Tootfinder

By engineering yeast to produce six essential sterols found in pollen, researchers provided bees with a nutritionally complete diet that boosted reproduction up to 15-fold.
Unlike commercial substitutes that lack key nutrients, this supplement mimics natural pollen’s sterol profile, giving bees the equivalent of a balanced diet.
…

Scientists found the missing nutrients bees need — Colonies grew 15-fold
Scientists have developed a breakthrough food supplement that could help save honeybees from devastating declines. By engineering yeast to produce six essential sterols found in pollen, researchers provided bees with a nutritionally complete diet that boosted reproduction up to 15-fold. Unlike commercial substitutes that lack key nutrients, this supplement mimics natural pollen’s sterol profile, giving bees the equivalent of a balanced diet.

Quantum Optimal Control with Geodesic Pulse Engineering
Dylan Lewis, Roeland Wiersema, Sougato Bose
https://arxiv.org/abs/2508.16029 https://arxiv.org/pdf/…

Quantum Optimal Control with Geodesic Pulse Engineering
Designing multi-qubit quantum logic gates with experimental constraints is an important problem in quantum computing. Here, we develop a new quantum optimal control algorithm for finding unitary transformations with constraints on the Hamiltonian. The algorithm, geodesic pulse engineering (GEOPE), uses differential programming and geodesics on the Riemannian manifold of $\textrm{SU}(2^n)$ for $n$ qubits. We demonstrate significant improvements over the widely used gradient-based method, GRAPE, …

Knock-Knock: Black-Box, Platform-Agnostic DRAM Address-Mapping Reverse Engineering
Antoine Plin, Lorenzo Casalino, Thomas Rokicki, Ruben Salvador
https://arxiv.org/abs/2509.19568

Knock-Knock: Black-Box, Platform-Agnostic DRAM Address-Mapping Reverse Engineering
Modern Systems-on-Chip (SoCs) employ undocumented linear address-scrambling functions to obfuscate DRAM addressing, which complicates DRAM-aware performance optimizations and hinders proactive security analysis of DRAM-based attacks; most notably, Rowhammer. Although previous work tackled the issue of reversing physical-to-DRAM mapping, existing heuristic-based reverse-engineering approaches are partial, costly, and impractical for comprehensive recovery. This paper establishes a rigorous theor…

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2
Zirui Li, Stephan Husung, Haoze Wang
https://arxiv.org/abs/2508.16181

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2
Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across independently developed system models. SysML v2 introduces enhanced structural modularity and formal semantics, offering a stronger foundation for interoperable modeling. Meanwhile, GPT-based Large Language Models (LLMs) provide new capabilities for assisting model understanding and integration. This paper proposes a structured, prompt-driven approach for LLM…

Bare-Metal RISC-V NVDLA SoC for Efficient Deep Learning Inference
Vineet Kumar (School of Electrical,Electronic Engineering, University College Dublin, Dublin, Ireland, Department of Electronic,Electrical Engineering, Trinity College Dublin, Dublin, Ireland), Ajay Kumar M (School of Electrical,Electronic Engineering, University College Dublin, Dublin, Ireland, Department of Electronic,Electrical Engineering, Trinity College Dublin, Dublin, Ireland), Yike Li (School of Electrical,Elec…

Bare-Metal RISC-V + NVDLA SoC for Efficient Deep Learning Inference
This paper presents a novel System-on-Chip (SoC) architecture for accelerating complex deep learning models for edge computing applications through a combination of hardware and software optimisations. The hardware architecture tightly couples the open-source NVIDIA Deep Learning Accelerator (NVDLA) to a 32-bit, 4-stage pipelined RISC-V core from Codasip called uRISC_V. To offload the model acceleration in software, our toolflow generates bare-metal application code (in assembly), overcoming co…

#Axum Backend Series: Models, Migration, DTOs and Repository Pattern
https://blog.0xshadow.dev/posts/backend-engineering-with-axum/axum-model-setup/

“50 years ago we had solid engineering practice and none of that techbro bullshit!”
50 years ago:

Intelligent Algorithm Selection for Recommender Systems: Meta-Learning via in-depth algorithm feature engineering
Jarne Mathi Decker
https://arxiv.org/abs/2509.20134 https://

Intelligent Algorithm Selection for Recommender Systems: Meta-Learning via in-depth algorithm feature engineering
The "No Free Lunch" theorem dictates that no single recommender algorithm is optimal for all users, creating a significant Algorithm Selection Problem. Standard meta-learning approaches aim to solve this by selecting an algorithm based on user features, but treat the fundamentally diverse algorithms themselves as equivalent, "black-box" choices. This thesis investigates the impact of overcoming this limitation by engineering a comprehensive feature set to explicitly characterize the algorithms …

Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs
Xingang Guo, Yaxin Li, Xiangyi Kong, Yilan Jiang, Xiayu Zhao, Zhihua Gong, Yufan Zhang, Daixuan Li, Tianle Sang, Beixiao Zhu, Gregory Jun, Yingbing Huang, Yiqi Liu, Yuqi Xue, Rahul Dev Kundu, Qi Jian Lim, Yizhou Zhao, Luke Alexander Granger, Mohamed Badr Younis, Darioush Keivan, Nippun Sabharwal, Shreyanka Sinha, Prakhar Agarwal, Kojo Vandyck, Hanlin Mai, Zichen Wang, Aditya Venkatesh, Ayush Barik, Jiankun…

Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs
Today, industry pioneers dream of developing general-purpose AI engineers capable of designing and building humanity's most ambitious projects--from starships that will carry us to distant worlds to Dyson spheres that harness stellar energy. Yet engineering design represents a fundamentally different challenge for large language models (LLMs) compared to traditional textbook-style problem solving or factual question answering. Real-world engineering design demands the synthesis of domain knowle…

EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving
Xiyuan Zhou, Xinlei Wang, Yirui He, Yang Wu, Ruixi Zou, Yuheng Cheng, Yulu Xie, Wenxuan Liu, Huan Zhao, Yan Xu, Jinjin Gu, Junhua Zhao
https://arxiv.org/abs/2509.17677

EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving
Large language models (LLMs) have shown strong performance on mathematical reasoning under well-posed conditions. However, real-world engineering problems require more than mathematical symbolic computation -- they need to deal with uncertainty, context, and open-ended scenarios. Existing benchmarks fail to capture these complexities. We introduce EngiBench, a hierarchical benchmark designed to evaluate LLMs on solving engineering problems. It spans three levels of increasing difficulty (founda…

Sources: GPT-5 shows improved performance in coding, particularly in practical software engineering tasks, outperforming prior OpenAI models and Claude Sonnet 4 (Stephanie Palazzolo/The Information)
https://www.theinformation.com/articles/openais-gpt-5-shines-coding…

OpenAI’s GPT-5 Shines in Coding Tasks
GPT-5 is almost here, and we’re hearing good things. The early reaction from at least one person who’s used the unreleased version was extremely positive.That’s good news for OpenAI. The ChatGPT creator has been under pressure to show major gains from its next big artificial intelligence model ...

Intrinsic Strain-Driven Topological Evolution in SrRuO3 via Flexural Strain Engineering
Liguang Gong, Hongping Jiang, Bin Lao, Xuan Zheng, Xuejiao Chen, Zhicheng Zhong, Yan Sun, Xianfeng Hao, Milan Radovic, Run-Wei Li, Zhiming Wang
https://arxiv.org/abs/2508.16084

Intrinsic Strain-Driven Topological Evolution in SrRuO3 via Flexural Strain Engineering
Strain engineering offers a powerful route to tailor topological electronic structures in correlated oxides, yet conventional epitaxial strain approaches introduce extrinsic factors such as substrate-induced phase transitions and crystalline quality variations, which makes the unambiguous identification of the intrinsic strain effects challenging. Here, we develop a flexural strain platform based on van der Waals epitaxy and flexible micro-fabrication, enabling precise isolation and quantificat…

Advancing Financial Engineering with Foundation Models: Progress, Applications, and Challenges
Liyuan Chen, Shuoling Liu, Jiangpeng Yan, Xiaoyu Wang, Henglin Liu, Chuang Li, Kecheng Jiao, Jixuan Ying, Yang Veronica Liu, Qiang Yang, Xiu Li
https://arxiv.org/abs/2507.18577

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
Arnaud Vadeboncoeur, Gregory Duth\'e, Mark Girolami, Eleni Chatzi
https://arxiv.org/abs/2509.19929

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
Uncertainty Quantification (UQ) is paramount for inference in engineering applications. A common inference task is to recover full-field information of physical systems from a small number of noisy observations, a usually highly ill-posed problem. Critically, engineering systems often have complicated and variable geometries prohibiting the use of standard Bayesian UQ. In this work, we introduce Geometric Autoencoders for Bayesian Inversion (GABI), a framework for learning geometry-aware genera…

I randomly bought this book in a quirky bookshop in Copenhagen for the sole reason that it said all the wrong things right on the cover.
(Sales: the single most important profession. NLP™: not natural language processing but neuro-linguistic programming. Meta: the Meta Model™ and Meta Publications™.)
I just started reading it and boy oh boy, I was not disappointed. It's outrageously hilarious.
"Persuasion engineering".

Persuasion engineering by Richard Bandler | Open Library
Persuasion engineering by Richard Bandler, unknown edition,

Only one more month to QGIS-DE Anwendertreffen (@…)
Freitag, 19. September 2025 — 9:30 bis 17:15 Uhr
FH Aachen
ISCE | Institute of Smart City Engineering
https://www.

High Clockrate Free-space Optical In-Memory Computing
Yuanhao Liang (Department of Electrical Engineering and Computing Sciences, University of California, Berkeley, United States, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, United States), James Wang (Department of Electrical Engineering and Computing Sciences, University of California, Berkeley, United States, Ming Hsieh Department of Electrical and Computer Engineerin…

High Clockrate Free-space Optical In-Memory Computing
The ability to process and act on data in real time is increasingly critical for applications ranging from autonomous vehicles, three-dimensional environmental sensing and remote robotics. However, the deployment of deep neural networks (DNNs) in edge devices is hindered by the lack of energy-efficient scalable computing hardware. Here, we introduce a fanout spatial time-of-flight optical neural network (FAST-ONN) that calculates billions of convolutions per second with ultralow latency and pow…

Jag har märkt att många tror att de får bra svar från olika AI verktyg när de i själva verket bara bekräftar det som användaren vill ha bekräftat.
OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational limits.

OpenAI admits AI hallucinations are mathematically inevitable, not just engineering flaws
In a landmark study, OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational limits.

"The Librarian Skillset and the Needs of Artificial Intelligence"
https://doi.org/10.1080/01639374.2025.2539787
"New roles in AI are emerging throughout Industry, Academia, and Government. From responsible AI management to AI systems engineering, these roles requi…

One concept that I hope most people in science and engineering have internalized is that, for any problem people have studied for decades, there is no simple solution that will comprehensively solve that problem. The problems with simple, comprehensive solutions would've been solved already. What's left are challenging problems where at most, you might chip off a corner of the problem with a simple solution.

Social Engineering & KI: Cyberkriminelle rekrutieren im Darknet
Cyberkriminelle suchen im Darknet verstärkt nach Experten für Social Engineering und KI. Ein Hinweis darauf, auf welche Bedrohungen Firmen achten sollten.

