Tootfinder

Relaying for a friend and colleague
Sr. Network Engineer (Akamai) - US based Remote person. The role is on the the Akamai backbone network engineering team. If you have experience with large scale MPLS and Traffic Engineering and would like to works on some large scale networking problems... https://jobs.akamai.com/en/sit…

Best Practices for Machine Learning-Assisted Protein Engineering
Fabio Herrera-Rocha, David Medina-Ortiz, Fabian Mauz, Juergen Pleiss, Mehdi D. Davari
https://arxiv.org/abs/2507.07547

Best Practices for Machine Learning-Assisted Protein Engineering
Data-driven modeling based on Machine Learning (ML) is becoming a central component of protein engineering workflows. This perspective presents the elements necessary to develop effective, reliable, and reproducible ML models, and a set of guidelines for ML developments for protein engineering. This includes a critical discussion of software engineering good practices for development and evaluation of ML-based protein engineering projects, emphasizing supervised learning. These guidelines cover…

State of the software engineering #jobsmarket, 2025: what hiring managers see
https://newsletter.pragmaticengineer.com/p/state-of-the-tech-market-in-2…

An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis
Mingda Zhang, Na Zhao, Jianglong Qing, Qing xu, Kaiwen Pan, Ting luo
https://arxiv.org/abs/2507.07893

An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis
The rapid development of artificial intelligence has positioned large language models as fundamental components of intelligent legal systems. However, these models face significant limitations in legal dispute analysis, including insufficient legal knowledge representation, limited concept understanding, and reasoning deficiencies. This research proposes an enhanced framework integrating prompt engineering with multidimensional knowledge graphs. The framework introduces a three-stage hierarchic…

Agentic Software Engineering: Foundational Pillars and a Research Roadmap
Ahmed E. Hassan, Hao Li, Dayi Lin, Bram Adams, Tse-Hsun Chen, Yutaro Kashiwa, Dong Qiu
https://arxiv.org/abs/2509.06216

Agentic Software Engineering: Foundational Pillars and a Research Roadmap
Agentic Software Engineering (SE 3.0) represents a new era where intelligent agents are tasked not with simple code generation, but with achieving complex, goal-oriented SE objectives. To harness these new capabilities while ensuring trustworthiness, we must recognize a fundamental duality within the SE field in the Agentic SE era, comprising two symbiotic modalities: SE for Humans and SE for Agents. This duality demands a radical reimagining of the foundational pillars of SE (actors, processes…

Eco Puzzlers For Masters of Engineering - For those on their way to mastering engineering... A set of thought experiments to help fix the real world. #ecoEngineering - https://www.earth.org.uk/MEng-Eco-Puzzlers

Eco Puzzlers For Masters of Engineering
For those on their way to mastering engineering... A set of thought experiments to help fix the real world. #ecoEngineering

The Linux Foundation will launch the React Foundation, a new home for Meta's React and React Native; founding members include Amazon, Meta, Microsoft, others (Engineering at Meta)
https://engineering.fb.com/2025/10/07/

Introducing the React Foundation: The New Home for React & React Native
Meta open-sourced React over a decade ago to help developers build better user experiences. Since then, React has grown into one of the world’s most popular open source projects, powering over 50 m…

The impact of gamification on learning outcomes: experiences from a Biomedical Engineering course
Gonzalo R. R\'ios-Mu\~noz, Caterina Fuster-Barcelo, Arrate Mu\~noz-Barrutia
https://arxiv.org/abs/2509.06126

The impact of gamification on learning outcomes: experiences from a Biomedical Engineering course
This study examines the integration of digital tools in project-based learning within a Biomedical Engineering course to enhance collaboration, transparency, and assessment fairness. Building on prior pilot experiences, we implemented a structured learning environment that combined experiment tracking, real-time collaboration, and peer-assessment practices. The intervention was deployed across two consecutive academic years, involving master's-level students in Biomedical Image Processing. Data…

Snowpark: Performant, Secure, User-Friendly Data Engineering and AI/ML Next To Your Data
Brandon Baker, Elliott Brossard, Chenwei Xie, Zihao Ye, Deen Liu, Yijun Xie, Arthur Zwiegincew, Nitya Kumar Sharma, Gaurav Jain, Eugene Retunsky, Mike Halcrow, Derek Denny-Brown, Istvan Cseri, Tyler Akidau, Yuxiong He
https://arxiv.org/abs/2508.05904…

Snowpark: Performant, Secure, User-Friendly Data Engineering and AI/ML Next To Your Data
Snowflake revolutionized data analytics with an elastic architecture that decouples compute and storage, enabling scalable solutions supporting data architectures like data lake, data warehouse, data lakehouse, and data mesh. Building on this foundation, Snowflake has advanced its AI Data Cloud vision by introducing Snowpark, a managed turnkey solution that supports data engineering and AI and ML workloads using Python and other programming languages. This paper outlines Snowpark's design obj…

https://engineering.fb.com/2025/10/07/open-source/introducing-the-react-foundation-the-new-home-for-react-react-native/ 🧐

Introducing the React Foundation: The New Home for React & React Native
Meta open-sourced React over a decade ago to help developers build better user experiences. Since then, React has grown into one of the world’s most popular open source projects, powering over 50 m…

Degradation-Aware Model Predictive Control for Battery Swapping Stations under Energy Arbitrage
Ruochen Li (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Zhichao Chen (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Zhaoting Zhang (Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong, China), Renjie Guo (Department of Decision Analytics and Operations, City Univers…

Degradation-Aware Model Predictive Control for Battery Swapping Stations under Energy Arbitrage
Battery swapping stations (BSS) offer a fast and scalable alternative to conventional electric vehicle (EV) charging, gaining growing policy support worldwide. However, existing BSS control strategies typically rely on heuristics or low-fidelity degradation models, limiting profitability and service level. This paper proposes BSS-MPC: a real-time, degradation-aware Model Predictive Control (MPC) framework for BSS operations to trade off economic incentives from energy market arbitrage and long-…

A large language model system for the field of chemical engineering technology
Heng Zhang, Jibin Zhou, Feiyang Xu, Jian Cui, Yi Li, Fan Yang, Hao Wang, Xin Li, Mao Ye
https://arxiv.org/abs/2509.07034

A large language model system for the field of chemical engineering technology
The development of chemical engineering technology is a multi-stage process that encompasses laboratory research, scaling up, and industrial deployment. This process demands interdisciplinary col laboration and typically incurs significant time and economic costs. To tackle these challenges, we have developed a system based on ChemELLM in this work. This system enables users to interact freely with the chem ical engineering model, establishing a new paradigm for AI-driven in novation an…

