Tootfinder

Glasgow Caledonian University is looking to appoint a Technical Officer in Electronic Engineering.
Details and application at:
https://www.jobs.ac.uk/job/DNL566/technical-officer-electronic-engineering

Technical Officer (Electronic Engineering) at Glasgow Caledonian University
Explore an exciting academic career as a Technical Officer (Electronic Engineering). Don't miss out on other academic jobs. Click to apply and explore more opportunities.

Please share this link about the EIGHT (STEM / coding / design / engineering summer camps Shelly Fryer and I are teaching in June and July 2025 through "Summer at Providence Day School!"
https://lessons.wesfryer.com/courses/summer-2025

Lessons by Dr. Wesley Fryer (wesfryer.com) - Summer 2025
Students: Come have FUN this summer and develop your STEM / coding / design skills with Dr. Fryer and Mrs. Fryer at "Summer Day School at Providence Day School!" All week-long classes are open to BOTH current PDS students and students attending other schools! Direct links to register for each camp

Designing a Custom Chaos Engineering Framework for Enhanced System Resilience at Softtech
Ethem Utku Aktas, Burak Tuzlutas, Burak Yesiltas
https://arxiv.org/abs/2506.14281

Designing a Custom Chaos Engineering Framework for Enhanced System Resilience at Softtech
Chaos Engineering is a discipline which enhances software resilience by introducing faults to observe and improve system behavior intentionally. This paper presents a design proposal for a customized Chaos Engineering framework tailored for Softtech, a leading software development company serving the financial sector. It outlines foundational concepts and activities for introducing Chaos Engineering within Softtech, while considering financial sector regulations. Building on these principles, t…

Intel names new engineering leadership, appointing Srinivasan Iyengar, Jean-Didier Allegrucci, and Shailendra Desai, as part of CEO Lip-Bu Tan's turnaround (Ian King/Bloomberg)
https://www.bloomberg.com/news/articles/20

I think that "chatbot" is a bad design paradigm for most problems. It's actually the refusal to to design work.
https://tante.cc/2025/06/19/chatbot-is-bad-design/

"ChatBot" is bad design
As anyone who has every seen anything I created knows: I am not a designer. So take my reasoning and thinking here with a grain of salt. I do have many designers amongst my friends and I do think that a lot of software engineering falls within the domain of design to a certain degree. […]

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
Jonas Lau, Annie Tran
https://arxiv.org/abs/2506.15294 h…

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
This paper discusses a popular UX research activity, feature prioritization, using the User Experience Research Point of View (UXR PoV) Playbook framework. We describe an application of multinomial logistic regression, frequently marketed as MaxDiff, for prioritizing product features in consumer product development. It addresses challenges of traditional surveying techniques. We propose a solution using MaxDiff to generate a reliable preference list with a reasonable sample size. We also adapt …

Oren Cass has a knack for reverse engineering a reasoned explanation for Trump’s latest policy, only to fall out of sync when it turns out Trump doesn’t work that way.
Here he is last week lamenting how “commentators stuck in the old world seem confused” in worrying about the US being dragged into a war with Iran. Instead, he explains confidently, Israel will “handle its own business”, while an “America First” US will “step back from conflicts in the Middle East”.

Is Israel the Ideal "America First" Ally?
And more from this week...

Near-field optical mode engineering-enabled freeform nonlocal metasurfaces
Zhongjun Jiang, Tianxiang Dai, Shuwei Guo, Soyaib Sohag, Yixuan Shao, Chenkai Mao, Andrea Al\`u, Jonathan A. Fan, You Zhou
https://arxiv.org/abs/2506.15495

Near-field optical mode engineering-enabled freeform nonlocal metasurfaces
Nanophotonic technologies inherently rely on tailoring light-matter interactions through the excitation and interference of deeply confined optical resonances. However, existing concepts in optical mode engineering remain heuristic and are challenging to extend towards complex and multi-functional resonant phenomena. Here, we introduce an inverse design framework that optimizes near-field distributions, ideally suited to tailor Mie-type modes within dielectric nanophotonic structures, and we de…

Generating Shakespeare-like text with an n-gram language model is straight forward and quite simple. But, don't expect to much of it. It will not be able to recreate a lost Shakespear play for you ;-) It's merely a parrot, making up well sounding sentences out of fragments of original Shakespeare texts...
#ise2025

Is there… like… an engineering reason that sometimes #AWS DynamoDB takes a long time (minutes, not seconds) to create an index (GSI) on an actually-empty table?

May 2025 recap | The latest edition of the GÉANT School of Software Engineering, hosted by PCSS, brought together developers and experts from across Europe to explore generative #AI tools, risks, secure coding practices.
Highlights:
🔹#GenAI Buzz-Free Programming with LLMs – training by Maciej Łabędzki…

Responsible AI in Practice: Shaping a Safer Future for AI-Powered Software Development | GÉANT CONNECT Online
Poznań, 20–22 May 2025 — The latest edition of the GÉANT School of Software Engineering, held at the Poznań Supercomputing and Networking Center (PSNC), brought together top-tier developers and experts from across Europe for a deep-dive into generative AI tools, risks, and secure coding practices. At the core of the event was the acclaimed training