Vamos a utilizar una tecnología que comete errores de forma irreparable por culpa del propio diseño en sí de la tecnología.
Ya me imagino a la gente montando en un avión que puede que llegue al destino o que se precipite contra una montaña, no se sabe. https:/…

Post Hoc Regression Refinement via Pairwise Rankings
Kevin Tirta Wijaya, Michael Sun, Minghao Guo, Hans-Peter Seidel, Wojciech Matusik, Vahid Babaei
https://arxiv.org/abs/2508.16495

Post Hoc Regression Refinement via Pairwise Rankings
Accurate prediction of continuous properties is essential to many scientific and engineering tasks. Although deep-learning regressors excel with abundant labels, their accuracy deteriorates in data-scarce regimes. We introduce RankRefine, a model-agnostic, plug-and-play post hoc method that refines regression with expert knowledge coming from pairwise rankings. Given a query item and a small reference set with known properties, RankRefine combines the base regressor's output with a rank-based e…

AECBench: A Hierarchical Benchmark for Knowledge Evaluation of Large Language Models in the AEC Field
Chen Liang, Zhaoqi Huang, Haofen Wang, Fu Chai, Chunying Yu, Huanhuan Wei, Zhengjie Liu, Yanpeng Li, Hongjun Wang, Ruifeng Luo, Xianzhong Zhao
https://arxiv.org/abs/2509.18776

Reverse Engineering User Stories from Code using Large Language Models
Mohamed Ouf, Haoyu Li, Michael Zhang, Mariam Guizani
https://arxiv.org/abs/2509.19587 https://

Reverse Engineering User Stories from Code using Large Language Models
User stories are essential in agile development, yet often missing or outdated in legacy and poorly documented systems. We investigate whether large language models (LLMs) can automatically recover user stories directly from source code and how prompt design impacts output quality. Using 1,750 annotated C++ snippets of varying complexity, we evaluate five state-of-the-art LLMs across six prompting strategies. Results show that all models achieve, on average, an F1 score of 0.8 for code up to 20…

Most educators have moved from denial about AI to cautious use, but the real cutting-edge is creators misusing it, twisting it, revealing off-label uses and glitches. At least that's what I claim in this U of T podcast https://edtech.engineering.utoronto.ca/made-for-u-o…

Removing Box-Free Watermarks for Image-to-Image Models via Query-Based Reverse Engineering
Haonan An, Guang Hua, Hangcheng Cao, Zhengru Fang, Guowen Xu, Susanto Rahardja, Yuguang Fang
https://arxiv.org/abs/2507.18034

Removing Box-Free Watermarks for Image-to-Image Models via Query-Based Reverse Engineering
The intellectual property of deep generative networks (GNets) can be protected using a cascaded hiding network (HNet) which embeds watermarks (or marks) into GNet outputs, known as box-free watermarking. Although both GNet and HNet are encapsulated in a black box (called operation network, or ONet), with only the generated and marked outputs from HNet being released to end users and deemed secure, in this paper, we reveal an overlooked vulnerability in such systems. Specifically, we show that t…

Crosslisted article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[1/1]:
- Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs
Xingang Guo, et al.

Arms manufacturer Pearson Engineering is chaired by Labour peer Lord Hutton and owned by Israel’s finance ministry, which is run by a far-right politician who is under UK sanctions. Makes sense??
https://www.declassifieduk.org/top-labour-official-…

Top Labour official married to lobbyist for Israeli arms firm
Pearson Engineering is owned by the Israeli government. Now, it has hired a lobbying firm run by the husband of Hollie Ridley, Labour’s general secretary.

Crosslisted article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/2]:
- Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs
Xingang Guo, et al.

Reverse Engineering of Music Mixing Graphs with Differentiable Processors and Iterative Pruning
Sungho Lee, Marco Mart\'inez-Ram\'irez, Wei-Hsiang Liao, Stefan Uhlich, Giorgio Fabbro, Kyogu Lee, Yuki Mitsufuji
https://arxiv.org/abs/2509.15948

Reverse Engineering of Music Mixing Graphs with Differentiable Processors and Iterative Pruning
Reverse engineering of music mixes aims to uncover how dry source signals are processed and combined to produce a final mix. We extend the prior works to reflect the compositional nature of mixing and search for a graph of audio processors. First, we construct a mixing console, applying all available processors to every track and subgroup. With differentiable processor implementations, we optimize their parameters with gradient descent. Then, we repeat the process of removing negligible process…

Discover the innovative engineering behind constructing the UK's tallest wind turbine. #climatechange #climatesolutions #climate

Constrained Higher-Order Binary Optimization for Wireless Communications Systems Using Ising Machines
Gan Zheng, Ioannis Krikidis
https://arxiv.org/abs/2509.20092 https://

Constrained Higher-Order Binary Optimization for Wireless Communications Systems Using Ising Machines
This paper develops an algorithmic solution using Ising machines to solve large-scale higher-order binary optimization (HOBO) problems with inequality constraints for resource optimization in wireless communications systems. Quadratic unconstrained binary optimization (QUBO) aims to solve a special category of these problems widely encountered in engineering and science. To solve QUBO instances, specialized Ising machines have been designed, while sophisticated quantum annealing algorithm and q…

This widely-linked story is, I think, much ado about nothing. Anyone who's seen the inside of an Amazon warehouse immediately thinks “Shouldn’t robots be doing this?” and that includes every Amazon biz and engineering leader, starting like 25 years ago. There is no doubt that the whole warehouse sector would love to replace humans with robots. It’s hard. So what’s new? Is it possible LLM fairy dust will solve the problem? Unconvinced.