Collective dissipation engineering of interacting Rydberg atoms
Tao Chen, Chenxi Huang, Jacob P. Covey, Bryce Gadway
https://arxiv.org/abs/2509.06373 https://

Collective dissipation engineering of interacting Rydberg atoms
Engineered dissipation is emerging as an alternative tool for quantum state control, enabling high-fidelity preparation, transfer and stabilization, and access to novel phase transitions. We realize a tunable, state-resolved laser-induced loss channel for individual Rydberg atoms, in both non-interacting and strongly correlated settings. This capability allows us to reveal interaction-driven shifts of the exceptional point separating quantum Zeno and anti-Zeno regimes, and to demonstrate intera…

Reversible local strain engineering of $\mathrm{WS}_2$ using a micro-mechanical spring
Eric Herrmann, Zhixiang Huang, Sai Rahul Sitaram, Ke Ma, S M Jahadun Nobi, Xi Wang
https://arxiv.org/abs/2507.07784

Reversible local strain engineering of $\mathrm{WS}_2$ using a micro-mechanical spring
Local strain engineering is a promising technique to tune the properties of two-dimensional materials at the nanoscale. However, many existing methods are static and limit the systematic exploration of strain-dependent material behavior. Here, we demonstrate dynamic and reversible control of local strain distributions in suspended trilayer tungsten disulfide ($\mathrm{WS}_2$) via nanoindentation using a micro-mechanical spring patterned with nanoscale probes. Micro-photoluminescence measurement…

Enhancing Plasmonic Superconductivity in Layered Materials via Dynamical Coulomb Engineering
Yann in 't Veld, Mikhail I. Katsnelson, Andrew J. Millis, Malte R\"osner
https://arxiv.org/abs/2508.06195

Enhancing Plasmonic Superconductivity in Layered Materials via Dynamical Coulomb Engineering
Conventional Coulomb engineering, through controlled manipulation of the environment, offers an effective route to tune the correlation properties of atomically thin van der Waals materials via static screening. Here we present tunable dynamical screening as a method for precisely tailoring bosonic modes to optimize many-body properties. We show that ``bosonic engineering'' of plasmon modes can be used to enhance plasmon-induced superconducting critical temperatures of layered superconductors i…

If you get an invite to this generative art software engineering call, note that if you submit something and it gets accepted, as far as I can tell it would cost you $3000 in open access fees... unless you want it to languish behind a paywall (you'd then only be allowed to share an unedited draft, and even then would have to advertise the paywall on it). They don't seem to want to make this clear in their call.

Among college graduates ages 22-27, computer science and computer engineering majors face unemployment rates of 6.1% and 7.5%, respectively, over double the unemployment rate among recent biology and art history graduates, which is just 3%.
Goodbye, $165,000 Tech Jobs. Student Coders Seek Work at Chipotle
https://www.…

Computer Science Grads Struggle to Find Jobs in the A.I. Age
As companies like Amazon and Microsoft lay off workers and embrace A.I. coding tools, computer science graduates say they’re struggling to land tech jobs.

Reliability of Single-Level Equality-Constrained Inverse Optimal Control
Filip Be\v{c}anovi\'c (University of Belgrade - School of Electrical Engineering), Kosta Jovanovi\'c (University of Belgrade - School of Electrical Engineering), Vincent Bonnet (LAAS-CNRS)
https://arxiv.org/abs/2510.08406

Reliability of Single-Level Equality-Constrained Inverse Optimal Control
Inverse optimal control (IOC) allows the retrieval of optimal cost function weights, or behavioral parameters, from human motion. The literature on IOC uses methods that are either based on a slow bilevel process or a fast but noise-sensitive minimization of optimality condition violation. Assuming equality-constrained optimal control models of human motion, this article presents a faster but robust approach to solving IOC using a single-level reformulation of the bilevel method and yields equi…

Spectral localization of single-nanoparticle plasmons through photonic substrate engineering
Shihao Feng, Juan-Feng Zhu, Xinyi Fan, Jindong Ai, Wenjie Zhou, Guangxin Liu, Jing-Feng Liu, Renming Liu, Wei Li, Lijun Guo, Lin Wu
https://arxiv.org/abs/2509.07699

Spectral localization of single-nanoparticle plasmons through photonic substrate engineering
Surface plasmon resonances (SPRs) are crucial for confining light beyond the diffraction limit, yet heavy metal losses often limit their spectral localization. Here, we propose a practical strategy for enabling the spectral localization of single-nanoparticle SPRs through photonic substrate engineering, which creates distinct optical pathways (OPs) to tailor the electromagnetic environments around plasmonic nanoparticles. By analyzing the multiplication factor spectrum of the projected local de…

Physics-Informed Machine Learning in Biomedical Science and Engineering
Nazanin Ahmadi, Qianying Cao, Jay D. Humphrey, George Em Karniadakis
https://arxiv.org/abs/2510.05433 htt…

Physics-Informed Machine Learning in Biomedical Science and Engineering
Physics-informed machine learning (PIML) is emerging as a potentially transformative paradigm for modeling complex biomedical systems by integrating parameterized physical laws with data-driven methods. Here, we review three main classes of PIML frameworks: physics-informed neural networks (PINNs), neural ordinary differential equations (NODEs), and neural operators (NOs), highlighting their growing role in biomedical science and engineering. We begin with PINNs, which embed governing equations…

Thanks for coming to my talk at @…, everyone! It was a joy and an honour to be invited – and I hope it was valuable! 🤗💚 Here are the slides: https://noti.st/matthiasott/ZXgFeg

Painting With the Web by Matthias Ott
Today’s Web is more complex, unpredictable, dynamic, and powerful than ever. Yet, 25 years after “A Dao of Web Design” we still approach building for the Web with a mindset of control, using linear workflows and static design tools that often don’t reflect the Web’s true nature and potential. The canvas we work on has transformed, the materials we use have changed. Together, we’ll explore how we can use web design engineering to start painting with the Web and create designs that ar…

Cybercriminals are using AI to execute highly targeted attacks at scale, causing people to unwittingly send money and sensitive information or simply open themselves up to theft.
Hackers are now able to rent generative AI large language models created in the underground cybercrime community to help formulate text-based scams.
But just as generative AI is enhancing and scaling social engineering attacks, so too is it giving defenders a leg up.

