Tootfinder

Debug-Logging-Techniken – ein technischer Leitfaden
Eine smarte Debug-Protokollierung unterstützt Entwickler dabei, Probleme schnell zu erkennen und Apps funktionsfähig zu halten. Diese Techniken und Best Practices empfehlen sich.
🧑‍💻 https://www.computerwoche.de/a…

Debug-Logging-Techniken – ein technischer Leitfaden
Eine smarte Debug-Protokollierung unterstützt Entwickler dabei, Probleme schnell zu erkennen und Apps funktionsfähig zu halten. Diese Techniken und Best Practices empfehlen sich.

Container Orchestration Patterns for Optimizing Resource Use
Diogo Maia, Filipe Correia, Andr\'e Restivo, Paulo Queiroz
https://arxiv.org/abs/2510.00197 https://

Container Orchestration Patterns for Optimizing Resource Use
Service-based architectures provide substantial benefits, yet service orchestration remains a challenge, particularly for newcomers. While various resources on orchestration techniques exist, they often lack clarity and standardization, making best practices difficult to implement and limiting their adoption within the software industry. To address this gap, we analyzed existing literature and tools to identify common orchestration practices. Based on our findings, we define three key orchest…

»Crate Layout Best Practices: lib.rs, mod.rs, and src/bin«
Slowly, slowly, I'm learning what Rust uses for what in its coding.
🦀 https://dev.to/sgchris/crate-layout-best-practices-librs-modrs-and-srcbin-4abd

Crate Layout Best Practices: lib.rs, mod.rs, and src/bin
Crate Layout Best Practices: lib.rs, mod.rs, and src/bin Rust has rapidly become one of...

Lol, I think this page is missing a big fucking elephant-in-the-room statement:
"Don't allow AI tools that make shit up and frequently make incorrect assertions run anything on any infrastructure, ever. If fact, just stop reading right now, because this was a stupid idea from the beginning."
https:…

Security Best Practices - Model Context Protocol

GCVE-BCP-04 - Recommendations and Best Practices for ID Allocation version 1.1 published.
BCP Document https://gcve.eu/bcp/gcve-bcp-04/
PDF https://

Recommendations for Best Practices for Data Preservation and Open Science in HEP
Simone Campana (CERN, Switzerland), Irakli Chakaberia (Lawrence Berkeley National Laboratory, USA), Gang Chen (Institute of High Energy Physics, China), Cristinel Diaconu (Centre de Physique des Particules de Marseille CPPM, France, CNRS/IN2P3 and Aix-Marseille Universit\'e, France), Caterina Doglioni (University of Manchester, UK), Dillon S. Fitzgerald (University of Michigan, USA), Vincent Garonne (B…

Recommendations for Best Practices for Data Preservation and Open Science in HEP
These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been done under the umbrella of the Data Lifecycle panel of the International Committee of Future Accelerators (ICFA), drawing on the expertise of a wide range of stakeholders. A key indicator of success in the data preservation efforts is the long-term usability of the data. Experience shows that achieving this requires pr…

My main takeaway from the #jsd2025 was that A.I. is "just another tool". A.I. tools/agents simply amplify your existing workflows. You can't improve a bad process by sprinkling A.I around.
So y'all have to make it work for humans to do good and efficient work at first. All the best practices we know about need to be in place. If you achieved *that* your humans can …

It's time for ✨Decal Patterns✨
Reference from Apache ECharts https://echarts.apache.org/handbook/en/best-practices/aria/#decal-patterns — Github issue here

Gotta love how quickly pull request best practices get abandoned the moment accessibility work is involved.

Virtual Reality User Interface Design: Best Practices and Implementation
Esin Mehmedova, Santiago Berrezueta-Guzman, Stefan Wagner
https://arxiv.org/abs/2508.09358 https://

Virtual Reality User Interface Design: Best Practices and Implementation
Designing effective user interfaces (UIs) for virtual reality (VR) is essential to enhance user immersion, usability, comfort, and accessibility in virtual environments. Despite the growing adoption of VR across domains such as education, healthcare, gaming, and rehabilitation, there is a noticeable lack of unified and comprehensive design guidelines for VR UI design. To address this gap, we conducted a systematic literature review to identify existing best practices and propose complete and un…