Amazon hopes to replace 600,000 US workers with robots, according to leaked documents
Amazon is leaning into automation plans that will enable the company to avoid hiring more than half a million US workers, according to leaked documents.

Happy with the day's work. I should've started this work 1-2 weeks earlier but it seems, tangled in stuff, I'd forgotten the joy in software engineering. But I'm glad to have it back, and, the joy is greater because this work is done as #service. 🙇‍♂️
Tomorrow might feel different but today is a #win. ☺️
#wipWednesday

Parametric design and adaptive sizing of lattice structures for 3d additive manufacturing
Jorge Manuel Mercado-Colmenero, Daniel Diaz - Perete, Miguel Angel Rubio- Paramio, Cristina Martin-Donate
https://arxiv.org/abs/2507.18318

Parametric design and adaptive sizing of lattice structures for 3d additive manufacturing
The present research is developed into the realm of industrial design engineering and additive manufacturing by introducing a parametric design model and adaptive mechanical analysis for a new lattice structure, with a focus on 3D additive manufacturing of complex parts. Focusing on the land-scape of complex parts additive manufacturing, this research proposes geometric parameterization, mechanical adaptive sizing, and numerical validation of a novel lattice structure to optimize the final prin…

Workday hit by social engineering data breach targeting its CRM platform https://therecord.media/workday-social-engineering-data-breach

Ukraine destroys Russian 'terminator on tracks' engineering vehicle in rare strike, military says: https://benborges.xyz/2025/09/21/ukraine-destroys-russian-terminator-on.html

Skills > MCP? I am starting to think so.
MCP is a full-blown protocol.
Skills? *Just* a folder of markdown scripts.
Simple. Shareable. Composable.

https://www.anthropic.com/engineering/equipping-agents-for-the-rea…

OnePiece: Bringing Context Engineering and Reasoning to Industrial Cascade Ranking System
Sunhao Dai, Jiakai Tang, Jiahua Wu, Kun Wang, Yuxuan Zhu, Bingjun Chen, Bangyang Hong, Yu Zhao, Cong Fu, Kangle Wu, Yabo Ni, Anxiang Zeng, Wenjie Wang, Xu Chen, Jun Xu, See-Kiong Ng
https://arxiv.org/abs/2509.18091

OnePiece: Bringing Context Engineering and Reasoning to Industrial Cascade Ranking System
Despite the growing interest in replicating the scaled success of large language models (LLMs) in industrial search and recommender systems, most existing industrial efforts remain limited to transplanting Transformer architectures, which bring only incremental improvements over strong Deep Learning Recommendation Models (DLRMs). From a first principle perspective, the breakthroughs of LLMs stem not only from their architectures but also from two complementary mechanisms: context engineering, w…

Blow-Up Results of Time Fractional Heat Equation With Nonlinear Neumann Boundary Conditions
Hind Ghazi Hameed, Burhan Selcuk, Maan A. Rasheed
https://arxiv.org/abs/2509.18927 ht…

Designing an Interdisciplinary Artificial Intelligence Curriculum for Engineering: Evaluation and Insights from Experts
Johannes Schleiss, Anke Manukjan, Michelle Ines Bieber, Sebastian Lang, Sebastian Stober
https://arxiv.org/abs/2508.14921

Designing an Interdisciplinary Artificial Intelligence Curriculum for Engineering: Evaluation and Insights from Experts
As Artificial Intelligence (AI) increasingly impacts professional practice, there is a growing need to AI-related competencies into higher education curricula. However, research on the implementation of AI education within study programs remains limited and requires new forms of collaboration across disciplines. This study addresses this gap and explores perspectives on interdisciplinary curriculum development through the lens of different stakeholders. In particular, we examine the case of cur…

Starting now: What Autonomous Vehicle Failures Can Tell Us About Engineering Safety-Critical AI, with Prof.dr. (and former jet pilot) Missy Cummings

https://nmclive.tudelft.nl/Mediasite/Channel/seminar-ai-robotics/watch/a525e686be53457e9dad690bfedf51721d?sortBy=most-recent

ELATE: Evolutionary Language model for Automated Time-series Engineering
Andrew Murray, Danial Dervovic, Michael Cashmore
https://arxiv.org/abs/2508.14667 https://

ELATE: Evolutionary Language model for Automated Time-series Engineering
Time-series prediction involves forecasting future values using machine learning models. Feature engineering, whereby existing features are transformed to make new ones, is critical for enhancing model performance, but is often manual and time-intensive. Existing automation attempts rely on exhaustive enumeration, which can be computationally costly and lacks domain-specific insights. We introduce ELATE (Evolutionary Language model for Automated Time-series Engineering), which leverages a langu…

Flow Engineering, which provides a collaborative hardware development platform for companies like Rivian, raised a $23M Series A led by Sequoia (Allie Garfinkle/Fortune)
https://fortune.com/2025/10/14/exclusive-f…

Exclusive: Flow Engineering raises $23 million Series A led by Sequoia to power hardware’s new era
Flow Engineering has raised a $23 million Series A, led by Sequoia and including the Collisons, Fortune has exclusively learned.