The hacking underworld has removed all of AI's guardrails, but the good guys are closing in
Fake Taylor Swift ads and malicious QR codes are just some of the newest ways cybercriminals are using AI as the cat-and-mouse cybersecurity game heats up.

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Haystack Engineering: Context Engineering for Heterogeneous and Agentic Long-Context Evaluation
Li, Fu, Wang, Zhang, Zeng, Sancak, Qiu, Wang, He, Bresson, Xia, Sun, Li

Distortion Minimization in Reverse Engineering for Additive Manufacturing: An Integrated 3D Scanning and Simulation Framework
Jannatul Bushra (The University of Arizona), Md Habibor Rahman (University of Massachusetts Dartmouth), Mohammed Shafae (The University of Arizona), Hannah D. Budinoff (The University of Arizona)
https://arxiv.org/a…

Distortion Minimization in Reverse Engineering for Additive Manufacturing: An Integrated 3D Scanning and Simulation Framework
Reverse engineering can be used to derive a 3D model of an existing physical part when such a model is not readily available. For parts that will be fabricated with subtractive and formative manufacturing processes, existing reverse engineering techniques can be readily applied, but parts produced with additive manufacturing can present new challenges due to the high level of process-induced distortions and unique part attributes. This paper introduces an integrated 3D scanning and process simu…

Students' Perception of LLM Use in Requirements Engineering Education: An Empirical Study Across Two Universities
Sharon Guardado, Risha Parveen, Zheying Zhang, Maruf Rayhan, Nirnaya Tripathi
https://arxiv.org/abs/2509.05995

Students' Perception of LLM Use in Requirements Engineering Education: An Empirical Study Across Two Universities
The integration of Large Language Models (LLMs) in Requirements Engineering (RE) education is reshaping pedagogical approaches, seeking to enhance student engagement and motivation while providing practical tools to support their professional future. This study empirically evaluates the impact of integrating LLMs in RE coursework. We examined how the guided use of LLMs influenced students' learning experiences, and what benefits and challenges they perceived in using LLMs in RE practices. The s…

Partially paywalled but still lots of juicy data. “State of the software engineering job market in 2025”: https://newsletter.pragmaticengineer.com/p/state-of-the-tech-market-in-2025
From which:

State of the software engineering job market in 2025
A deepdive into today’s tech jobs market, with exclusive data on tech jobs, AI engineering, Big Tech recruitment, the growing importance of location, and more

A multi-strategy improved gazelle optimization algorithm for solving numerical optimization and engineering applications
Qi Diao, Chengyue Xie, Yuchen Yin, Hoileong Lee, Haolong Yang
https://arxiv.org/abs/2509.07211

A multi-strategy improved gazelle optimization algorithm for solving numerical optimization and engineering applications
Aiming at the shortcomings of the gazelle optimization algorithm, such as the imbalance between exploration and exploitation and the insufficient information exchange within the population, this paper proposes a multi-strategy improved gazelle optimization algorithm (MSIGOA). To address these issues, MSIGOA proposes an iteration-based updating framework that switches between exploitation and exploration according to the optimization process, which effectively enhances the balance between local …

Impact of Fading Correlation on the High-SNR Regime of Reconfigurable Intelligent Surfaces
Paula Isabel Tilleria Lucero (Wireless Technology Laboratory, Department of Communications, School of Electrical and Computer Engineering, State University of Campinas), Bryan Fernando Sarango Rodr\'iguez (Wireless Technology Laboratory, Department of Communications, School of Electrical and Computer Engineering, State University of Campinas), Fernando Dar\'io Almeida Garc\'ia (Wirele…

A bit expensive but i can really recommend this book. It strikes a good balance between technical details and overview of current generative AI technology. It is also readable for non-developers/engineers like me without skipping too much technical details to understand what is going on.
https://www.amazon.nl/-/en/Chip…

A controllable anti-P-pseudo-Hermitian mechanical system and its application
Yanzheng Wang (Huanjiang Laboratory, Zhejiang University, Department of Mechanical and Aerospace Engineering, University of Missouri), Jianlei Zhao (Department of Mechanics and Engineering Science, Peking University), Qian Wu (Department of Mechanical and Aerospace Engineering, University of Missouri), Xiaoming Zhou (Key Laboratory of Dynamics and Control of Flight Vehicle of Ministry of Education, School of A…

A controllable anti-P-pseudo-Hermitian mechanical system and its application
A novel anti-P-pseudo-Hermitian mechanical system that integrates piezoelectric actuators and sensors with non-reciprocal coupling into mechanical beams is proposed. This configuration enables the system to exhibit programmable exceptional points (EPs), which are critical for enhancing sensitivity in sensing applications. Our theoretical analysis, supported by numerical simulations and experimental validation, demonstrates the system's capability to detect minute mass variations and identify su…

✨ Carbon-fiber smart plastic: Self-healing, shape-shifting and stronger than steel
#plastics

Carbon-fiber smart plastic: Self-healing, shape-shifting and stronger than steel
Aerospace engineering and materials science researchers at Texas A&M University have uncovered new properties of an ultra-durable, recyclable, smart plastic—paving the way for transformative applications in the defense, aerospace and automotive industries.

Learning to Rewrite Prompts for Bootstrapping LLMs on Downstream Tasks
Qinhao Zhou, Xiang Xiang, Kun He, John E. Hopcroft
https://arxiv.org/abs/2510.06695 https://

Learning to Rewrite Prompts for Bootstrapping LLMs on Downstream Tasks
In recent years, the growing interest in Large Language Models (LLMs) has significantly advanced prompt engineering, transitioning from manual design to model-based optimization. Prompts for LLMs generally comprise two components: the \textit{instruction}, which defines the task or objective, and the \textit{input}, which is tailored to the instruction type. In natural language generation (NLG) tasks such as machine translation, the \textit{input} component is particularly critical, while the \…

Toward Axion Signal Extraction in Semiconductor Spin Qubits Via Spectral Engineering
Xiangjun Tan, Zhanning Wang
https://arxiv.org/abs/2509.06791 https://a…

Toward Axion Signal Extraction in Semiconductor Spin Qubits Via Spectral Engineering
Recent advances in quantum sensing and computational technologies indicate the possibility of improving the precision of measurements aimed at detecting cosmological particles and weakly interacting massive particles using various qubit platforms. While recent progress has been made, mitigating environmental noise remains a challenge in extracting particle parameters with high fidelity. Addressing these challenges requires efforts on two levels. At the device level, the qubit and its array acti…

Austin-based Routefusion, whose API for financial institutions lets them embed accounts, payments, currency conversion, and compliance, raised a $26.7M Series A (Mary Ann Azevedo/Crunchbase News)
https://news.crunchbase.com/venture/fintech-startup-routefusion-…

Exclusive: Payments Tech Startup Routefusion Raises $26.7M Series A 
Routefusion says it will use its new funding to help grow its engineering product and compliance teams, and expand its go-to-market efforts.