Engineering Supercomputing Platforms for Biomolecular Applications
Robert Welch, Charles Laughton, Oliver Henrich, Tom Burnley, Daniel Cole, Alan Real, Sarah Harris, James Gebbie-Rayet
https://arxiv.org/abs/2506.15585

Engineering Supercomputing Platforms for Biomolecular Applications
A range of computational biology software (GROMACS, AMBER, NAMD, LAMMPS, OpenMM, Psi4 and RELION) was benchmarked on a representative selection of HPC hardware, including AMD EPYC 7742 CPU nodes, NVIDIA V100 and AMD MI250X GPU nodes, and an NVIDIA GH200 testbed. The raw performance, power efficiency and data storage requirements of the software was evaluated for each HPC facility, along with qualitative factors such as the user experience and software environment. It was found that the diversit…

The word "hacker" has been hijacked to mean something even worse than "cracker" (from LinkedIn):

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- An improved point-to-surface contact algorithm with penalty method for peridynamics
Haoran Zhang, Lisheng Liu, Xin Lai, Jun Li

An interview with Craig Federighi on the journey to iPadOS' new windowing system and menu bar, the iPad's essence as a "magical piece of glass", and more (Federico Viticci/MacStories)
https://www.macstories.net/…

Interview: Craig Federighi Opens Up About iPadOS, Its Multitasking Journey, and the iPad’s Essence
It’s a cool, sunny morning at Apple Park as I’m walking my way along the iconic glass ring to meet with Apple’s SVP of Software Engineering, Craig Federighi, for a conversation about the iPad. It’s the Wednesday after WWDC, and although there are still some developers and members of the press around Apple’s campus, it

Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach
Wenqi Guan, Yang Fang
https://arxiv.org/abs/2506.15512

Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach
Large Language Models have brought a radical change in the process of remote learning students, among other aspects of educative activities. Current retrieval of remote learning resources lacks depth in contextual meaning that provides comprehensive information on complex student queries. This work proposes a novel approach to enhancing remote learning retrieval by integrating GPT-based models within the LangChain framework. We achieve this system in a more intuitive and productive manner using…

#PlatformEngineering: Evolution or Rebranding? #DevOps
https://www.pulumi.com/blog/platform-eng-r

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
Wenhao Li, Selvakumar Manickam, Yung-wey Chong, Shankar Karuppayah
https://arxiv.org/abs/2506.15656 …

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
Phishing websites continue to pose a significant cybersecurity threat, often leveraging deceptive structures, brand impersonation, and social engineering tactics to evade detection. While recent advances in large language models (LLMs) have enabled improved phishing detection through contextual understanding, most existing approaches rely on single-agent classification facing the risks of hallucination and lack interpretability or robustness. To address these limitations, we propose PhishDebate…

'Tariff engineering' is making a comeback as businesses employ creative ways to skirt higher duties (Anniek Bao/CNBC)
https://www.cnbc.com/2025/06/18/businesses-tweak-products-to-qualify-for-lowter-tariffed-categories-.html
http://www.memeorandum.com/250618/p34#a250618p34

Weyl semimetal engineering by symmetry control in NiTe$_2$
Marcos G. O. Junior, Augusto L. Ara\'ujo, Emmanuel V. C. Lopes, Tome M. Schmidt
https://arxiv.org/abs/2506.13908

Weyl semimetal engineering by symmetry control in NiTe$_2$
In this work, we investigate the emergence of Weyl points in an inversion symmetry-breaking 1T-NiTe$_2$ system. Through first-principles calculations based on the density functional theory combined with tight-binding methods, distinct number of Weyl crossings arise under an appropriate symmetry breaking. We identify three sets of Weyl points by breaking the inversion symmetry in NiTe$_2$, resulting in a total of 28 Weyl crossings. The first set comes from the Dirac semimetal, whereas the other …

Unified Software Engineering agent as AI Software Engineer
Leonhard Applis, Yuntong Zhang, Shanchao Liang, Nan Jiang, Lin Tan, Abhik Roychoudhury
https://arxiv.org/abs/2506.14683 …

Unified Software Engineering agent as AI Software Engineer
The growth of Large Language Model (LLM) technology has raised expectations for automated coding. However, software engineering is more than coding and is concerned with activities including maintenance and evolution of a project. In this context, the concept of LLM agents has gained traction, which utilize LLMs as reasoning engines to invoke external tools autonomously. But is an LLM agent the same as an AI software engineer? In this paper, we seek to understand this question by developing a U…

Right a few days before I'll be talking about patterns in DRAM init at #GPN23, #Binarly are posting on their type inference tooling:

Type Inference for Decompiled Code: From Hidden Semantics to Structured Insights
Learn how Binarly enhances decompiled code by recovering meaningful type info—boosting binary analysis, triage, and reverse engineering accuracy.