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Wenliang Li, Rui Yan, Xu Zhang, Li Chen, Hongji Zhu, Jing Zhao, Junjun Li, Mengru Li, Wei Cao, Zihang Jiang, Wei Wei, Kun Zhang, Shaohua Kevin Zhou
https://arxiv.org/abs/2509.20067

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Large language models (LLMs) have demonstrated notable potential in medical applications, yet they face substantial challenges in handling complex real-world clinical diagnoses using conventional prompting methods. Current prompt engineering and multi-agent approaches typically optimize isolated inferences, neglecting the accumulation of reusable clinical experience. To address this, this study proposes a novel Multi-Agent Clinical Diagnosis (MACD) framework, which allows LLMs to self-learn cli…

Prompts as Software Engineering Artifacts: A Research Agenda and Preliminary Findings
Hugo Villamizar, Jannik Fischbach, Alexander Korn, Andreas Vogelsang, Daniel Mendez
https://arxiv.org/abs/2509.17548

Prompts as Software Engineering Artifacts: A Research Agenda and Preliminary Findings
Developers now routinely interact with large language models (LLMs) to support a range of software engineering (SE) tasks. This prominent role positions prompts as potential SE artifacts that, like other artifacts, may require systematic development, documentation, and maintenance. However, little is known about how prompts are actually used and managed in LLM-integrated workflows, what challenges practitioners face, and whether the benefits of systematic prompt management outweigh the associat…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Select2Drive: Pragmatic Communications for Real-Time Collaborative Autonomous Driving
Jiahao Huang, Jianhang Zhu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

Propagation of intense squeezed vacuum light in non-linear media
J. Rivera-Dean, D. Kanti, P. Stammer, N. Tsatrafyllis, M. Lewenstein, P. Tzallas
https://arxiv.org/abs/2509.19608

Propagation of intense squeezed vacuum light in non-linear media
Recent developments in quantum light engineering have enabled the use of infrared bright squeezed vacuum (BSV) femtosecond pulses in highly nonlinear optics, particularly strong-field physics and high-harmonic generation. However, theoretical studies were focused on interactions with single-atoms only, neglecting that under realistic conditions light propagates through the media. This raises two key questions: How does BSV propagates in strongly light-driven nonlinear media, and under what cond…

HAMSA: Hijacking Aligned Compact Models via Stealthy Automation
Alexey Krylov, Iskander Vagizov, Dmitrii Korzh, Maryam Douiba, Azidine Guezzaz, Vladimir Kokh, Sergey D. Erokhin, Elena V. Tutubalina, Oleg Y. Rogov
https://arxiv.org/abs/2508.16484

HAMSA: Hijacking Aligned Compact Models via Stealthy Automation
Large Language Models (LLMs), especially their compact efficiency-oriented variants, remain susceptible to jailbreak attacks that can elicit harmful outputs despite extensive alignment efforts. Existing adversarial prompt generation techniques often rely on manual engineering or rudimentary obfuscation, producing low-quality or incoherent text that is easily flagged by perplexity-based filters. We present an automated red-teaming framework that evolves semantically meaningful and stealthy jailb…

How Usable is Automated Feature Engineering for Tabular Data?
Bastian Sch\"afer, Lennart Purucker, Maciej Janowski, Frank Hutter
https://arxiv.org/abs/2508.13932 https://…

How Usable is Automated Feature Engineering for Tabular Data?
Tabular data, consisting of rows and columns, is omnipresent across various machine learning applications. Each column represents a feature, and features can be combined or transformed to create new, more informative features. Such feature engineering is essential to achieve peak performance in machine learning. Since manual feature engineering is expensive and time-consuming, a substantial effort has been put into automating it. Yet, existing automated feature engineering (AutoFE) methods have…

Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering
Ziyou Li, Agnia Sergeyuk, Maliheh Izadi
https://arxiv.org/abs/2509.17096 https://

Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering
Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflows. We present Prompt-with-Me, a practical solution for structured prompt management embedded directly in the development environment. The system automatically classifies prompts using a four-dimensional taxonomy encompassing intent, author role, software development lifecycle stage, and prompt type. To enhance prompt…

Large Language Models as Visualization Agents for Immersive Binary Reverse Engineering
Dennis Brown, Samuel Mulder
https://arxiv.org/abs/2508.13413 https://

Large Language Models as Visualization Agents for Immersive Binary Reverse Engineering
Immersive virtual reality (VR) offers affordances that may reduce cognitive complexity in binary reverse engineering (RE), enabling embodied and external cognition to augment the RE process through enhancing memory, hypothesis testing, and visual organization. In prior work, we applied a cognitive systems engineering approach to identify an initial set of affordances and implemented a VR environment to support RE through spatial persistence and interactivity. In this work, we extend that platfo…

Exploration of Evolving Quantum Key Distribution Network Architecture Using Model-Based Systems Engineering
Hayato Ishida, Amal Elsokary, Maria Aslam, Catherine White, Michael J. de C. Henshaw, Siyuan Ji
https://arxiv.org/abs/2508.15733

Exploration of Evolving Quantum Key Distribution Network Architecture Using Model-Based Systems Engineering
Realisation of significant advances in capabilities of sensors, computing, timing, and communication enabled by quantum technologies is dependent on engineering highly complex systems that integrate quantum devices into existing classical infrastructure. A systems engineering approach is considered to address the growing need for quantum-secure telecommunications that overcome the threat to encryption caused by maturing quantum computation. This work explores a range of existing and future quan…

MIM-Diode-Like Rectification in Lateral 1T/1H/1T-MoS$_2$ Homojunctions via Interfacial Dipole Engineering
Elias Eckmann, Ersoy \c{S}a\c{s}{\i}o\u{g}lu, Nicki F. Hinsche, Ingrid Mertig
https://arxiv.org/abs/2509.17947

MIM-Diode-Like Rectification in Lateral 1T/1H/1T-MoS$_2$ Homojunctions via Interfacial Dipole Engineering
Lateral two-dimensional (2D) tunnel diodes that reproduce metal-insulator-metal (MIM)-diode-like rectification without using dissimilar contacts are attractive for scalable nanoelectronics. MoS$_2$ can exist in both the semiconducting 1H phase and the metallic 1T phase, enabling phase-engineered homojunctions within a single material. First-principles electronic structure and quantum transport calculations show that phase-engineered 1T/1H/1T--MoS$_2$ homojunctions exhibit pronounced MIM-diode-l…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Generalized Scattering Matrix Synthesis: Independent Region Decomposition for Hybrid Antenna--Sca...
Chenbo Shi, Shichen Liang, Jin Pan, Xin Gu, Le Zuo