I've apparently reached "Figure out IPV6 for my network" levels of unemployment.
So if you need a software engineering manager or something else vaguely me-shaped, hit me up.
https://grahams.github.io/verifyme/resume.pdf

Disa: Accurate Learning-based Static Disassembly with Attentions
Peicheng Wang, Monika Santra, Mingyu Liu, Cong Sun, Dongrui Zeng, Gang Tan
https://arxiv.org/abs/2507.07246

Disa: Accurate Learning-based Static Disassembly with Attentions
For reverse engineering related security domains, such as vulnerability detection, malware analysis, and binary hardening, disassembly is crucial yet challenging. The fundamental challenge of disassembly is to identify instruction and function boundaries. Classic approaches rely on file-format assumptions and architecture-specific heuristics to guess the boundaries, resulting in incomplete and incorrect disassembly, especially when the binary is obfuscated. Recent advancements of disassembly ha…

A Rapid Review Regarding the Concept of Legal Requirements in Requirements Engineering
Jukka Ruohonen
https://arxiv.org/abs/2509.06012 https://arxiv.org/pd…

A Rapid Review Regarding the Concept of Legal Requirements in Requirements Engineering
Out of a personal puzzlement, recent peer review comments, and demonstrable confusion in the existing literature, the paper presents a rapid review of the concept of legal requirements (LRs) in requirements engineering (RE) research. According to reviewing results, a normative understanding of LRs has often been present, although proper definitions and conceptual operationalizations are lacking. Some papers also see LRs as functional and others as non-functional requirements. Legal requirements…

Motion Exploration of Articulated Product Concepts in Interactive Sketching Environment
Kalyan Ramana Gattoz, Prasad S. Onkar
https://arxiv.org/abs/2510.08328 https://

Motion Exploration of Articulated Product Concepts in Interactive Sketching Environment
In the early stages of engineering design, it is essential to know how a product behaves, especially how it moves. As designers must keep adjusting the motion until it meets the intended requirements, this process is often repetitive and time-consuming. Although the physics behind these motions is usually based on simple equations, manually working through them can be tedious and inefficient. To ease this burden, some tasks are now handled by computers. One common method involves converting han…

A facile vector substrate platform via BaTiO3 membrane transfer enables high quality solution processed epitaxial PZT on silicon
Asraful Haque (Centre for Nanoscience,Engineering, Indian Institute of Science, Bengaluru, India), Antony Jeyaseelan (Centre for Nanoscience,Engineering, Indian Institute of Science, Bengaluru, India), Shubham Kumar Parate (Centre for Nanoscience,Engineering, Indian Institute of Science, Bengaluru, India), Srinivasan Raghavan (Centre for Nanoscience,Engineeri…

A facile vector substrate platform via BaTiO3 membrane transfer enables high quality solution processed epitaxial PZT on silicon
The direct integration of high-performance ferroelectric oxides with silicon remains challenging due to lattice mismatch, thermal incompatibility, and the need for high-temperature epitaxial growth. Here, a hybrid integration approach is demonstrated in which crystalline BaTiO3 (BTO) membranes are first transferred onto Pt coated Si substrates and subsequently used as vector substrates (VS) for the growth of epitaxial (001) Pb(Zr0.52Ti0.48)O3 (PZT) thin films via chemical solution deposition (C…

RAISE: A self-driving laboratory for interfacial property formulation discovery
Mohammad Nazeri (Institute of Biomedical Engineering, University of Toronto, Canada), Sheldon Mei (Department of Chemical Engineering and Applied Chemistry, University of Toronto, Canada), Jeffrey Watchorn (Acceleration Consortium, University of Toronto, Canada), Alex Zhang (Department of Mechanical and Industrial Engineering, University of Toronto, Canada), Erin Ng (Department of Chemical Engineering and A…

RAISE: A self-driving laboratory for interfacial property formulation discovery
Surface wettability is a critical design parameter for biomedical devices, coatings, and textiles. Contact angle measurements quantify liquid-surface interactions, which depend strongly on liquid formulation. Herein, we present the Robotic Autonomous Imaging Surface Evaluator (RAISE), a closed-loop, self-driving laboratory that is capable of linking liquid formulation optimization with surface wettability assessment. RAISE comprises a full experimental orchestrator with the ability of mixing li…

Hydrodynamic Insight Drives Multimodal Vortex-Field Dynamics via Streamline Engineering
Wenxiang Yan, Zheng Yuan, Yuan Gao, Zhaozhong Chen, Zhi-Cheng Ren, Xi-Lin Wang, Jianping Ding, Hui-Tian Wang
https://arxiv.org/abs/2507.07928

Hydrodynamic Insight Drives Multimodal Vortex-Field Dynamics via Streamline Engineering
Since the 1970s, analogies between laser dynamics and (super)fluid systems have elucidated phenomena from superconductivity to BoseEinstein condensation. Inspired by Coullet et al.s 1989 formalization of optical vortices via hydrodynamic whirlpools, we here advance a hydrodynamic paradigm for vortex_beam propagation. By treating the Poynting_vector trajectories as energy streamlines, we establish a three_dimensional map of photon trajectories and energy flow. Angular_spectrum engineering in mom…

Building a Runtime JAR inspector in 10 hours
https://devblogs.microsoft.com/java/building-a-runtime-jar-inspector-in-10-hours/

🌝 Reverse engineering the mysterious Up-Data Link Test Set from Apollo
http://www.righto.com/2025/07/reverse-engineering-mysterious-up-data.html
#electronics

Reverse engineering the mysterious Up-Data Link Test Set from Apollo
Back in 2021, a collector friend of ours was visiting a dusty warehouse in search of Apollo-era communications equipment. A box with NASA-st...