Practice Points: Best from Cowboys' final padded practice in Oxnard https://www.dallascowboys.com/news/practice-points-best-from-cowboys-final-padded-practice-in-oxnard

📊 Comprehensive notification analytics with delivery tracking, open rates, click-through analytics, and user engagement metrics for data-driven improvements
🛡️ Security best practices for notification systems including rate limiting, content sanitization, encrypted payloads, and user permission management
🌐 https://

That’s a really hard problem, and not one that will be solved in my ad hoc Saturday posts (or in my replies). I have no answers. I do however have one model to study, which is this org my dad helped found:
https://www.wildernessalliance.org
They help people set up local wilderness stewardship volunteer groups. (There’s a wilderness area near you! You want to help take care of it! How do you do that? What is actually helpful?? What are models and best practices??? Where do you even start????)
8/

Unveiling Chain of Step Reasoning for Vision-Language Models with Fine-grained Rewards
Honghao Chen, Xingzhou Lou, Xiaokun Feng, Kaiqi Huang, Xinlong Wang
https://arxiv.org/abs/2509.19003

Unveiling Chain of Step Reasoning for Vision-Language Models with Fine-grained Rewards
Chain of thought reasoning has demonstrated remarkable success in large language models, yet its adaptation to vision-language reasoning remains an open challenge with unclear best practices. Existing attempts typically employ reasoning chains at a coarse-grained level, which struggles to perform fine-grained structured reasoning and, more importantly, are difficult to evaluate the reward and quality of intermediate reasoning. In this work, we delve into chain of step reasoning for vision-langu…

OpenAI / ChatGPT is shit at UI #accessibility:
• https://html5accessibility.com/stuff/2025/08/15/ai-effluential/
•

🌟 New SIGs Spotlight: SIG-AI 🌟
A new space for collaboration on Artificial Intelligence within the NREN community is here.
SIG-AI brings the Research & Education community together to share expertise, best practices, and explore practical use cases of AI in NREN context—from cybersecurity and High-Performance Computing (HPC) to network automation and next-generation networks.
📖 For more insights, read the full interview with Leonie Schäfer (@…

"DH Spaces: Freie Schaffensräume als multifunktionale Orte an Bibliotheken"
#DigitalHumanities

Current and Future Directions for Responsible Quantum Technologies: A ResQT Community Perspective
Adrian Schmidt, Alexandre Artaud, Arsev Umur Aydinoglu, Astrid B\"otticher, Rodrigo Araiza Bravo, Marilu Chiofalo, Rebecca Coates, Ilke Ercan, Alexei Grinbaum, Emily Haworth, Carolyn Ten Holter, Eline de Jong, Bart Karstens, Matthias C. Kettemann, Anna Kn\"orr, Clarissa Ai Ling Lee, Fabienne Marco, Wenzel Mehnert, Josephine C. Meyer, Shantanu Sharma, Pieter Vermaas, Carrie Weidne…

Current and Future Directions for Responsible Quantum Technologies: A ResQT Community Perspective
Quantum technologies (QT) are advancing rapidly, promising advancements across a wide spectrum of applications but also raising significant ethical, societal, and geopolitical impacts, including dual-use capabilities, varying levels of access, and impending quantum divide(s). To address these, the Responsible Quantum Technologies (ResQT) community was established to share knowledge, perspectives, and best practices across various disciplines. Its mission is to ensure QT developments align with …

Practice Points: Best from Cowboys' final padded practice in Oxnard https://www.dallascowboys.com/news/practice-points-best-from-cowboys-final-padded-practice-in-oxnard

SHERPA: A Model-Driven Framework for Large Language Model Execution
Boqi Chen, Kua Chen, Jos\'e Antonio Hern\'andez L\'opez, Gunter Mussbacher, D\'aniel Varr\'o, Amir Feizpour
https://arxiv.org/abs/2509.00272

SHERPA: A Model-Driven Framework for Large Language Model Execution
Recently, large language models (LLMs) have achieved widespread application across various fields. Despite their impressive capabilities, LLMs suffer from a lack of structured reasoning ability, particularly for complex tasks requiring domain-specific best practices, which are often unavailable in the training data. Although multi-step prompting methods incorporating human best practices, such as chain-of-thought and tree-of-thought, have gained popularity, they lack a general mechanism to cont…