A Nodal Discontinuous Galerkin Method with Low-Rank Velocity Space Representation for the Multi-Scale BGK Model
Andres Galindo-Olarte, Joseph Nakao, Mirjeta Pasha, Jing-Mei Qiu, William Taitano
https://arxiv.org/abs/2508.16564

A Nodal Discontinuous Galerkin Method with Low-Rank Velocity Space Representation for the Multi-Scale BGK Model
A novel hybrid algorithm is presented for the Boltzmann-BGK equation, in which a low-rank decomposition is applied solely in the velocity subspace, while a full-rank representation is maintained in the physical (position) space. This approach establishes a foundation for extending modern low-rank techniques to solve the Boltzmann equation in realistic settings, particularly where structured representations -- such as conformal geometries -- may not be feasible in practical engineering applicati…

Nonlocal Electrostatics and Boundary Charges in Continuum Limits of Two-Dimensional Materials
Shoham Sen, Yang Wang, Timothy Breitzman, Kaushik Dayal
https://arxiv.org/abs/2509.17744

Nonlocal Electrostatics and Boundary Charges in Continuum Limits of Two-Dimensional Materials
Two-dimensional (2D) electronic materials are of significant technological interest due to their exceptional properties and broad applicability in engineering. The transition from nanoscale physics, that dictates their stable configurations, to macroscopic engineering applications requires the use of multiscale methods to systematically capture their electronic properties at larger scales. A key challenge in coarse-graining is the rapid and near-periodic variation of the charge density, which e…

Anthropic details three infrastructure bugs that intermittently degraded Claude's responses between August and early September, and explains how they were fixed (Anthropic)
https://www.anthropic.com/engineering/a-postmortem-of-three-recent-issues

A postmortem of three recent issues
This is a technical report on three bugs that intermittently degraded responses from Claude. Below we explain what happened, why it took time to fix, and what we're changing.

One Filters All: A Generalist Filter for State Estimation
Shiqi Liu, Wenhan Cao, Chang Liu, Zeyu He, Tianyi Zhang, Shengbo Eben Li
https://arxiv.org/abs/2509.20051 https://

One Filters All: A Generalist Filter for State Estimation
Estimating hidden states in dynamical systems, also known as optimal filtering, is a long-standing problem in various fields of science and engineering. In this paper, we introduce a general filtering framework, \textbf{LLM-Filter}, which leverages large language models (LLMs) for state estimation by embedding noisy observations with text prototypes. In various experiments for classical dynamical systems, we find that first, state estimation can significantly benefit from the reasoning knowledg…

Improving the efficiency of quantum engineering of SCSs by adding two demultiplexed input photons
Mikhail S. Podoshvedov, Sergey A. Podoshvedov
https://arxiv.org/abs/2509.14625 …

Improving the efficiency of quantum engineering of SCSs by adding two demultiplexed input photons
Conditional addition and subtraction of photons is a powerful tool for quantum engineering of continuous variable (CV) states that forms the fundamental building blocks of advanced photonic technologies. For high fidelity information processing, precise control of quantum engineering of CV states is highly demanded. We propose a scheme for measurement induced quantum engineering of even/odd superposition of coherent states (SCSs) of amplitude>2.5 and with fidelity exceeding>0.99. It includes si…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- System for systematic literature review using multiple AI agents: Concept and an empirical evalua...
Sami, Rasheed, Kemell, Waseem, Kilamo, Saari, Duc, Syst\"a, Abrahamsson

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Sup...
Ghasemshirazi, Shirvani, Tavakoli, Ghaedi, Langarizadeh

Giant optical anisotropy in CrSBr from giant exciton oscillator strength
Georgy Ermolaev, Tagir Mazitov, Arslan Mazitov, Adilet Toksumakov, Dmitriy Grudinin, Anton Minnekhanov, Gleb Tselikov, Dmitry Yakubovsky, Gleb Tikhonowski, Nikolay Pak, Umer Ahsan, Aleksandr Slavich, Mikhail Mironov, Alexey Tsapenko, Andrey Vyshnevyy, Ivan Kruglov, Zdenek Sofer, Aleksey Arsenin, Kostya Novoselov, Andrey Katanin, Valentyn Volkov

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- A Preliminary Study on the Robustness of Code Generation by Large Language Models
Zike Li, Mingwei Liu, Anji Li, Kaifeng He, Yanlin Wang, Xin Peng, Zibin Zheng

Hijacking Living Cells with Surface Engineering for the Internet of Bio-Nano Things
Ekin Ince, Murat Kuscu
https://arxiv.org/abs/2509.17227 https://arxiv.o…

Hijacking Living Cells with Surface Engineering for the Internet of Bio-Nano Things
The Internet of Bio-Nano Things (IoBNT) promises to revolutionize healthcare by interfacing the cyber domain with the living systems at unprecedented resolution. Realizing this vision hinges on the development of Bio-Nano Things (BNTs), i.e., functional nodes capable of sensing, actuation, and communications within biological environments. Existing BNT architectures, e.g., nanomaterial-based, biosynthetic, and passive molecular agents, face significant limitations, including toxicity, lack of a…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer
Wenyan Xu, Rundong Wang, Chen Li, Yonghong Hu, Zhonghua Lu

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Security smells in infrastructure as code: a taxonomy update beyond the seven sins
Aicha War, Serge L. B. Nikiema, Jordan Samhi, Jacques Klein, Tegawende F. Bissyande

