. The conditional randomization test of the remote audit evaluates whether treatment assignment is more predictable from pre-treatment satellite features than expected under the experiment's registered …

GenIA-E2ETest: A Generative AI-Based Approach for End-to-End Test Automation
Elvis J\'unior, Alan Valejo, Jorge Valverde-Rebaza, V\^ania de Oliveira Neves
https://arxiv.org/abs/2510.01024

GenIA-E2ETest: A Generative AI-Based Approach for End-to-End Test Automation
Software testing is essential to ensure system quality, but it remains time-consuming and error-prone when performed manually. Although recent advances in Large Language Models (LLMs) have enabled automated test generation, most existing solutions focus on unit testing and do not address the challenges of end-to-end (E2E) testing, which validates complete application workflows from user input to final system response. This paper introduces GenIA-E2ETest, which leverages generative AI to generat…

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Siddarth Venkatraman, Vineet Jain, Sarthak Mittal, Vedant Shah, Johan Obando-Ceron, Yoshua Bengio, Brian R. Bartoldson, Bhavya Kailkhura, Guillaume Lajoie, Glen Berseth, Nikolay Malkin, Moksh Jain
https://arxiv.org/abs/2509.26626…

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Test-time scaling methods improve the capabilities of large language models (LLMs) by increasing the amount of compute used during inference to make a prediction. Inference-time compute can be scaled in parallel by choosing among multiple independent solutions or sequentially through self-refinement. We propose Recursive Self-Aggregation (RSA), a test-time scaling method inspired by evolutionary methods that combines the benefits of both parallel and sequential scaling. Each step of RSA refines…

Vladimir Putin boasted this week that Russia has tested a
nuclear-powered super torpedo,
the Poseidon, that was unstoppable and more powerful than a nuclear missile,
the second announcement in a week of Russian trials involving
nuclear-powered weapons systems.

Days earlier, Russia announced the test of a new nuclear-powered cruise missile,
the Burevestnik or Skyfall,
that seemed in particular to irritate Donald Trump.
In the wake of the tests,…

What we know about the Poseidon, Russia’s new super torpedo
Poseidon is part of Russia’s line up of “super weapons” meant to gain military parity with the West and it can supposedly drown coastal cities.

RE: https://mastodon.social/@martinmoorland/115473837604240041
Toll! Und gleichzeitig soll dies für mich ein Test sein für die neue Zitierfunktion von Mastodon, die ich heute über das RC2 Softwarerelease eingebaut habe. Mal schauen, wie das Ganze na…

Mahomes-Allen Part X will expose fatal flaws for both contenders ahead of NFL's trade deadline

https://www.cbssports.com/nfl/news/mahomes-allen-part-x-will-expos…

Pretrain-Test Task Alignment Governs Generalization in In-Context Learning
Mary I. Letey, Jacob A. Zavatone-Veth, Yue M. Lu, Cengiz Pehlevan
https://arxiv.org/abs/2509.26551 htt…

Pretrain-Test Task Alignment Governs Generalization in In-Context Learning
In-context learning (ICL) is a central capability of Transformer models, but the structures in data that enable its emergence and govern its robustness remain poorly understood. In this work, we study how the structure of pretraining tasks governs generalization in ICL. Using a solvable model for ICL of linear regression by linear attention, we derive an exact expression for ICL generalization error in high dimensions under arbitrary pretraining-testing task covariance mismatch. This leads to a…

Text-Based Approaches to Item Alignment to Content Standards in Large-Scale Reading & Writing Tests
Yanbin Fu, Hong Jiao, Tianyi Zhou, Robert W. Lissitz, Nan Zhang, Ming Li, Qingshu Xu, Sydney Peters
https://arxiv.org/abs/2509.26431

Text-Based Approaches to Item Alignment to Content Standards in Large-Scale Reading & Writing Tests
Aligning test items to content standards is a critical step in test development to collect validity evidence based on content. Item alignment has typically been conducted by human experts. This judgmental process can be subjective and time-consuming. This study investigated the performance of fine-tuned small language models (SLMs) for automated item alignment using data from a large-scale standardized reading and writing test for college admissions. Different SLMs were trained for alignment at…

heise | Gezielt trainieren: Suunto Race 2 im Test
Suunto ergänzt bei seiner Sportuhr Race 2 ein Sprachfeedback und Trainingspläne. Wie gut ist die Fitness-Smartwatch?
https://www.heise.de/tests/Gezi…

My latest haul, for anyone interested, contains the following volumes:
Test Driven Development by Example: https://www.powells.com/book/test-driven-development-by-example-9780321146533
Building Serverless Applications on Knative:

🚁 DoorDash plans to test drone deliveries in San Francisco warehouse
https://www.latimes.com/business/story/2025-09-10/doordash-plans-to-test-drone-deliveries-in-san-francisco
🆓

DoorDash plans to test drone deliveries in San Francisco warehouse
DoorDash leased a warehouse in San Francisco last month for research and development.