The best artificial Total #SolarEclipse ever, delivered by ESA's #Proba3 spacecraft duo of which one carries the telescope while the other plays Moon - this allows imaging the solar #corona closer to the photosphere than any other coronagraph: https://www.esa.int/Enabling_Support/Space_Engineering_Technology/Proba-3/Proba-3_s_first_artificial_solar_eclipse

Energy-consistent dynamic fracture phase field models: unilateral constraints and finite element simulations
Md Mamun Miah, Ryuhei Wakida, Masato Kimura
https://arxiv.org/abs/2506.14788

Energy-consistent dynamic fracture phase field models: unilateral constraints and finite element simulations
Phase field models have emerged as a powerful and flexible framework for simulating complex interface-driven phenomena across a wide range of scientific and engineering applications. In fracture mechanics, the phase field approach--formulated as a gradient flow of the Griffith fracture energy with Ambrosio-Tortorelli regularization--has gained significant attention for its ability to capture complex crack topologies. In this study, we propose a dynamic fracture phase field model (DF-PFM) based …

"The biggest problem facing software engineering is the one it will
never solve - politics."
-- Gavin Baker, ca 1996, An unusually cynical moment inspired
by working on a large project beseiged by politics

Engineering teams often get stuck striving for perfection, not out of laziness, but due to an insatiable desire to improve. Join Tim Schmolka next week at Berlin Buzzwords to discover how teams can overcome perfectionism. He will discuss the significance of setting clear boundaries, balancing quality with timely delivery, and focusing on what truly matters.
Learn more:

The Perfection Trap
Many engineering teams face a common struggle: the desire to deliver perfect solutions can delay projects and limit business impact. This session explores how the familiar Parkinson’s Law is often misunderstood in engineering contexts. Instead of laziness, it’s excessive craftsmanship and relentless perfectionism that extend timelines. Through real-world examples and practical insights, you’ll learn about the “perfection pressure spectrum,” which helps diagnose whether your team is st…

Distracting myself with crafting tonight. Tonight's project - reverse engineering a skirt I already own. I want to use the pattern to make a skirt with this ocean-themed fabric.

PFMBench: Protein Foundation Model Benchmark
Zhangyang Gao, Hao Wang, Cheng Tan, Chenrui Xu, Mengdi Liu, Bozhen Hu, Linlin Chao, Xiaoming Zhang, Stan Z. Li
https://arxiv.org/abs/2506.14796

PFMBench: Protein Foundation Model Benchmark
This study investigates the current landscape and future directions of protein foundation model research. While recent advancements have transformed protein science and engineering, the field lacks a comprehensive benchmark for fair evaluation and in-depth understanding. Since ESM-1B, numerous protein foundation models have emerged, each with unique datasets and methodologies. However, evaluations often focus on limited tasks tailored to specific models, hindering insights into broader generali…

Anthropic details how it built its multi-agent Claude Research system, claiming significant improvements in internal evaluations over single-agent systems (Anthropic)
https://www.anthropic.com/engineering/built-multi-agent-research-system

How we built our multi-agent research system
On the the engineering challenges and lessons learned from building Claude's Research system

Doppelg\"anger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Daewon Kang, YeongHwan Shin, Doyeon Kim, Kyu-Hwan Jung, Meong Hi Son
https://arxiv.org/abs/2506.14539

Doppelgänger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack
Since the advent of large language models, prompt engineering now enables the rapid, low-effort creation of diverse autonomous agents that are already in widespread use. Yet this convenience raises urgent concerns about the safety, robustness, and behavioral consistency of the underlying prompts, along with the pressing challenge of preventing those prompts from being exposed to user's attempts. In this paper, we propose the ''Doppelgänger method'' to demonstrate the risk of an agent being hij…

Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison
Jan C. Schulze, Alexander Mitsos
https://arxiv.org/abs/2506.12819

Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison
Computationally cheap yet accurate enough dynamical models are vital for real-time capable nonlinear optimization and model-based control. When given a computationally expensive high-order prediction model, a reduction to a lower-order simplified model can enable such real-time applications. Herein, we review state-of-the-art nonlinear model order reduction methods and provide a theoretical comparison of method properties. Additionally, we discuss both general-purpose methods and tailored appro…

Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers
Daniel D'souza, Julia Kreutzer, Adrien Morisot, Ahmet \"Ust\"un, Sara Hooker
https://arxiv.org/abs/2506.14702

Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers
One of the most profound challenges of modern machine learning is performing well on the long-tail of rare and underrepresented features. Large general-purpose models are trained for many tasks, but work best on high-frequency use cases. After training, it is hard to adapt a model to perform well on specific use cases underrepresented in the training corpus. Relying on prompt engineering or few-shot examples to maximize the output quality on a particular test case can be frustrating, as models …

SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning
Hexian Ni, Tao Lu, Haoyuan Hu, Yinghao Cai, Shuo Wang
https://arxiv.org/abs/2506.14648

SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning
Preference-based Reinforcement Learning (PbRL) methods provide a solution to avoid reward engineering by learning reward models based on human preferences. However, poor feedback- and sample- efficiency still remain the problems that hinder the application of PbRL. In this paper, we present a novel efficient query selection and preference-guided exploration method, called SENIOR, which could select the meaningful and easy-to-comparison behavior segment pairs to improve human feedback-efficiency…

my annoying engineering trait is that i don't like hardware abstraction layers
they're usually irritating to write code for, and equally irritating to reverse-engineer whenever i need to. i mostly end up reverse-engineering these days

Cool research paper (presented at HARRIS but I finally had time to read the full paper) on hardware reverse engineering education https://dl.acm.org/doi/10.1145/3641554.3701797
According to their fairly extensive survey (section 4, figure 1), my 2014 course on hardware R…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Predicting the Understandability of Computational Notebooks through Code Metrics Analysis
Ghahfarokhi, Asadi, Asgari, Mohammadi, Heydarnoori, Rizi