Sources: Apple's foldable iPad with an 18" screen faces engineering challenges tied to weight, features, and display tech, pushing its debut to 2029 or later (Mark Gurman/Bloomberg)
https://www.bloomberg.com/news/articles/20

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- A Spline-Based Stress Function Approach for the Principle of Minimum Complementary Energy
Fabian Key, Lukas Freinberger

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Is Reuse All You Need? A Systematic Comparison of Regular Expression Composition Strategies
Berk \c{C}akar, Charles M. Sale, Sophie Chen, Dongyoon Lee, James C. Davis

Computation and Sensitivity Analysis of the Deformation-Gradient Tensor Reconstruction in Dark-Field X-ray Microscopy
Brinthan Kanesalingam, Darshan Chalise, Carsten Detlefs, Leora Dresselhaus-Marais
https://arxiv.org/abs/2507.17929

Computation and Sensitivity Analysis of the Deformation-Gradient Tensor Reconstruction in Dark-Field X-ray Microscopy
Spatially resolved strain measurements are crucial to understanding the properties of engineering materials. Although strain measurements utilizing techniques such as transmission electron microscopy and electron backscatter diffraction offer high spatial resolution, they are limited to surface or thin samples. X-ray diffraction methods, including Bragg Coherent Diffraction Imaging and X-ray topography, enable strain measurements deep inside bulk materials but face challenges in simultaneously …

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Agentic Metacognition: Designing a "Self-Aware" Low-Code Agent for Failure Prediction and Human H...
Jiexi Xu

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- A Coopetitive-Compatible Data Generation Framework for Cross-silo Federated Learning
Thanh Linh Nguyen, Quoc-Viet Pham

Some developers say GPT-5 excels at technical reasoning and planning coding tasks and is cost-effective, but Claude Opus and Sonnet still produce better code (Lauren Goode/Wired)
https://www.wired.com/story/gpt-5-coding-review-software-engineering/

Developers Say GPT-5 Is a Mixed Bag
Software engineers are finding that OpenAI’s new GPT-5 model is helping them think through coding problems—but isn’t much better at actual coding.

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study
Waseem, Liang, Ahmad, Khan, Shahin, Abrahamsson, Nasab, Mikkonen

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Data Fusion for Full-Range Response Reconstruction via Diffusion Models
Wingho Feng, Quanwang Li, Chen Wang, Jian-sheng Fan

ParaAegis: Parallel Protection for Flexible Privacy-preserved Federated Learning
Zihou Wu (School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China), Yuecheng Li (School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China), Tianchi Liao (School of Software Engineering, Sun Yat-sen University, Zhuhai, China), Jian Lou (School of Software Engineering, Sun Yat-sen University, Zhuhai, China), Chuan Chen (School of Computer Science and E…

ParaAegis: Parallel Protection for Flexible Privacy-preserved Federated Learning
Federated learning (FL) faces a critical dilemma: existing protection mechanisms like differential privacy (DP) and homomorphic encryption (HE) enforce a rigid trade-off, forcing a choice between model utility and computational efficiency. This lack of flexibility hinders the practical implementation. To address this, we introduce ParaAegis, a parallel protection framework designed to give practitioners flexible control over the privacy-utility-efficiency balance. Our core innovation is a strat…

Sb2S3 and GaAs Absorber Layer-based Quantum Dot Solar Cells with Cadmium Telluride-based HTL: A Comparative Study
Sayak Banerjee (Department of Physics, Indian Institute of Technology, Jodhpur, Rajasthan, India-342037, Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Jodhpur, Rajasthan, India), Anupam Chetia (Department of Physics, Indian Institute of Technology, Jodhpur, Rajasthan, India-342037), Satyajit Sahu (Department of Physics, Indian Instit…

Sb2S3 and GaAs Absorber Layer-based Quantum Dot Solar Cells with Cadmium Telluride-based HTL: A Comparative Study
Quantum dot solar cells (QDSC) are widely acknowledged to be one of the best solar energy harvesting devices in the present world. Absorber layer is a core component of a QDSC with a strong influence on its operational efficiency. Hence, we choose to undertake a comparative study of two QDSC having different QD absorber layers: Sb2S3 and GaAs with the motive to identify the better absorber layer material. The numerical analysis has been carried out using SCAPS-1D (Solar Cell Capacitance Simulat…

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Leveraging Large Language Models to Detect Missed Peephole Optimizations
Zhenyang Xu, Hongxu Xu, Yongqiang Tian, Xintong Zhou, Chengnian Sun

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- An Overview of Meshfree Collocation Methods
Tomas Halada, Serhii Yaskovets, Abhinav Singh, Ludek Benes, Pratik Suchde, Ivo F. Sbalzarini

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- It is Giving Major Satisfaction: Why Fairness Matters for Software Practitioners
Emeralda Sesari, Federica Sarro, Ayushi Rastogi

[2025-07-25 Fri (UTC), 1 new article found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

[2025-09-24 Wed (UTC), 7 new articles found for cs.SE Software Engineering]
toXiv_bot_toot

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…

[2025-09-24 Wed (UTC), 2 new articles found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

[2025-09-25 Thu (UTC), 14 new articles found for cs.SE Software Engineering]
toXiv_bot_toot

[2025-09-25 Thu (UTC), 4 new articles found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

[2025-08-25 Mon (UTC), 17 new articles found for cs.SE Software Engineering]
toXiv_bot_toot

[2025-07-25 Fri (UTC), 18 new articles found for cs.SE Software Engineering]
toXiv_bot_toot