Beyond Pass/Fail: The Story of Learning-Based Testing
Sheikh Md. Mushfiqur Rahman, Nasir Eisty
https://arxiv.org/abs/2510.00450 https://arxiv.org/pdf/2510.…

Beyond Pass/Fail: The Story of Learning-Based Testing
Learning-Based Testing (LBT) merges learning and testing processes to achieve both testing and behavioral adequacy. LBT utilizes active learning to infer the model of the System Under Test (SUT), enabling scalability for large and complex programs by requiring only a minimal set of initial test cases. The core principle of LBT is that the SUT's behavior can be thoroughly inferred by progressively generating test cases and subjecting the SUT to testing, thereby ensuring comprehensive testing. De…

TTT3R: 3D Reconstruction as Test-Time Training
Xingyu Chen, Yue Chen, Yuliang Xiu, Andreas Geiger, Anpei Chen
https://arxiv.org/abs/2509.26645 https://arxi…

TTT3R: 3D Reconstruction as Test-Time Training
Modern Recurrent Neural Networks have become a competitive architecture for 3D reconstruction due to their linear-time complexity. However, their performance degrades significantly when applied beyond the training context length, revealing limited length generalization. In this work, we revisit the 3D reconstruction foundation models from a Test-Time Training perspective, framing their designs as an online learning problem. Building on this perspective, we leverage the alignment confidence betw…

heise | Toniebox 2 im Test: Audioplayer mit Spielfunktion fürs Kinderzimmer
Das beliebte Hörspielsystem Toniebox ist in der zweiten Version erschienen und unterstützt erstmals auch Spiele. Dazu kommen viele Detailänderungen.
…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
Andr\'es Corrada-Emmanuel
https://arxiv.org/abs/2510.00821 https://arxiv.org/…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
If two experts disagree on a test, we may conclude both cannot be 100 per cent correct. But if they completely agree, no possible evaluation can be excluded. This asymmetry in the utility of agreements versus disagreements is explored here by formalizing a logic of unsupervised evaluation for classifiers. Its core problem is computing the set of group evaluations that are logically consistent with how we observe them agreeing and disagreeing in their decisions. Statistical summaries of their al…

LatentEvolve: Self-Evolving Test-Time Scaling in Latent Space
Guibin Zhang, Fanci Meng, Guancheng Wan, Zherui Li, Kun Wang, Zhenfei Yin, Lei Bai, Shuicheng Yan
https://arxiv.org/abs/2509.24771

LatentEvolve: Self-Evolving Test-Time Scaling in Latent Space
Test-time Scaling (TTS) has been demonstrated to significantly enhance the reasoning capabilities of Large Language Models (LLMs) during the inference phase without altering model parameters. However, existing TTS methods are largely independent, implying that LLMs have not yet evolved to progressively learn how to scale more effectively. With the objective of evolving LLMs to learn ``how to scale test-time computation,'' we propose LatentEvolve, a self-evolving latent TTS framework inspired by…

ProbTest: Unit Testing for Probabilistic Programs (Extended Version)
Katrine Christensen, Mahsa Varshosaz, Ra\'ul Pardo
https://arxiv.org/abs/2509.02012 https://

ProbTest: Unit Testing for Probabilistic Programs (Extended Version)
Testing probabilistic programs is non-trivial due to their stochastic nature. Given an input, the program may produce different outcomes depending on the underlying stochastic choices in the program. This means testing the expected outcomes of probabilistic programs requires repeated test executions unlike deterministic programs where a single execution may suffice for each test input. This raises the following question: how many times should we run a probabilistic program to effectively test i…

Trump directs Pentagon to test nuclear weapons, just before meeting China’s Xi
Donald Trump on Thursday morning said he directed the Pentagon to begin testing nuclear weapons
“on an equal basis” with Russia and China,
-- abruptly inserting nuclear issues into the discussion just before meeting his Chinese counterpart, Xi Jinping, for a high-stakes trade summit here.