Meta-Metrics and Best Practices for System-Level Inference Performance Benchmarking
Shweta Salaria, Zhuoran Liu, Nelson Mimura Gonzalez
https://arxiv.org/abs/2508.10251 https://…

Meta-Metrics and Best Practices for System-Level Inference Performance Benchmarking
Benchmarking inference performance (speed) of Foundation Models such as Large Language Models (LLM) involves navigating a vast experimental landscape to understand the complex interactions between hardware and software components. However, evaluating every possible test configuration is impractical, unfeasible and unnecessary. To address this challenge, we introduce FMwork, a comprehensive and methodical approach to creating a controlled testing environment that accurately reflects and characte…

Operationalizing AI: Empirical Evidence on MLOps Practices, User Satisfaction, and Organizational Context
Stefan Pasch
https://arxiv.org/abs/2510.09968 https://

Operationalizing AI: Empirical Evidence on MLOps Practices, User Satisfaction, and Organizational Context
Organizational efforts to utilize and operationalize artificial intelligence (AI) are often accompanied by substantial challenges, including scalability, maintenance, and coordination across teams. In response, the concept of Machine Learning Operations (MLOps) has emerged as a set of best practices that integrate software engineering principles with the unique demands of managing the ML lifecycle. Yet, empirical evidence on whether and how these practices support users in developing and operat…

Run-Time Monitoring of ERTMS/ETCS Control Flow by Process Mining
Francesco Vitale, Tommaso Zoppi, Francesco Flammini, Nicola Mazzocca
https://arxiv.org/abs/2509.10419 https://…

Run-Time Monitoring of ERTMS/ETCS Control Flow by Process Mining
Ensuring the resilience of computer-based railways is increasingly crucial to account for uncertainties and changes due to the growing complexity and criticality of those systems. Although their software relies on strict verification and validation processes following well-established best-practices and certification standards, anomalies can still occur at run-time due to residual faults, system and environmental modifications that were unknown at design-time, or other emergent cyber-threat sce…

The Perils of Chart Deception: How Misleading Visualizations Affect Vision-Language Models
Ridwan Mahbub, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, Mizanur Rahman, Mir Tafseer Nayeem, Enamul Hoque
https://arxiv.org/abs/2508.09716

The Perils of Chart Deception: How Misleading Visualizations Affect Vision-Language Models
Information visualizations are powerful tools that help users quickly identify patterns, trends, and outliers, facilitating informed decision-making. However, when visualizations incorporate deceptive design elements-such as truncated or inverted axes, unjustified 3D effects, or violations of best practices-they can mislead viewers and distort understanding, spreading misinformation. While some deceptive tactics are obvious, others subtly manipulate perception while maintaining a facade of legi…

Best practices for nonadiabatic molecular dynamics simulations
Antonio Prlj, Jack T. Taylor, Ji\v{r}\'i Jano\v{s}, Petr Slav\'i\v{c}ek, Federica Agostini, Basile F. E. Curchod
https://arxiv.org/abs/2508.05263

Best practices for nonadiabatic molecular dynamics simulations
Nonadiabatic molecular dynamics simulations aim to describe the coupled electron-nuclear dynamics of molecules in excited electronic states. These simulations have been applied to understand a plethora of photochemical and photophysical processes, and, as a result, the number of nonadiabatic dynamics simulations has been growing significantly over the past decade. Yet, the field remains in its infancy, and a potential user may find it difficult to approach this type of simulation, given their c…

At Berlin Buzzwords 2025, Kevin Liang discussed how Apache Solr/Lucene builds dense vector indexes and talked about how he and his team optimised their dense vector setup, sharing the challenges they faced and the best practices they learned along the way.
Watch the full session: https://youtu.be/cDiCX3mVAlQ?si=YWMkpEVpA-lWrH04
Berlin Buzzwords returns on 7-9 June 2026! Get 36% off with our Trust Us Ticket: https://tickets.plainschwarz.com/bbuzz26/c/8Hvk0ZvJA/

Using LLMs and Essence to Support Software Practice Adoption
Sonia Nicoletti, Paolo Ciancarini
https://arxiv.org/abs/2508.16445 https://arxiv.org/pdf/2508.…