Evolutionary Profiles for Protein Fitness Prediction
Jigang Fan, Xiaoran Jiao, Shengdong Lin, Zhanming Liang, Weian Mao, Chenchen Jing, Hao Chen, Chunhua Shen
https://arxiv.org/abs/2510.07286

Evolutionary Profiles for Protein Fitness Prediction
Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequence space. Protein language models (pLMs) trained with masked language modeling (MLM) exhibit strong zero-shot fitness prediction; we provide a unifying view by interpreting natural evolution as implicit reward maximization and MLM as inverse reinforcement learning (IRL), in which extant sequences act as expert demonstrations and pLM log-odds serve as fitne…

Embedding Sustainability in Software Engineering Curriculum: A Case Study
Ruzanna Chitchyan, Niki Mahmoudi
https://arxiv.org/abs/2510.03321 https://arxiv.o…

Embedding Sustainability in Software Engineering Curriculum: A Case Study
Sustainability is increasingly recognized as a critical dimension of engineering education, yet its integration into Software Engineering curricula remains a challenge. This paper reports on a case study that examines how sustainability is being embedded across modules in the Software Engineering program at one university. The paper outlines the process through which academics and students co-identified opportunities for integration, guided by the five dimensions of the Sustainability Awareness…

AutoMLGen: Navigating Fine-Grained Optimization for Coding Agents
Shangheng Du, Xiangchao Yan, Dengyang Jiang, Jiakang Yuan, Yusong Hu, Xin Li, Liang He, Bo Zhang, Lei Bai
https://arxiv.org/abs/2510.08511

AutoMLGen: Navigating Fine-Grained Optimization for Coding Agents
Large language models (LLMs) have shown impressive performance in general programming tasks. However, in Machine Learning Engineering (MLE) scenarios such as AutoML and Kaggle competitions, achieving high performance depends heavily on expert intervention and repeated adjustments rather than simply generating correct code. When applied directly to these tasks, LLMs often lack fine-grained domain priors, and existing MLE approaches that use linear or tree-structured searches limit knowledge tran…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Unfitted hybrid high-order methods stabilized by polynomial extension for elliptic interface prob...
Erik Burman, Alexandre Ern, Romain Mottier

Rare-Earth Engineering of NaAlO3 Perovskites Unlocks Unified Optoelectronic, Thermoelectric, and Spintronic Functionalities
Muhammad Imran, Sikander Azam, Qaiser Rafiq, Amin Ur Rahman
https://arxiv.org/abs/2510.08130

Rare-Earth Engineering of NaAlO3 Perovskites Unlocks Unified Optoelectronic, Thermoelectric, and Spintronic Functionalities
Perovskite oxides are promising for energy and quantum technologies, but wide-gap hosts such as NaAlO3 suffer from deep-UV absorption and limited carrier transport. Using first-principles GGA+U+SOC calculations, we investigate Eu3+-, Gd3+-, and Tb3+-doped NaAlO3 and evaluate their electronic, optical, elastic, and thermoelectric properties. Rare-earth substitution is thermodynamically favorable (formation energies 1.2-1.6 eV) and induces strong f-p hybridization, reducing the pristine band gap …

Source: OpenAI awards bonuses to ~1,000 research and engineering employees, or ~30% of its staff, ranging from several hundred thousand to millions of dollars (Stephanie Palazzolo/The Information)
https://www.theinformation.com/briefings/o

OpenAI Pays Bonuses Ranging Up To Millions of Dollars to 1,000 Researchers, Engineers
OpenAI is paying bonuses to around 1,000 employees on its technical research and engineering teams, or about a third of the company, ranging from the low hundreds of thousands to millions, as the company gears up to release its latest flagship GPT-5 model and faces an ever-rising battle for AI talent, according to a person with knowledge of the bonuses. The size of the bonuses will be

Exploit Tool Invocation Prompt for Tool Behavior Hijacking in LLM-Based Agentic System
Yu Liu, Yuchong Xie, Mingyu Luo, Zesen Liu, Zhixiang Zhang, Kaikai Zhang, Zongjie Li, Ping Chen, Shuai Wang, Dongdong She
https://arxiv.org/abs/2509.05755

Exploit Tool Invocation Prompt for Tool Behavior Hijacking in LLM-Based Agentic System
LLM-based agentic systems leverage large language models to handle user queries, make decisions, and execute external tools for complex tasks across domains like chatbots, customer service, and software engineering. A critical component of these systems is the Tool Invocation Prompt (TIP), which defines tool interaction protocols and guides LLMs to ensure the security and correctness of tool usage. Despite its importance, TIP security has been largely overlooked. This work investigates TIP-rela…

Prompts Generalize with Low Data: Non-vacuous Generalization Bounds for Optimizing Prompts with More Informative Priors
David Madras (Richard), Joshua Safyan (Richard), Qiuyi (Richard), Zhang
https://arxiv.org/abs/2510.08413

Prompts Generalize with Low Data: Non-vacuous Generalization Bounds for Optimizing Prompts with More Informative Priors
Many prompt engineering techniques have been successful in practice, even when optimizing over a large prompt space with with a small amount of task-specific data. Recent work has partially explained this success by showing generalization bounds which apply PAC-Bayes theory to the discrete prompt space, but they are non-vacuous only in data-rich scenarios. We argue that such widespread success can be more fully explained through more carefully considering data- or distribution-dependent perplex…

Addressing Visual Impairments with Model-Driven Engineering: A Systematic Literature Review
Judith Michael, Lukas Netz, Bernhard Rumpe, Ingo M\"uller, John Grundy, Shavindra Wickramathilaka, Hourieh Khalajzadeh
https://arxiv.org/abs/2510.06483

Addressing Visual Impairments with Model-Driven Engineering: A Systematic Literature Review
Software applications often pose barriers for users with accessibility needs, e.g., visual impairments. Model-driven engineering (MDE), with its systematic nature of code derivation, offers systematic methods to integrate accessibility concerns into software development while reducing manual effort. This paper presents a systematic literature review on how MDE addresses accessibility for vision impairments. From 447 initially identified papers, 30 primary studies met the inclusion criteria. Abo…

From Ethical Declarations to Provable Independence: An Ontology-Driven Optimal-Transport Framework for Certifiably Fair AI Systems
Sukriti Bhattacharya, Chitro Majumdar
https://arxiv.org/abs/2510.08086

From Ethical Declarations to Provable Independence: An Ontology-Driven Optimal-Transport Framework for Certifiably Fair AI Systems
This paper presents a framework for provably fair AI that overcomes the limits of current bias mitigation methods by systematically removing all sensitive information and its proxies. Using ontology engineering in OWL 2 QL, it formally defines sensitive attributes and infers their proxies through logical reasoning, constructing a sigma algebra G that captures the full structure of biased patterns. Fair representations are then obtained via Delbaen Majumdar optimal transport, which generates var…