The announcement signaled a reversal of decades of United States nuclear policy that could have far-re…

Trump directs Pentagon to test nuclear weapons for first time since 1992
The president said he wanted testing to occur “on an equal basis” with Russia and China, just before he met his Chinese counterpart for high-stakes trade talks.

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/5]:
- Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distr...
Cao, Huang, Guo, Zhang, Nan, Mai, Wang, Cheng, Sun, Han, Zhao, Zhang, Guo, Zheng, Song, Li, Luo, Luo
…

Reusable Test Suites for Reinforcement Learning
J{\o}rn Eirik Betten, Quentin Mazouni, Dennis Gross, Pedro Lind, Helge Spieker
https://arxiv.org/abs/2508.21553 https://

Reusable Test Suites for Reinforcement Learning
Reinforcement learning (RL) agents show great promise in solving sequential decision-making tasks. However, validating the reliability and performance of the agent policies' behavior for deployment remains challenging. Most reinforcement learning policy testing methods produce test suites tailored to the agent policy being tested, and their relevance to other policies is unclear. This work presents Multi-Policy Test Case Selection (MPTCS), a novel automated test suite selection method for RL en…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
Andr\'es Corrada-Emmanuel
https://arxiv.org/abs/2510.00821 https://arxiv.org/…

Logical Consistency Between Disagreeing Experts and Its Role in AI Safety
If two experts disagree on a test, we may conclude both cannot be 100 per cent correct. But if they completely agree, no possible evaluation can be excluded. This asymmetry in the utility of agreements versus disagreements is explored here by formalizing a logic of unsupervised evaluation for classifiers. Its core problem is computing the set of group evaluations that are logically consistent with how we observe them agreeing and disagreeing in their decisions. Statistical summaries of their al…

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
Tavor Z. Baharav, Spyros Dragazis, Aldo Pacchiano
https://arxiv.org/abs/2510.01020 https:/…

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
We study the problem of sequentially testing individuals for a binary disease outcome whose true risk is governed by an unknown logistic model. At each round, a patient arrives with feature vector $x_t$, and the decision maker may either pay to administer a (noiseless) diagnostic test--revealing the true label--or skip testing and predict the patient's disease status based on their feature vector and prior history. Our goal is to minimize the total number of costly tests required while guarante…

EQ-Robin: Generating Multiple Minimal Unique-Cause MC/DC Test Suites
Robin Lee, Youngho Nam
https://arxiv.org/abs/2509.26458 https://arxiv.org/pdf/2509.264…

EQ-Robin: Generating Multiple Minimal Unique-Cause MC/DC Test Suites
Modified Condition/Decision Coverage (MC/DC), particularly its strict Unique-Cause form, is a cornerstone of safety-critical software verification. A recent algorithm, "Robin's Rule," introduced a deterministic method to construct the theoretical minimum of N+1 test cases for Singular Boolean Expressions (SBEs). However, this approach yields only a single test suite, introducing a critical risk: if a test case forming a required 'independence pair' is an illegal input forbidden by system constr…

Entropy-Guided Loop: Achieving Reasoning through Uncertainty-Aware Generation
Andrew G. A. Correa, Ana C. H de Matos
https://arxiv.org/abs/2509.00079 https://

Entropy-Guided Loop: Achieving Reasoning through Uncertainty-Aware Generation
Reasoning models often outperform smaller models but at 3--5$\times$ higher cost and added latency. We present entropy-guided refinement: a lightweight, test-time loop that uses token-level uncertainty to trigger a single, targeted refinement pass. We extract logprobs, compute Shannon entropy on top-$k$ alternatives, and apply a simple OR-logic trigger over perplexity, maximum token entropy, and low-confidence-token count. Unlike approaches that use entropy only for measurement or decoding, we …

heise | Endlich präziser spielen: PSVR2-Controller im Test mit der Apple Vision Pro
Endlich lässt sich die Apple Vision Pro auch mit VR-Controllern bedienen. Wir haben die Unterstützung der PSVR2-Controller in Spielen und Menüs getestet.