Engineering Fast and Space-Efficient Recompression from SLP-Compressed Text
Ankith Reddy Adudodla, Dominik Kempa
https://arxiv.org/abs/2506.12011 https://

Engineering Fast and Space-Efficient Recompression from SLP-Compressed Text
Compressed indexing enables powerful queries over massive and repetitive textual datasets using space proportional to the compressed input. While theoretical advances have led to highly efficient index structures, their practical construction remains a bottleneck (especially for complex components like recompression RLSLP), a grammar-based representation crucial for building powerful text indexes that support widely used suffix array queries. In this work, we present the first implementation …

Forecasting the spatiotemporal evolution of fluid-induced microearthquakes with deep learning
Jaehong Chung, Michael Manga, Timothy Kneafsey, Tapan Mukerji, Mengsu Hu
https://arxiv.org/abs/2506.14923

Forecasting the spatiotemporal evolution of fluid-induced microearthquakes with deep learning
Microearthquakes (MEQs) generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their full spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems (EGS), CO$_2$ sequestration and other geo-engineering applications. We present a transformer-based deep learning model that ingests hydraulic stimulation history and prior MEQ observations to forecast four key quantities: cumulative MEQ count, cum…

[2025-06-19 Thu (UTC), 3 new articles found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

The World of AI: A Novel Approach to AI Literacy for First-year Engineering Students
Siddharth Siddharth, Brainerd Prince, Amol Harsh, Shreyas Ramachandran
https://arxiv.org/abs/2506.08041

The World of AI: A Novel Approach to AI Literacy for First-year Engineering Students
This work presents a novel course titled The World of AI designed for first-year undergraduate engineering students with little to no prior exposure to AI. The central problem addressed by this course is that engineering students often lack foundational knowledge of AI and its broader societal implications at the outset of their academic journeys. We believe the way to address this gap is to design and deliver an interdisciplinary course that can a) be accessed by first-year undergraduate engin…

Anomalous diffusion for mass transport phenomena I: Analytic solutions to time fractional diffusion
Nathaniel G. Hermann, M. Shane Hutson
https://arxiv.org/abs/2506.14043

Anomalous diffusion for mass transport phenomena I: Analytic solutions to time fractional diffusion
Mass transport problems are ubiquitous in diverse fields of physics and engineering. With the development of fractional calculus, many have taken to studying problems of fractional mass transport either through numerical simulations or through complex mathematical structures (e.g. Fox-H functions). Here, we present a set of analytic solutions to common time fractional diffusion problems, written in terms of Mittag-Leffler and M-Wright functions, as well as generalized fractional error and compl…

A case study: the savings potential thanks to FAIR data in one Materials Science PhD project
Michael Seitz, Nick Garabedian, Ilia Bagov, Christian Greiner
https://arxiv.org/abs/2506.12043

A case study: the savings potential thanks to FAIR data in one Materials Science PhD project
The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles have gained significant attention as a means to enhance data sharing, collaboration, and reuse across various domains. Here, we explore the potential benefits of implementing FAIR data practices within engineering projects, with a monetary focus in the German context, but by considering aspects which are relatively universal. By examining the FAIR-data aspect of a Materials Science and Engineering PhD project, it becom…

Look, I’d really like to help with your surveys, but I’m already getting stuck at the first question!
#AcademicChatter #interdisciplinary

Min arbejdsgiver leder efter en ny medarbejder.
Det er i Thisted- og jeg kan bekræfte, at det er en hyggelig lille firma :)
https://www.jobindex.dk/jobannonce/h1571567/dahl-engineering-soeger-en-alsidig-produktionsmedarbejd…

Deep Learning-Based Prediction of High Explosive Induced Fluid Dynamics
Francis G. VanGessel, Mitul Pandya
https://arxiv.org/abs/2506.14710 https://…

Deep Learning-Based Prediction of High Explosive Induced Fluid Dynamics
Underwater explosions produce complex fluid phenomena relevant to diverse applications including maritime engineering, medical therapeutics, and inertial confinement fusion. These systems exhibit multiphase flows, chemical kinetics, and highly compressible dynamics that challenge traditional computational approaches. Current hydrodynamic solvers, while accurate, are computationally expensive and non-differentiable, limiting their use in design optimization and real-time applications. Here we sh…

A Mapping Study About Training in Industry Context in Software Engineering
Breno Alves de Andrade, Rodrigo Siqueira, Lidiane Gomes, Antonio Oliveira, Danilo Monteiro Ribeiro
https://arxiv.org/abs/2506.12590

A Mapping Study About Training in Industry Context in Software Engineering
Context: Corporate training plays a strategic role in the continuous development of professionals in the software engineering industry. However, there is a lack of systematized understanding of how training initiatives are designed, implemented, and evaluated within this domain. Objective: This study aims to map the current state of research on corporate training in software engineering in industry settings, using Eduardo Salas' training framework as an analytical lens. Method: A systematic…

Leveraging erasure errors in logical qubits with metastable $^{171}$Yb atoms
Bichen Zhang, Genyue Liu, Guillaume Bornet, Sebastian P. Horvath, Pai Peng, Shuo Ma, Shilin Huang, Shruti Puri, Jeff D. Thompson
https://arxiv.org/abs/2506.13724