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Minimizing the Value-at-Risk of Loan Portfolio via Deep Neural Networks
Albert Di Wang, Ye Du

Saying #NO is not a free action in the world of #softwareengineering
https://sh…

End-to-End Quantum Algorithm for Topology Optimization in Structural Mechanics
Leonhard H\"olscher, Oliver Ahrend, Lukas Karch, Carlotta L'Estocq, Marc Marfany Andreu, Tobias Stollenwerk, Frank K. Wilhelm, Julia Kowalski
https://arxiv.org/abs/2510.07280

End-to-End Quantum Algorithm for Topology Optimization in Structural Mechanics
Topology optimization is a key methodology in engineering design for finding efficient and robust structures. Due to the enormous size of the design space, evaluating all possible configurations is typically infeasible. In this work, we present an end-to-end, fault-tolerant quantum algorithm for topology optimization that operates on the exponential Hilbert space representing the design space. We demonstrate the algorithm on the two-dimensional Messerschmitt-Bölkow-Blohm (MBB) beam problem. By…

ReNiL: Relative Neural Inertial Locator with Any-Scale Bayesian Inference
Kaixuan Wu (School of Computer Science, Wuhan University, Wuhan, China, School of Cyber Science and Engineering, Wuhan University, Wuhan, China), Yuanzhuo Xu (School of Computer Science, Wuhan University, Wuhan, China), Zejun Zhang (University of Southern California, Los Angeles, United States), Weiping Zhu (School of Computer Science, Wuhan University, Wuhan, China), Steve Drew (Department of Electrical and Soft…

ReNiL: Relative Neural Inertial Locator with Any-Scale Bayesian Inference
Pedestrian inertial localization is key for mobile and IoT services because it provides infrastructure-free positioning. Yet most learning-based methods depend on fixed sliding-window integration, struggle to adapt to diverse motion scales and cadences, and yield inconsistent uncertainty, limiting real-world use. We present ReNiL, a Bayesian deep-learning framework for accurate, efficient, and uncertainty-aware pedestrian localization. ReNiL introduces Inertial Positioning Demand Points (IPDPs)…

Cadence Design to acquire Hexagon's Stockholm-based design and engineering unit, a computer-aided engineering software provider, for €2.7B in cash and stock (Juby Babu/Reuters)
https://www.reuters.com/business/cadence-design-bu…

Variational Rank Reduction Autoencoders for Generative
Alicia Tierz, Jad Mounayer, Beatriz Moya, Francisco Chinesta
https://arxiv.org/abs/2509.08515 https://

Variational Rank Reduction Autoencoders for Generative
Generative thermal design for complex geometries is fundamental in many areas of engineering, yet it faces two main challenges: the high computational cost of high-fidelity simulations and the limitations of conventional generative models. Approaches such as autoencoders (AEs) and variational autoencoders (VAEs) often produce unstructured latent spaces with discontinuities, which restricts their capacity to explore designs and generate physically consistent solutions. To address these limitat…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs
Fatemeh Hadadi, Qinghua Xu, Domenico Bianculli, Lionel Briand

A Framework for Inherently Safer AGI through Language-Mediated Active Inference
Bo Wen
https://arxiv.org/abs/2508.05766 https://arxiv.org/pdf/2508.05766

A Framework for Inherently Safer AGI through Language-Mediated Active Inference
This paper proposes a novel framework for developing safe Artificial General Intelligence (AGI) by combining Active Inference principles with Large Language Models (LLMs). We argue that traditional approaches to AI safety, focused on post-hoc interpretability and reward engineering, have fundamental limitations. We present an architecture where safety guarantees are integrated into the system's core design through transparent belief representations and hierarchical value alignment. Our framewor…

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Optimizing Stateful Microservice Migration in Kubernetes with MS2M and Forensic Checkpointing
Hai Dinh-Tuan, Jialun Jiang

Parametric resonance and nonlinear dynamics in a coupled double-pendulum system
Yusheng Niu, Yixian Liu, Hongyan Fan, Zhenqi Bai, Yichi Zhang
https://arxiv.org/abs/2509.08509 ht…

Parametric resonance and nonlinear dynamics in a coupled double-pendulum system
Nonlinear dynamics plays a significant role in interdisciplinary fields spanning biology, engineering, mathematics, and physics. Under small-amplitude approximations, certain nonlinear systems can be effectively described by the linear Mathieu equation, which is widely recognized for modeling the response of systems with periodically modulated parameters. Here we investigated a collision-coupled double pendulum system within the framework of Lagrangian mechanics, further explored the nonlinear …

MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline
Rushi Qiang, Yuchen Zhuang, Anikait Singh, Percy Liang, Chao Zhang, Sherry Yang, Bo Dai
https://arxiv.org/abs/2510.07307

MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline
While Language Models (LMs) have made significant progress in automating machine learning engineering (MLE), the acquisition of high-quality MLE training data is significantly constrained. Current MLE benchmarks suffer from low scalability and limited applicability because they rely on static, manually curated tasks, demanding extensive time and manual effort to produce. We introduce MLE-Smith, a fully automated multi-agent pipeline, to transform raw datasets into competition-style MLE challeng…

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Traceability and Accountability in Role-Specialized Multi-Agent LLM Pipelines
Amine Barrak

Interactive Shaping of Granular Media Using Reinforcement Learning
Benedikt Kreis, Malte Mosbach, Anny Ripke, Muhammad Ehsan Ullah, Sven Behnke, Maren Bennewitz
https://arxiv.org/abs/2509.06469

Interactive Shaping of Granular Media Using Reinforcement Learning
Autonomous manipulation of granular media, such as sand, is crucial for applications in construction, excavation, and additive manufacturing. However, shaping granular materials presents unique challenges due to their high-dimensional configuration space and complex dynamics, where traditional rule-based approaches struggle without extensive engineering efforts. Reinforcement learning (RL) offers a promising alternative by enabling agents to learn adaptive manipulation strategies through trial …

Intel announces top-level executive changes, including the departure of its products chief, Michelle Holthaus, and establishes a new central engineering group (Zaheer Kachwala/Reuters)
https://www.reuters.com/technology/intel-a

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- A simple and efficient hybrid discretization approach to alleviate membrane locking in isogeometr...
Roger A. Sauer, Zhihui Zou, Thomas J. R. Hughes