Using LLMs and Essence to Support Software Practice Adoption
Recent advancements in natural language processing (NLP) have enabled the development of automated tools that support various domains, including software engineering. However, while NLP and artificial intelligence (AI) research has extensively focused on tasks such as code generation, less attention has been given to automating support for the adoption of best practices, the evolution of ways of working, and the monitoring of process health. This study addresses this gap by exploring the integr…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/7]:
- Understanding Prompt Management in GitHub Repositories: A Call for Best Practices
Hao Li, Hicham Masri, Filipe R. Cogo, Abdul Ali Bangash, Bram Adams, Ahmed E. Hassan

Generative AI as a Safety Net for Survey Question Refinement
Erica Ann Metheney, Lauren Yehle
https://arxiv.org/abs/2509.08702 https://arxiv.org/pdf/2509.0…

Generative AI as a Safety Net for Survey Question Refinement
Writing survey questions that easily and accurately convey their intent to a variety of respondents is a demanding and high-stakes task. Despite the extensive literature on best practices, the number of considerations to keep in mind is vast and even small errors can render collected data unusable for its intended purpose. The process of drafting initial questions, checking for known sources of error, and developing solutions to those problems requires considerable time, expertise, and financia…

Green Computing: The Ultimate Carbon Destroyer for a Sustainable Future
Sayed Mahbub Hasan Amiri, Prasun Goswami, Md. Mainul Islam, Mohammad Shakhawat Hossen, Marzana Mithila, Naznin Akter
https://arxiv.org/abs/2508.00153

Green Computing: The Ultimate Carbon Destroyer for a Sustainable Future
Green computing represents a critical pathway to decarbonize the digital economy while maintaining technological progress. This article examines how sustainable IT strategies including energy-efficient hardware, AI-optimized data centres, and circular e-waste systems can transform computing into a net carbon sink. Through analysis of industry best practices and emerging technologies like quantum computing and biodegradable electronics, we demonstrate achievable reductions of 40-60% in energy co…

Fraudulent Publishing in the Mathematical Sciences
Ilka Agricola, Lynn Heller, Wil Schilders, Moritz Schubotz, Peter Taylor, Luis Vega
https://arxiv.org/abs/2509.07257 https://

Fraudulent Publishing in the Mathematical Sciences
This report is the first of two publications of a joint Working Group of the International Mathematical Union (IMU) and the International Council of Industrial and Applied Mathematics (ICIAM). In it, we shall analyze the current state of publishing in the mathematical sciences and explain the resulting problems. Our second publication will offer concrete recommendations, guidelines, and best practices for researchers, policymakers, and evaluators of mathematical research. It will explain how to…

SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Xiang Deng, Jeff Da, Edwin Pan, Yannis Yiming He, Charles Ide, Kanak Garg, Niklas Lauffer, Andrew Park, Nitin Pasari, Chetan Rane, Karmini Sampath, Maya Krishnan, Srivatsa Kundurthy, Sean Hendryx, Zifan Wang, Chen Bo Calvin Zhang, Noah Jacobson, Bing Liu, Brad Kenstler
https://

SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
We introduce SWE-Bench Pro, a substantially more challenging benchmark that builds upon the best practices of SWE-BENCH [25], but is explicitly designed to capture realistic, complex, enterprise-level problems beyond the scope of SWE-BENCH. SWE-BENCH PRO contains 1,865 problems sourced from a diverse set of 41 actively maintained repositories spanning business applications, B2B services, and developer tools. The benchmark is partitioned into a public set with open access to problems sourced fro…

MCP2OSC: Parametric Control by Natural Language
Yuan-Yi Fan
https://arxiv.org/abs/2508.10414 https://arxiv.org/pdf/2508.10414

MCP2OSC: Parametric Control by Natural Language
Text prompts enable intuitive content creation but may fall short in achieving high precision for intricate tasks; knob or slider controls offer precise adjustments at the cost of increased complexity. To address the gap between knobs and prompts, a new MCP (Model Context Protocol) server and a unique set of prompt design criteria are presented to enable exploring parametric OSC (OpenSoundControl) control by natural language prompts. Demonstrated by 14 practical QA examples with best practices …

📖 Complete deployment guide for voice AI agents covering setup, configuration and production best practices. 📚 https://docs.livekit.io/agents/start/voice-ai/
📝 Stay updated with latest features and technical insights on the LiveKit blog. 📝

Aligning LLMs for the Classroom with Knowledge-Based Retrieval -- A Comparative RAG Study
Amay Jain, Liu Cui, Si Chen
https://arxiv.org/abs/2509.07846 https://