Leveraging erasure errors in logical qubits with metastable $^{171}$Yb atoms
Implementing large-scale quantum algorithms with practical advantage will require fault-tolerance achieved through quantum error correction, but the associated overhead is a significant cost. The overhead can be reduced by engineering physical qubits with fewer errors, and by shaping the residual errors to be more easily correctable. In this work, we demonstrate quantum error correcting codes and logical qubit circuits in a metastable ${}^{171}$Yb qubit with a noise bias towards erasure errors,…

Anomalous diffusion for mass transport phenomena II: Subdiffusion in polydimethylsiloxane (PDMS)
Nathaniel G. Hermann, Dmitry A. Markov, M. Shane Hutson
https://arxiv.org/abs/2506.14600

Anomalous diffusion for mass transport phenomena II: Subdiffusion in polydimethylsiloxane (PDMS)
Polydimethylsiloxane (PDMS) is a glassy polymer widely used in biomedical engineering, namely in microfluidics applications. However, PDMS is known to interact with hydrophobic chemicals. This interaction is exacerbated at the scale of microfluidics, making careful modeling of in-device concentrations vital for PDMS-based microfluidic devices. While it has been previously reported that many chemicals diffuse through PDMS, here we report that diffusion in PDMS is anomalous, i.e. characterized by…

“When people say I changed the culture of Boeing, that was the intent, so that it’s run like a business rather than a great engineering firm.”
– Harry Stonecipher, former Boeing CEO

"We can argue over the specific time at which empathy in software design entered the software engineering body of knowledge. Barry Boehm’s 1999 paper “Escaping the Software Tar Pit” introduces the modified golden rule to software engineering:
> Do unto others as you would have them do unto you — if you were like them."

Works-magnet: Accelerating Metadata Curation for Open Science
Eric Jeangirard
https://arxiv.org/abs/2506.14430 https://arxiv.org/pdf/…

Works-magnet: Accelerating Metadata Curation for Open Science
The transition to Open Science necessitates robust and reliable metadata. While national initiatives, such as the French Open Science Monitor, aim to track this evolution using open data, reliance on proprietary databases persists in many places. Open platforms like OpenAlex still require significant human intervention for data accuracy. This paper introduces Works-magnet, a project by the French Ministry of Higher Education and Research (MESR) Data Science & Engineering Team. Works-magnet is d…

How to find #deadcode in your #Java services
https://blog.picnic.nl/how-to-find-dea

I just read Lorena Barba's "Experience embracing genAI in an engineering computations course: What went wrong and what next" and it's one of the best pieces I've read on the challenges of using LLMs in beginning computing classrooms.
"Students quickly developed patterns of using AI as a shortcut rather than a learning companion, leading to decreased attendance and an 'illusion of competence'"
13/10 will read again
https://doi.org/10.6084/m9.figshare.28926647.v1

Nano-resolved sensing of 3D electromagnetic fields via single emitters' extreme variation of enhanced spontaneous emission
R. Margoth C\'ordova-Castro, Dirk Jonker, Cl\'ement Cabriel, Mario Zapata-Herrera, Bart van Dam, Yannick De Wilde, Robert W. Boyd, Arturo Susarrey-Arce, Ignacio Izeddin, Valentina Krachmalnicoff
https://

Nano-resolved sensing of 3D electromagnetic fields via single emitters' extreme variation of enhanced spontaneous emission
Controlling quantum light-matter interactions at scales smaller than the diffraction limit at the single quantum emitter level is a critical challenge to the goal of advancing quantum technologies. We introduce a novel material platform that enables precise engineering of spontaneous emission changes in molecular single emitters through 3D nanofields. This platform is based on a 3D hollow plasmonic nanomaterial arranged in a square lattice, uniformly scalable to the centimeter scale while maint…

In our #ISE2025 lecture last Wednesday, we learned how in n-gram language models via Markov assumption and maximum likelihood estimation we can predict the probability of the occurrence of a word given a specific context (i.e. n words previous in the sequence of words).
#NLP

[2025-06-20 Fri (UTC), no new articles found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

AST-Enhanced or AST-Overloaded? The Surprising Impact of Hybrid Graph Representations on Code Clone Detection
Zixian Zhang, Takfarinas Saber
https://arxiv.org/abs/2506.14470

AST-Enhanced or AST-Overloaded? The Surprising Impact of Hybrid Graph Representations on Code Clone Detection
As one of the most detrimental code smells, code clones significantly increase software maintenance costs and heighten vulnerability risks, making their detection a critical challenge in software engineering. Abstract Syntax Trees (ASTs) dominate deep learning-based code clone detection due to their precise syntactic structure representation, but they inherently lack semantic depth. Recent studies address this by enriching AST-based representations with semantic graphs, such as Control Flow Gra…

Directed Acyclic Graph Convolutional Networks
Samuel Rey, Hamed Ajorlou, Gonzalo Mateos
https://arxiv.org/abs/2506.12218 https://arxi…

Directed Acyclic Graph Convolutional Networks
Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architecture search. In this work, we introduce the DAG Convolutional Network (DCN), a novel graph neural network (GNN) architecture designed specifically for convolutional learning from signals supported on DAGs. The DCN leverages causal graph filters to learn nodal representations that account for the partial ordering inherent to DAGs, a strong inductive bias d…