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- AgentDroid: A Multi-Agent Framework for Detecting Fraudulent Android Applications
Ruwei Pan, Hongyu Zhang, Zhonghao Jiang, Ran Hou

Fundamental Costs of Noise-Robust Quantum Control: Speed Limits and Complexity
Junkai Zeng, Xiu-Hao Deng
https://arxiv.org/abs/2510.07183 https://arxiv.org…

Fundamental Costs of Noise-Robust Quantum Control: Speed Limits and Complexity
Noise is ubiquitous in quantum systems and is a major obstacle for the advancement of quantum information science. Noise-robust quantum control achieves high-fidelity operations by engineering the evolution path so that first-order noise contributions cancel at the final time. Such dynamical error correction typically incurs a time overhead beyond standard quantum speed limits. We derive general lower bounds on control complexity that quantify this overhead for quasi-static coherent noise under…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- PyHexTop: a compact Python code for topology optimization using hexagonal elements
Aditi Agarwal, Anupam Saxena, Prabhat Kumar

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Adaptive Protein Design Protocols and Middleware
Aymen Alsaadi, Jonathan Ash, Mikhail Titov, Matteo Turilli, Andre Merzky, Shantenu Jha, Sagar Khare

Internal memo: Microsoft is unifying its key Windows engineering teams under a single organization led by Windows chief Pavan Davuluri, reversing a 2018 split (Tom Warren/The Verge)
https://www.theverge.com/report/787796/microsoft-windows-reorg-…

Microsoft is bringing its Windows engineering teams back together again
Microsoft has announced an internal reorg of its Windows teams. The server and client engineering teams are now under a single leader again.

Single photon emission from lithographically-positioned engineered nanodiamonds for cryogenic applications
Vivekanand Tiwari, Zhaojin Liu, Hao-Cheng Weng, Krishna C Balram, John G Rarity, Soumen Mandal, Oliver A Williams, Gavin W Morley, Joe A Smith
https://arxiv.org/abs/2508.06424

Single photon emission from lithographically-positioned engineered nanodiamonds for cryogenic applications
Nitrogen-vacancy centres in nanodiamonds (NDs) provide a promising resource for quantum photonic systems. However, developing a technology beyond proof-of-principle physics requires optimally engineering its component parts. In this work, we present a hybrid materials platform by photolithographically positioning ball-milled isotopically-enriched NDs on broadband metal reflectors. The structure enhances the photonic collection efficiency, enabling cryogenic characterisation despite the limited …

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries
Maharaj, Munigala, Tamilselvam, Kumar, Sen, Kodeswaran, Mishra, Bhattacharyya

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Towards automatizing detection and quantification of intestinal metaplasia: a multi-expert compar...
Cano, Caviedes, Siabatto, Villarreal, Quijano, Bedoya, Viswanath, Cruz-Roa, Gonzalez, Romero

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- FuzzBox: Blending Fuzzing into Emulation for Binary-Only Embedded Targets
Carmine Cesarano, Roberto Natella

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Multi-Agent Taskforce Collaboration: Self-Correction of Compounding Errors in Long-Form Literatur...
Zhi Zhang, Yan Liu, Zhejing Hu, Gong Chen, Sheng-hua Zhong, Jiannong Cao

Memo: Meta Superintelligence Labs' products team, led by Nat Friedman, pushes staff to ditch Meta's slow internal systems in favor of external tools like Vercel (Pranav Dixit/Business Insider)
https://www.businessinsider.com/meta-super

Meta Superintelligence Labs executives are pushing staff to ditch slow internal systems for faster engineering tools
As part of Meta's big bet on superintelligence, it's steering its AI teams to new tools like Vercel and GitHub, as revealed by internal memos.

Characterization of low-nitrogen quantum diamond for pulsed magnetometry applications
Jiashen Tang, Connor A. Roncaioli, Andrew M. Edmonds, Atli Davidsson, Connor A. Hart, Matthew L. Markham, Ronald L. Walsworth
https://arxiv.org/abs/2509.06884

Characterization of low-nitrogen quantum diamond for pulsed magnetometry applications
Ensembles of nitrogen-vacancy (NV) centers in diamond are versatile quantum sensors with broad applications in the physical and life sciences. The concentration of neutral substitutional nitrogen ([N$_\text{s}^0$]) strongly influences coherence times, sensitivity, and optimal sensing strategies. Diamonds with [N$_\text{s}^0$] $\sim\,1-10\,\text{ppm}$ are a focus of recent material engineering efforts, with higher concentrations being favorable for continuous-wave optically detected magnetic res…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Challenging Bug Prediction and Repair Models with Synthetic Bugs
Ali Reza Ibrahimzada, Yang Chen, Ryan Rong, Reyhaneh Jabbarvand

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models
Akash Yadav, Ruda Zhang

Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- From Passive to Participatory: How Liberating Structures Can Revolutionize Our Conferences
Daniel Russo, Margaret-Anne Storey

Digital Twins for Software Engineering Processes
Robin Kimmel, Judith Michael, Andreas Wortmann, Jingxi Zhang
https://arxiv.org/abs/2510.05768 https://arxi…

Digital Twins for Software Engineering Processes
Digital twins promise a better understanding and use of complex systems. To this end, they represent these systems at their runtime and may interact with them to control their processes. Software engineering is a wicked challenge in which stakeholders from many domains collaborate to produce software artifacts together. In the presence of skilled software engineer shortage, our vision is to leverage DTs as means for better rep- resenting, understanding, and optimizing software engineering proce…

A comprehensive comparison of neural operators for 3D industry-scale engineering designs
Weiheng Zhong, Qibang Liu, Diab Abueidda, Seid Koric, Hadi Meidani
https://arxiv.org/abs/2510.05995

A comprehensive comparison of neural operators for 3D industry-scale engineering designs
Neural operators have emerged as powerful tools for learning nonlinear mappings between function spaces, enabling real-time prediction of complex dynamics in diverse scientific and engineering applications. With their growing adoption in engineering design evaluation, a wide range of neural operator architectures have been proposed for various problem settings. However, model selection remains challenging due to the absence of fair and comprehensive comparisons. To address this, we propose and …

[2025-10-10 Fri (UTC), 9 new articles found for cs.SE Software Engineering]
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[2025-09-10 Wed (UTC), 8 new articles found for cs.SE Software Engineering]
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[2025-09-11 Thu (UTC), 8 new articles found for cs.SE Software Engineering]
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[2025-08-11 Mon (UTC), 12 new articles found for cs.SE Software Engineering]
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Execution-Feedback Driven Test Generation from SWE Issues
Toufique Ahmed, Jatin Ganhotra, Avraham Shinnar, Martin Hirzel
https://arxiv.org/abs/2508.06365 https://