Evaluation Guidelines for Empirical Studies in Software Engineering involving LLMs
Sebastian Baltes, Florian Angermeir, Chetan Arora, Marvin Mu\~noz Bar\'on, Chunyang Chen, Lukas B\"ohme, Fabio Calefato, Neil Ernst, Davide Falessi, Brian Fitzgerald, Davide Fucci, Marcos Kalinowski, Stefano Lambiase, Daniel Russo, Mircea Lungu, Lutz Prechelt, Paul Ralph, Christoph Treude, Stefan Wagner

Evaluation Guidelines for Empirical Studies in Software Engineering involving LLMs
Large language models (LLMs) are increasingly being integrated into software engineering (SE) research and practice, yet their non-determinism, opaque training data, and evolving architectures complicate the reproduction and replication of empirical studies. We present a community effort to scope this space, introducing a taxonomy of LLM-based study types together with eight guidelines for designing and reporting empirical studies involving LLMs. The guidelines present essential (must) criteria…

Enhancing Requirement Traceability through Data Augmentation Using Large Language Models
Jianzhang Zhang, Jialong Zhou, Nan Niu, Chuang Liu
https://arxiv.org/abs/2509.20149 http…

Enhancing Requirement Traceability through Data Augmentation Using Large Language Models
Requirements traceability is crucial in software engineering to ensure consistency between requirements and code. However, existing automated traceability methods are constrained by the scarcity of training data and challenges in bridging the semantic gap between artifacts. This study aims to address the data scarcity problem in requirements traceability by employing large language models (LLMs) for data augmentation. We propose a novel approach that utilizes prompt-based techniques with LLMs t…

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat
Zezhou Yang, Ting Peng, Cuiyun Gao, Chaozheng Wang, Hailiang Huang, Yuetang Deng
https://arxiv.org/abs/2507.18515

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat
Code completion, a crucial task in software engineering that enhances developer productivity, has seen substantial improvements with the rapid advancement of large language models (LLMs). In recent years, retrieval-augmented generation (RAG) has emerged as a promising method to enhance the code completion capabilities of LLMs, which leverages relevant context from codebases without requiring model retraining. While existing studies have demonstrated the effectiveness of RAG on public repositori…

How Software Engineers Engage with AI: A Pragmatic Process Model and Decision Framework Grounded in Industry Observations
Vahid Garousi, Zafar Jafarov
https://arxiv.org/abs/2507.17930

How Software Engineers Engage with AI: A Pragmatic Process Model and Decision Framework Grounded in Industry Observations
Artificial Intelligence (AI) has the potential to transform Software Engineering (SE) by enhancing productivity, efficiency, and decision support. Tools like GitHub Copilot and ChatGPT have given rise to "vibe coding"-an exploratory, prompt-driven development style. Yet, how software engineers engage with these tools in daily tasks, especially in deciding whether to trust, refine, or reject AI-generated outputs, remains underexplored. This paper presents two complementary contributions. First, …

An Empirical Study of Complexity, Heterogeneity, and Compliance of GitHub Actions Workflows
Edward Abrokwah, Taher A. Ghaleb
https://arxiv.org/abs/2507.18062 https://

An Empirical Study of Complexity, Heterogeneity, and Compliance of GitHub Actions Workflows
Continuous Integration (CI) has evolved from a tooling strategy to a fundamental mindset in modern CI engineering. It enables teams to develop, test, and deliver software rapidly and collaboratively. Among CI services, GitHub Actions (GHA) has emerged as a dominant service due to its deep integration with GitHub and a vast ecosystem of reusable workflow actions. Although GHA provides official documentation and community-supported best practices, there appears to be limited empirical understandi…

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…

Factors Impacting Faculty Adoption of Project-Based Learning in Computing Education: a Survey
Ahmad D. Suleiman, Yiming Tang, Daqing Hou
https://arxiv.org/abs/2507.18039 https:/…

Factors Impacting Faculty Adoption of Project-Based Learning in Computing Education: a Survey
This research full paper investigates the factors influencing computing educators' adoption of project-based learning (PjBL) in software engineering and computing curricula. Recognized as a student-centered pedagogical approach, PjBL has the potential to enhance student motivation, engagement, critical thinking, collaboration, and problem-solving skills. Despite these benefits, faculty adoption remains inconsistent due to challenges such as insufficient institutional support, time constraints, …

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Discovering Software Parallelization Points Using Deep Neural Networks
Izavan dos S. Correia, Henrique C. T. Santos, Tiago A. E. Ferreira

A Comparative Study of Delta Parquet, Iceberg, and Hudi for Automotive Data Engineering Use Cases
Dinesh Eswararaj, Ajay Babu Nellipudi, Vandana Kollati
https://arxiv.org/abs/2508.13396

A Comparative Study of Delta Parquet, Iceberg, and Hudi for Automotive Data Engineering Use Cases
The automotive industry generates vast amounts of data from sensors, telemetry, diagnostics, and real-time operations. Efficient data engineering is critical to handle challenges of latency, scalability, and consistency. Modern data lakehouse formats Delta Parquet, Apache Iceberg, and Apache Hudi offer features such as ACID transactions, schema enforcement, and real-time ingestion, combining the strengths of data lakes and warehouses to support complex use cases. This study presents a comparati…

QUPER-MAn: Benchmark-Guided Target Setting for Maintainability Requirements
Markus Borg, Martin Larsson, Philip Breid, Nadim Hagatulah
https://arxiv.org/abs/2508.15512 https://

QUPER-MAn: Benchmark-Guided Target Setting for Maintainability Requirements
Maintainable source code is essential for sustainable development in any software organization. Unfortunately, many studies show that maintainability often receives less attention than its importance warrants. We argue that requirements engineering can address this gap the problem by fostering discussions and setting appropriate targets in a responsible manner. In this preliminary work, we conducted an exploratory study of industry practices related to requirements engineering for maintainabili…