Aligning LLMs for the Classroom with Knowledge-Based Retrieval -- A Comparative RAG Study
Large language models like ChatGPT are increasingly used in classrooms, but they often provide outdated or fabricated information that can mislead students. Retrieval Augmented Generation (RAG) improves reliability of LLMs by grounding responses in external resources. We investigate two accessible RAG paradigms, vector-based retrieval and graph-based retrieval to identify best practices for classroom question answering (QA). Existing comparative studies fail to account for pedagogical factors s…

📊 Configurable parameters including connection name, retry attempts, and exception handling
🚀 Best practices guide for choosing appropriate transaction method per application layer
https://github.com/mohamadsheam/laravel-auto-transaction

Automated Visualization Makeovers with LLMs
Siddharth Gangwar, David A. Selby, Sebastian J. Vollmer
https://arxiv.org/abs/2508.05637 https://arxiv.org/pdf/…

Automated Visualization Makeovers with LLMs
Making a good graphic that accurately and efficiently conveys the desired message to the audience is both an art and a science, typically not taught in the data science curriculum. Visualisation makeovers are exercises where the community exchange feedback to improve charts and data visualizations. Can multi-modal large language models (LLMs) emulate this task? Given a plot in the form of an image file, or the code used to generate it, an LLM, primed with a list of visualization best practices,…

When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction
Zhenchang Xing, Yang Liu, Zhuo Cheng, Qing Huang, Dehai Zhao, Daniel Sun, Chenhua Liu
https://arxiv.org/abs/2508.06942

When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction
With the growing capabilities of large language models (LLMs), they are increasingly applied in areas like intelligent customer service, code generation, and knowledge management. Natural language (NL) prompts act as the ``APIs'' for human-LLM interaction. To improve prompt quality, best practices for prompt engineering (PE) have been developed, including writing guidelines and templates. Building on this, we propose Controlled NL for Prompt (CNL-P), which not only incorporates PE best practice…

Optimal control driven functional electrical stimulation: A scoping review
Kevin Co, Micka\"el Begon, Fran\c{c}ois Bailly, Florent Moissenet
https://arxiv.org/abs/2508.02899

Optimal control driven functional electrical stimulation: A scoping review
Introduction: Rehabilitation after a neurological impairment can be supported by functional electrical stimulation (FES). However, FES is limited by early muscle fatigue, slowing down the recovery progress. The use of optimal control to reduce overstimulation and improve motion precision is gaining interest. This review aims to map the current literature state meanwhile clarifying the best practices, identifying persistent challenges, and outlining directions for future research. Methods: Follo…

WIP: Leveraging LLMs for Enforcing Design Principles in Student Code: Analysis of Prompting Strategies and RAG
Dhruv Kolhatkar, Soubhagya Akkena, Edward F. Gehringer
https://arxiv.org/abs/2508.11717

WIP: Leveraging LLMs for Enforcing Design Principles in Student Code: Analysis of Prompting Strategies and RAG
This work-in-progress research-to-practice paper explores the integration of Large Language Models (LLMs) into the code-review process for open-source software projects developed in computer science and software engineering courses. The focus is on developing an automated feedback tool that evaluates student code for adherence to key object-oriented design principles, addressing the need for more effective and scalable methods to teach software design best practices. The innovative practice inv…

Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis
Nicole Hoess, Carlos Paradis, Rick Kazman, Wolfgang Mauerer
https://arxiv.org/abs/2510.06844

Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis
Context: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by researchers and practitioners, but their limitations and agreement are often not well understood. Objective: This study investigates some threats to validity in complex tool pipelines for evolutionary software analyses and evaluates the tools' agreement in …

Tool-Assisted Conformance Checking to Reference Process Models
Bernhard Rumpe, Max Stachon, Sebastian St\"uber, Valdes Voufo
https://arxiv.org/abs/2508.00738 https://

Tool-Assisted Conformance Checking to Reference Process Models
Reference models convey best practices and standards. The reference frameworks necessitate conformance checks to ensure adherence to established guidelines and principles, which is crucial for maintaining quality and consistency in various processes. This paper explores automated conformance checks for concrete process models against reference models using causal dependency analysis of tasks and events. Existing notions of conformance checking for process models focus on verifying process execu…