Tootfinder

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…

Sobre mi anterior Retoot. Os he contado que en el trabajo, por temas del cliente, tuve que pedir que me dieran un ordenador con Windows. Lo primero que hice fue instalar el WSL y aplicaciones comi Emacs, Age... Y usando aplicaciones que son S
Software Libre o casi, como Libreoffice, KeePassXC, Vivaldi...

Folks creating free and open software for the common good: here’s a checklist of everything else you should be doing so corporations can make the best use of your free labour.
I mean, sure, some good security tips here and worth reading anyway but do fuck off with holding free software developers to account for supply chain attacks. It’s your fucking supply chain, not ours, you fucking corporation.

https://libre.fm is freedom-respecting scrobbling software, the open, community-driven alternative to https://last.fm and

Much thanks and heartfelt support to @… for writing up the kind of article that I, too, have been dreading to have to write: that absolutist OSS is bad and we protect the commons with fair licensing, non-commercial and otherwise

Please don't upload my code on GitHub
This is a call to free/libre and open source software developers to not upload the work of others to GitHub.
🚫 #NoGitHub

AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysis
Jiongchi Yu, Weipeng Jiang, Xiaoyu Zhang, Qiang Hu, Xiaofei Xie, Chao Shen
https://arxiv.org/abs/2510.04997

AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysis
Understanding software faults is essential for empirical research in software development and maintenance. However, traditional fault analysis, while valuable, typically involves multiple expert-driven steps such as collecting potential faults, filtering, and manual investigation. These processes are both labor-intensive and time-consuming, creating bottlenecks that hinder large-scale fault studies in complex yet critical software systems and slow the pace of iterative empirical research. In …

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 5. Extensions beyond the standard modelling of theoretical probes and systematic effects
Collaboration, Goh, Nouri-Zonoz, Pamuk, Ballardini, Bose, Ca\~nas-Herrera, Casas, Franco-Abell\'an, Ili\'c, Keil, Kunz, Le Brun, Lepori, Martinelli, Sakr, Sorrenti, Teixeira, Tutusaus, Blot, Bonici, Bonvin, Camera, Cardone, Carrilho, Di Domizio, Durrer, Farrens, Beauchamps, Joudaki, Moretti, Pezzotta, S\'anchez, …

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 5. Extensions beyond the standard modelling of theoretical probes and systematic effects
Euclid is expected to establish new state-of-the-art constraints on extensions beyond the standard LCDM cosmological model by measuring the positions and shapes of billions of galaxies. Specifically, its goal is to shed light on the nature of dark matter and dark energy. Achieving this requires developing and validating advanced statistical tools and theoretical prediction software capable of testing extensions of the LCDM model. In this work, we describe how the Euclid likelihood pipeline, Cos…

BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Zehua Zhang, Ati Priya Bajaj, Divij Handa, Siyu Liu, Arvind S Raj, Hongkai Chen, Hulin Wang, Yibo Liu, Zion Leonahenahe Basque, Souradip Nath, Vishal Juneja, Nikhil Chapre, Yan Shoshitaishvili, Adam Doup\'e, Chitta Baral, Ruoyu Wang
https://arxiv.org/abs/2…

BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for LLM Agents. Existing methods rely on manually curated rules and workflows, which cannot adapt to OSS that requires customized configuration or environment setup. Recent attempts using Large Language Models (LLMs) used selective evaluation on a subset of highly rated OSS, a practice that underestimates the realistic challenges of OSS compilation. In pract…

InsightQL: Advancing Human-Assisted Fuzzing with a Unified Code Database and Parameterized Query Interface
Wentao Gao, Renata Borovica-Gajic, Sang Kil Cha, Tian Qiu, Van-Thuan Pham
https://arxiv.org/abs/2510.04835

InsightQL: Advancing Human-Assisted Fuzzing with a Unified Code Database and Parameterized Query Interface
Fuzzing is a highly effective automated testing method for uncovering software vulnerabilities. Despite advances in fuzzing techniques, such as coverage-guided greybox fuzzing, many fuzzers struggle with coverage plateaus caused by fuzz blockers, limiting their ability to find deeper vulnerabilities. Human expertise can address these challenges, but analyzing fuzzing results to guide this support remains labor-intensive. To tackle this, we introduce InsightQL, the first human-assisting framewor…