Hues and Cues: Human vs. CLIP
Nuria Alabau-Bosque, Jorge Vila-Tom\'as, Paula Daud\'en-Oliver, Pablo Hern\'andez-C\'amara, Jose Manuel Ja\'en-Lorites, Valero Laparra, Jes\'us Malo
https://arxiv.org/abs/2509.02305

Hues and Cues: Human vs. CLIP
Playing games is inherently human, and a lot of games are created to challenge different human characteristics. However, these tasks are often left out when evaluating the human-like nature of artificial models. The objective of this work is proposing a new approach to evaluate artificial models via board games. To this effect, we test the color perception and color naming capabilities of CLIP by playing the board game Hues & Cues and assess its alignment with humans. Our experiments show that …

StockBench: Can LLM Agents Trade Stocks Profitably In Real-world Markets?
Yanxu Chen, Zijun Yao, Yantao Liu, Jin Ye, Jianing Yu, Lei Hou, Juanzi Li
https://arxiv.org/abs/2510.02209

StockBench: Can LLM Agents Trade Stocks Profitably In Real-world Markets?
Large language models (LLMs) have recently demonstrated strong capabilities as autonomous agents, showing promise in reasoning, tool use, and sequential decision-making. While prior benchmarks have evaluated LLM agents in domains such as software engineering and scientific discovery, the finance domain remains underexplored, despite its direct relevance to economic value and high-stakes decision-making. Existing financial benchmarks primarily test static knowledge through question answering, bu…

Enhancing Software Testing Education: Understanding Where Students Struggle
Shiza Andleeb, Teo Mendoza, Lucas Cordova, Gursimran Walia, Jeffrey C. Carver
https://arxiv.org/abs/2510.00957

Enhancing Software Testing Education: Understanding Where Students Struggle
Effective software testing is critical for producing reliable and secure software, yet many computer science students struggle to master the foundational concepts required to construct comprehensive test suites. While automated feedback tools are widely used to support student learning, it remains unclear which testing concepts are most frequently misunderstood and how these misunderstandings are reflected in students' test suite revisions. This study examines the specific testing concepts that…

Data-Driven Loss Functions for Inference-Time Optimization in Text-to-Image Generation
Sapir Esther Yiflach, Yuval Atzmon, Gal Chechik
https://arxiv.org/abs/2509.02295 https://

Data-Driven Loss Functions for Inference-Time Optimization in Text-to-Image Generation
Text-to-image diffusion models can generate stunning visuals, yet they often fail at tasks children find trivial--like placing a dog to the right of a teddy bear rather than to the left. When combinations get more unusual--a giraffe above an airplane--these failures become even more pronounced. Existing methods attempt to fix these spatial reasoning failures through model fine-tuning or test-time optimization with handcrafted losses that are suboptimal. Rather than imposing our assumptions abou…

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark
Minhui Zhu, Minyang Tian, Xiaocheng Yang, Tianci Zhou, Penghao Zhu, Eli Chertkov, Shengyan Liu, Yufeng Du, Lifan Yuan, Ziming Ji, Indranil Das, Junyi Cao, Yufeng Du, Jinchen He, Yifan Su, Jiabin Yu, Yikun Jiang, Yujie Zhang, Chang Liu, Ze-Min Huang, Weizhen Jia, Xinan Chen, Peixue Wu, Yunkai Wang, Juntai Zhou, Yong Zhao, Farshid Jafarpour, Jessie Shelton, Aaron Young, John Bartolotta, Wenchao Xu,…

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark
While large language models (LLMs) with reasoning capabilities are progressing rapidly on high-school math competitions and coding, can they reason effectively through complex, open-ended challenges found in frontier physics research? And crucially, what kinds of reasoning tasks do physicists want LLMs to assist with? To address these questions, we present the CritPt (Complex Research using Integrated Thinking - Physics Test, pronounced "critical point"), the first benchmark designed to test LL…

heise | heise Update vom 29. August 2025: Lesetipps fürs Wochenende
Der wöchentliche Newsletter von heise mit Pixel 10 im Test, KI findet Schwachstellen, Quälgeistern im Internet, Antriebswende und mobilen Solarpaneelen.