Berlin Buzzwords is made possible by the incredible support of our partners!
A big thank you to OpenSearch Project and Vespa.ai, Kleinanzeigen and Superlinked, Bloomberg Engineering, Elastic, Search Guard, Restate, Apple, OpenSource Connections, Qdrant, and Voyager.
Their support brings Berlin Buzzwords to life each year!
#bbuzz

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Hao Peng, Yunjia Qi, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
https://arxiv.org/abs/2506.09942 …

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing large language models (LLMs), with verification engineering playing a central role. However, best practices for RL in instruction following remain underexplored. In this work, we explore the verification challenge in RL for instruction following and propose VerIF, a verification method that combines rule-based code verification with LLM-based verification from a large reasoning model (e.g., QwQ-32B). …

[2025-06-20 Fri (UTC), no new articles found for cs.SE Software Engineering]
toXiv_bot_toot

Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
Jan van Delden, Julius Schultz, Sebastian Rothe, Christian Libner, Sabine C. Langer, Timo L\"uddecke
https://arxiv.org/abs/2506.15263

Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
Structural vibrations are a source of unwanted noise in engineering systems like cars, trains or airplanes. Minimizing these vibrations is crucial for improving passenger comfort. This work presents a novel design optimization approach based on guided flow matching for reducing vibrations by placing beadings (indentations) in plate-like structures. Our method integrates a generative flow matching model and a surrogate model trained to predict structural vibrations. During the generation process…

[2025-06-19 Thu (UTC), 9 new articles found for cs.SE Software Engineering]
toXiv_bot_toot

Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains
Emanuel Moss, Elizabeth Watkins, Christopher Persaud, Passant Karunaratne, Dawn Nafus
https://arxiv.org/abs/2506.14567

Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains
Generative AI tools have become more prevalent in engineering workflows, particularly through chatbots and code assistants. As the perceived accuracy of these tools improves, questions arise about whether and how those who work in high-precision domains might maintain vigilance for errors, and what other aspects of using such tools might trouble their work. This paper analyzes interviews with hardware and software engineers, and their collaborators, who work in integrated circuit design to iden…

Documenting Your Prompts a Best Practice for Success
#promptengineering

Coercive Field Reduction in Ultra-thin Al1-XScXN via Interfacial Engineering with a Scandium Electrode
Yinuo Zhang, Rajeev Kumar Rai, Giovanni Esteves, Yubo Wang, Deep M. Jariwala, Eric A. Stach, Roy H. Olsson III
https://arxiv.org/abs/2506.10169

Coercive Field Reduction in Ultra-thin Al1-XScXN via Interfacial Engineering with a Scandium Electrode
Aluminum scandium nitride (AlScN) ferroelectrics are promising for next-generation non-volatile memory applications due to their high remnant polarization as well as fast switching and scalability to nanometer thicknesses. As device dimensions shrink, the coercive field in ultra-thin ferroelectric films increases, which challenges low-voltage operation. We demonstrate that interfacial engineering through bottom electrode selection and strain management reduces this coercive field increase and i…

The Tech DEI Backlash -- The Changing Landscape of Diversity, Equity, and Inclusion in Software Engineering
Sonja M. Hyrynsalmi, Mary Sanchez-Gordon, Anna Szlavi, Letizia Jaccheri
https://arxiv.org/abs/2506.14232

The Tech DEI Backlash -- The Changing Landscape of Diversity, Equity, and Inclusion in Software Engineering
Not long ago, Diversity, Equity, and Inclusion (DEI) initiatives were a top priority for leading software companies. However, in a short period, a wave of backlash has led many firms to re-assess their DEI strategies. Responding to this DEI backlash is crucial in academic research, especially because, currently, little scholarly research has been done on it. In this paper, therefore, we have set forth the following research question (RQ): "How have leading software companies changed their DEI s…

ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
Yuki Imajuku, Kohki Horie, Yoichi Iwata, Kensho Aoki, Naohiro Takahashi, Takuya Akiba
https://arxiv.org/abs/2506.09050

ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
How well do AI systems perform in algorithm engineering for hard optimization problems in domains such as package-delivery routing, crew scheduling, factory production planning, and power-grid balancing? We introduce ALE-Bench, a new benchmark for evaluating AI systems on score-based algorithmic programming contests. Drawing on real tasks from the AtCoder Heuristic Contests, ALE-Bench presents optimization problems that are computationally hard and admit no known exact solution. Unlike short-du…

Get on the Train or be Left on the Station: Using LLMs for Software Engineering Research
Bianca Trinkenreich, Fabio Calefato, Geir Hanssen, Kelly Blincoe, Marcos Kalinowski, Mauro Pezz\`e, Paolo Tell, Margaret-Anne Storey
https://arxiv.org/abs/2506.12691

Get on the Train or be Left on the Station: Using LLMs for Software Engineering Research
The adoption of Large Language Models (LLMs) is not only transforming software engineering (SE) practice but is also poised to fundamentally disrupt how research is conducted in the field. While perspectives on this transformation range from viewing LLMs as mere productivity tools to considering them revolutionary forces, we argue that the SE research community must proactively engage with and shape the integration of LLMs into research practices, emphasizing human agency in this transformation…

Large Language Models for Unit Testing: A Systematic Literature Review
Quanjun Zhang, Chunrong Fang, Siqi Gu, Ye Shang, Zhenyu Chen, Liang Xiao
https://arxiv.org/abs/2506.15227

Large Language Models for Unit Testing: A Systematic Literature Review
Unit testing is a fundamental practice in modern software engineering, with the aim of ensuring the correctness, maintainability, and reliability of individual software components. Very recently, with the advances in Large Language Models (LLMs), a rapidly growing body of research has leveraged LLMs to automate various unit testing tasks, demonstrating remarkable performance and significantly reducing manual effort. However, due to ongoing explorations in the LLM-based unit testing field, it is…

This week, we were discussing the central question Can we "predict" a word? as the basis for statistical language models in our #ISE2025 lecture. Of course, I wasx trying Shakespeare quotes to motivate the (international) students to complement the quotes with "predicted" missing words ;-)
"All the world's a stage, and all the men and women merely...."