Execution-Feedback Driven Test Generation from SWE Issues
A software engineering issue (SWE issue) is easier to resolve when accompanied by a reproduction test. Unfortunately, most issues do not come with functioning reproduction tests, so this paper explores how to generate them automatically. The primary challenge in this setting is that the code to be tested is either missing or wrong, as evidenced by the existence of the issue in the first place. This has held back test generation for this setting: without the correct code to execute, it is diffic…

The Impact of Team Diversity in Agile Development Education
Marco Torchiano, Riccardo Coppola, Antonio Vetro', Xhoi Musaj
https://arxiv.org/abs/2509.08389 https://

The Impact of Team Diversity in Agile Development Education
Software Engineering is mostly a male-dominated sector, where gender diversity is a key feature for improving equality of opportunities, productivity, and innovation. Other diversity aspects, including but not limited to nationality and ethnicity, are often understudied.In this work we aim to assess the impact of team diversity, focusing mainly on gender and nationality, in the context of an agile software development project-based course. We analyzed 51 teams over three academic years, measuri…

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 …

Building Whitespace-Sensitive Languages Using Whitespace-Insensitive Components
Alexander Hellwig, Nico Jansen, Bernhard Rumpe
https://arxiv.org/abs/2510.08200 https://

Building Whitespace-Sensitive Languages Using Whitespace-Insensitive Components
In Software Language Engineering, there is a trend towards reusability by composing modular language components. However, this reusability is severely inhibited by a gap in integrating whitespace-sensitive and whitespace-insensitive languages. There is currently no consistent procedure for seamlessly reusing such language components in both cases, such that libraries often cannot be reused, and whitespacesensitive languages are developed from scratch. This paper presents a technique for using m…

Efficiently Ranking Software Variants with Minimal Benchmarks
Th\'eo Matricon, Mathieu Acher, Helge Spieker, Arnaud Gotlieb
https://arxiv.org/abs/2509.06716 https://

Efficiently Ranking Software Variants with Minimal Benchmarks
Benchmarking is a common practice in software engineering to assess the qualities and performance of software variants, coming from multiple competing systems or from configurations of the same system. Benchmarks are used notably to compare and understand variant performance, fine-tune software, detect regressions, or design new software systems. The execution of benchmarks to get a complete picture of software variants is highly costly in terms of computational resources and time. In this pape…

Analyzing the Instability of Large Language Models in Automated Bug Injection and Correction
Mehmet Bilal Er, Nagehan \.Ilhan, Umut Kuran
https://arxiv.org/abs/2509.06429 https:…

Analyzing the Instability of Large Language Models in Automated Bug Injection and Correction
The use of Large Language Models (LLMs) in software engineering tasks is growing, especially in the areas of bug fixing and code generation. Nevertheless, these models often yield unstable results; when executed at different times with the same input, they can generate radically different code. The consistency of LLMs in bug-fixing tasks has not yet been thoroughly assessed, despite the fact that this instability has typically been discussed in the literature in relation to code generation. The…

Minimal Data, Maximum Clarity: A Heuristic for Explaining Optimization
Amirali Rayegan, Tim Menzies
https://arxiv.org/abs/2509.08667 https://arxiv.org/pdf/…

Minimal Data, Maximum Clarity: A Heuristic for Explaining Optimization
Efficient, interpretable optimization is a critical but underexplored challenge in software engineering, where practitioners routinely face vast configuration spaces and costly, error-prone labeling processes. This paper introduces EZR, a novel and modular framework for multi-objective optimization that unifies active sampling, learning, and explanation within a single, lightweight pipeline. Departing from conventional wisdom, our Maximum Clarity Heuristic demonstrates that using less (but more…

ChatGPT for Code Refactoring: Analyzing Topics, Interaction, and Effective Prompts
Eman Abdullah AlOmar, Luo Xu, Sofia Martinez, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni
https://arxiv.org/abs/2509.08090

ChatGPT for Code Refactoring: Analyzing Topics, Interaction, and Effective Prompts
Large Language Models (LLMs), such as ChatGPT, have become widely popular and widely used in various software engineering tasks such as refactoring, testing, code review, and program comprehension. Although recent studies have examined the effectiveness of LLMs in recommending and suggesting refactoring, there is a limited understanding of how developers express their refactoring needs when interacting with ChatGPT. In this paper, our goal is to explore interactions related to refactoring betwe…

Learning From Software Failures: A Case Study at a National Space Research Center
Dharun Anandayuvaraj, Zain Hammadeh, Andreas Lund, Alexandra Holloway, James C. Davis
https://arxiv.org/abs/2509.06301 …

Learning From Software Failures: A Case Study at a National Space Research Center
Software failures can have significant consequences, making learning from failures a critical aspect of software engineering. While software organizations are recommended to conduct postmortems, the effectiveness and adoption of these practices vary widely. Understanding how engineers gather, document, share, and apply lessons from failures is essential for improving reliability and preventing recurrence. High-reliability organizations (HROs) often develop software systems where failures carry …

AI-Guided Exploration of Large-Scale Codebases
Yoseph Berhanu Alebachew
https://arxiv.org/abs/2508.05799 https://arxiv.org/pdf/2508.05799

AI-Guided Exploration of Large-Scale Codebases
Understanding large-scale, complex software systems is a major challenge for developers, who spend a significant portion of their time on program comprehension. Traditional tools such as static visualizations and reverse engineering techniques provide structural insights but often lack interactivity, adaptability, and integration with contextual information. Recent advancements in large language models (LLMs) offer new opportunities to enhance code exploration workflows, yet their lack of groun…

RustAssure: Differential Symbolic Testing for LLM-Transpiled C-to-Rust Code
Yubo Bai, Tapti Palit
https://arxiv.org/abs/2510.07604 https://arxiv.org/pdf/25…

RustAssure: Differential Symbolic Testing for LLM-Transpiled C-to-Rust Code
Rust is a memory-safe programming language that significantly improves software security. Existing codebases written in unsafe memory languages, such as C, must first be transpiled to Rust to take advantage of Rust's improved safety guarantees. RustAssure presents a system that uses Large Language Models (LLMs) to automatically transpile existing C codebases to Rust. RustAssure uses prompt engineering techniques to maximize the chances of the LLM generating idiomatic and safe Rust code. Moreove…