A Privacy-Preserving Recommender for Filling Web Forms Using a Local Large Language Model
Amirreza Nayyeri, Abbas Rasoolzadegan
https://arxiv.org/abs/2509.01527 https://

A Privacy-Preserving Recommender for Filling Web Forms Using a Local Large Language Model
Web applications are increasingly used in critical domains such as education, finance, and e-commerce. This highlights the need to ensure their failure-free performance. One effective method for evaluating failure-free performance is web form testing, where defining effective test scenarios is key to a complete and accurate evaluation. A core aspect of this process involves filling form fields with suitable values to create effective test cases. However, manually generating these values is time…

Learning to Generate Unit Test via Adversarial Reinforcement Learning
Dongjun Lee, Changho Hwang, Kimin Lee
https://arxiv.org/abs/2508.21107 https://arxiv.…

Learning to Generate Unit Test via Adversarial Reinforcement Learning
Unit testing is a core practice in programming, enabling systematic evaluation of programs produced by human developers or large language models (LLMs). Given the challenges in writing comprehensive unit tests, LLMs have been employed to automate test generation, yet methods for training LLMs to produce high-quality tests remain underexplored. In this work, we propose UTRL, a novel reinforcement learning framework that trains an LLM to generate high-quality unit tests given a programming instru…

Automated Test Oracles for Flaky Cyber-Physical System Simulators: Approach and Evaluation
Baharin A. Jodat, Khouloud Gaaloul, Mehrdad Sabetzadeh, Shiva Nejati
https://arxiv.org/abs/2508.20902

Automated Test Oracles for Flaky Cyber-Physical System Simulators: Approach and Evaluation
Simulation-based testing of cyber-physical systems (CPS) is costly due to the time-consuming execution of CPS simulators. In addition, CPS simulators may be flaky, leading to inconsistent test outcomes and requiring repeated test re-execution for reliable test verdicts. Automated test oracles that do not require system execution are therefore crucial for reducing testing costs. Ideally, such test oracles should be interpretable to facilitate human understanding of test verdicts, and they must b…

Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development
Yuxuan Wan, Tingshuo Liang, Jiakai Xu, Jingyu Xiao, Yintong Huo, Michael R. Lyu
https://arxiv.org/abs/2509.25297

Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development
Developing full-stack web applications is complex and time-intensive, demanding proficiency across diverse technologies and frameworks. Although recent advances in multimodal large language models (MLLMs) enable automated webpage generation from visual inputs, current solutions remain limited to front-end tasks and fail to deliver fully functional applications. In this work, we introduce TDDev, the first test-driven development (TDD)-enabled LLM-agent framework for end-to-end full-stack web app…

DiffTester: Accelerating Unit Test Generation for Diffusion LLMs via Repetitive Pattern
Lekang Yang, Yuetong Liu, Yitong Zhang, Jia Li
https://arxiv.org/abs/2509.24975 https://

DiffTester: Accelerating Unit Test Generation for Diffusion LLMs via Repetitive Pattern
Software development relies heavily on extensive unit testing, which makes the efficiency of automated Unit Test Generation (UTG) particularly important. However, most existing LLMs generate test cases one token at a time in each forward pass, which leads to inefficient UTG. Recently, diffusion LLMs (dLLMs) have emerged, offering promising parallel generation capabilities and showing strong potential for efficient UTG. Despite this advantage, their application to UTG is still constrained by a c…

Unit Test Update through LLM-Driven Context Collection and Error-Type-Aware Refinement
Yuanhe Zhang, Zhiquan Yang, Shengyi Pan, Zhongxin Liu
https://arxiv.org/abs/2509.24419 htt…

Unit Test Update through LLM-Driven Context Collection and Error-Type-Aware Refinement
Unit testing is critical for ensuring software quality and software system stability. The current practice of manually maintaining unit tests suffers from low efficiency and the risk of delayed or overlooked fixes. Therefore, an automated approach is required to instantly update unit tests, with the capability to both repair and enhance unit tests. However, existing automated test maintenance methods primarily focus on repairing broken tests, neglecting the scenario of enhancing existing tests …

Navigating the Labyrinth: Path-Sensitive Unit Test Generation with Large Language Models
Dianshu Liao, Xin Yin, Shidong Pan, Chao Ni, Zhenchang Xing, Xiaoyu Sun
https://arxiv.org/abs/2509.23812

Navigating the Labyrinth: Path-Sensitive Unit Test Generation with Large Language Models
Unit testing is essential for software quality assurance, yet writing and maintaining tests remains time-consuming and error-prone. To address this challenge, researchers have proposed various techniques for automating unit test generation, including traditional heuristic-based methods and more recent approaches that leverage large language models (LLMs). However, these existing approaches are inherently path-insensitive because they rely on fixed heuristics or limited contextual information an…