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
A comparative analysis for different finite element types in strain-gradient elasticity simulatio...

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Shuchang Wang, Xiaopeng Qiu, Yingxing Xue, Yanfu Li, Wei Yang
https://arxiv.org/abs/2506.14129

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Search-based software engineering (SBSE) addresses critical optimization challenges in software engineering, including the next release problem (NRP) and feature selection problem (FSP). While traditional heuristic approaches and integer linear programming (ILP) methods have demonstrated efficacy for small to medium-scale problems, their scalability to large-scale instances remains unknown. Here, we introduce quantum annealing (QA) as a subroutine to tackling multi-objective SBSE problems, leve…

Engineering topological phase transitions via sliding ferroelectricity in MBi2Te4 (M = Ge, Sn, Pb) bilayers
Xinlong Dong, Dan Qiao, Zeyu Li, Zhenhua Qiao, Xiaohong Xu
https://arxiv.org/abs/2506.09317

Engineering topological phase transitions via sliding ferroelectricity in MBi2Te4 (M = Ge, Sn, Pb) bilayers
Materials combining electrically switchable ferroelectricity and tunable topological states hold significant promise for advancing both foundamental quantum phenomena and innovative device architectures. Here, we employ first-principles calculations to systematically investigate the sliding ferroelectricity-mediated topological transitions in bilayer MBi2Te4 (M = Ge, Sn, Pb). By strategically engineering interlayer sliding configurations with oppositely polarized states, we demonstrate reversib…

Agile and Student-Centred Teaching of Agile/Scrum Concepts
Maria Spichkova
https://arxiv.org/abs/2506.14369 https://arxiv.org/pdf/250…

Agile and Student-Centred Teaching of Agile/Scrum Concepts
In this paper, we discuss our experience in designing and teaching a course on Software Engineering Project Management, where the focus is on Agile/Scrum development and Requirement Engineering activities. The course has undergone fundamental changes since 2020 to make the teaching approach more student-centred and flexible. As many universities abandoned having face-to-face exams at the end of the semester, authentic assessments now play an even more important role than before. This makes asse…

[2025-06-18 Wed (UTC), 4 new articles found for cs.CE Computational Engineering, Finance, and Science]
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Augmenting the Generality and Performance of Large Language Models for Software Engineering
Fabian C. Pe\~na
https://arxiv.org/abs/2506.11548 https://

Augmenting the Generality and Performance of Large Language Models for Software Engineering
Large Language Models (LLMs) are revolutionizing software engineering (SE), with special emphasis on code generation and analysis. However, their applications to broader SE practices including conceptualization, design, and other non-code tasks, remain partially underexplored. This research aims to augment the generality and performance of LLMs for SE by (1) advancing the understanding of how LLMs with different characteristics perform on various non-code tasks, (2) evaluating them as sources o…

Active Digital Twins via Active Inference
Matteo Torzoni, Domenico Maisto, Andrea Manzoni, Francesco Donnarumma, Giovanni Pezzulo, Alberto Corigliano
https://arxiv.org/abs/2506.14453

Active Digital Twins via Active Inference
Digital twins are transforming engineering and applied sciences by enabling real-time monitoring, simulation, and predictive analysis of physical systems and processes. However, conventional digital twins rely primarily on passive data assimilation, which limits their adaptability in uncertain and dynamic environments. This paper introduces the active digital twin paradigm, based on active inference. Active inference is a neuroscience-inspired, Bayesian framework for probabilistic reasoning and…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
SimLOB: Learning Representations of Limited Order Book for Financial Market Simulation

Evaluating Large Language Models on Non-Code Software Engineering Tasks
Fabian C. Pe\~na, Steffen Herbold
https://arxiv.org/abs/2506.10833 https://

Evaluating Large Language Models on Non-Code Software Engineering Tasks
Large Language Models (LLMs) have demonstrated remarkable capabilities in code understanding and generation; however, their effectiveness on non-code Software Engineering (SE) tasks remains underexplored. We present the first comprehensive benchmark, which we name `Software Engineering Language Understanding' (SELU), for evaluating LLMs on 17 non-code tasks, spanning from identifying whether a requirement is functional or non-functional to estimating the effort and complexity of backlog items. …

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Simin Sun, Yuchuan Jin, Miroslaw Staron
https://arxiv.org/abs/2506.11659

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Developing autonomous driving systems (ADSs) involves generating and storing extensive log data from test drives, which is essential for verification, research, and simulation. However, these high-frequency logs, recorded over varying durations, pose challenges for developers attempting to locate specific driving scenarios. This difficulty arises due to the wide range of signals representing various vehicle components and driving conditions, as well as unfamiliarity of some developers' with the…

Model Discovery and Graph Simulation: A Lightweight Alternative to Chaos Engineering
Anatoly A. Krasnovsky, Alexander Zorkin
https://arxiv.org/abs/2506.11176

Model Discovery and Graph Simulation: A Lightweight Alternative to Chaos Engineering
Microservice applications are prone to cascading failures because of dense inter-service dependencies. Ensuring resilience usually demands fault-injection experiments in production-like setups. We propose \textit{model discovery} -- an automated CI/CD step that extracts a live dependency graph from trace data -- and show that this lightweight representation is sufficient for accurate resilience prediction. Using the DeathStarBench Social Network, we build the graph, simulate failures via Monte-…

Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
Shuo Jiang, Min Xie, Frank Youhua Chen, Jian Ma, Jianxi Luo
https://arxiv.org/abs/2506.09755

Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
Research and practice in Intelligent Design (ID) have significantly enhanced engineering innovation, efficiency, quality, and productivity over recent decades, fundamentally reshaping how engineering designers think, behave, and interact with design processes. The recent emergence of Foundation Models (FMs), particularly Large Language Models (LLMs), has demonstrated general knowledge-based reasoning capabilities, and open new paths and avenues for further transformation in engineering design. …

MLDebugging: Towards Benchmarking Code Debugging Across Multi-Library Scenarios
Jinyang Huang, Xiachong Feng, Qiguang Chen, Hanjie Zhao, Zihui Cheng, Jiesong Bai, Jingxuan Zhou, Min Li, Libo Qin
https://arxiv.org/abs/2506.13824

MLDebugging: Towards Benchmarking Code Debugging Across Multi-Library Scenarios
Code debugging is a crucial task in software engineering, which attracts increasing attention. While remarkable success has been made in the era of large language models (LLMs), current research still focuses on the simple no-library or single-library setting, ignoring the complex multi-library scenario in real-world applications. To address this limitation, we make the first attempt to introduce MLDebugging (Multi-Library Debugging), a comprehensive benchmark designed to assess debugging chall…

[2025-06-17 Tue (UTC), 5 new articles found for cs.CE Computational Engineering, Finance, and Science]
toXiv_bot_toot

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
Aaditaa Vashisht (Department of Information Science,Engineering, RV College of Engineering, India), Rekha B S (Department of Information Science,Engineering, RV College of Engineering, India)
https://arxiv.org/abs/25…

Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies
With the rapid pace of digital transformation, the retail industry is increasingly depending on real-time, scalable, and resilient systems to manage financial transactions, analyze customer behavior, and streamline order processing. This literature review explores how modern event-driven and microservices-based architectures, particularly those leveraging Apache Kafka, Spring Boot, MongoDB, and Kubernetes are transforming retail and financial systems. By systematically reviewing academic public…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
Retrieval-augmented code completion for local projects using large language models

How Does LLM Reasoning Work for Code? A Survey and a Call to Action
Ira Ceka, Saurabh Pujar, Irene Manotas, Gail Kaiser, Baishakhi Ray, Shyam Ramji
https://arxiv.org/abs/2506.13932

How Does LLM Reasoning Work for Code? A Survey and a Call to Action
The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. These advancements have extended into the domain of code, facilitating complex tasks such as code generation, translation, summarization, and repair. However, their utility for real-world deployment in-the-wild has only recently been studied, particularly on software engineering (SWE) tasks such as GitHub issue resolution. In this study, we examine the code reasoning techniqu…

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
Ina K. Schieferdecker
https://arxiv.org/abs/2506.14640

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
In industry, software testing is the primary method to verify and validate the functionality, performance, security, usability, and so on, of software-based systems. Test automation has gained increasing attention in industry over the last decade, following decades of intense research into test automation and model-based testing. However, designing, developing, maintaining and evolving test automation is a considerable effort. Meanwhile, AI's breakthroughs in many engineering fields are opening…

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks
E. G. Santana Jr, Gabriel Benjamin, Melissa Araujo, Harrison Santos, David Freitas, Eduardo Almeida, Paulo Anselmo da M. S. Neto, Jiawei Li, Jina Chun, Iftekhar Ahmed
https://arxiv.org/abs/2506.05614

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks
A growing variety of prompt engineering techniques has been proposed for Large Language Models (LLMs), yet systematic evaluation of each technique on individual software engineering (SE) tasks remains underexplored. In this study, we present a systematic evaluation of 14 established prompt techniques across 10 SE tasks using four LLM models. As identified in the prior literature, the selected prompting techniques span six core dimensions (Zero-Shot, Few-Shot, Thought Generation, Ensembling, Sel…

[2025-06-17 Tue (UTC), 22 new articles found for cs.SE Software Engineering]
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Understanding Software Engineering Agents Through the Lens of Traceability: An Empirical Study
Ira Ceka, Saurabh Pujar, Shyam Ramji, Luca Buratti, Gail Kaiser, Baishakhi Ray
https://arxiv.org/abs/2506.08311

Understanding Software Engineering Agents Through the Lens of Traceability: An Empirical Study
With the advent of large language models (LLMs), software engineering agents (SWE agents) have emerged as a powerful paradigm for automating a range of software tasks -- from code generation and repair to test case synthesis. These agents operate autonomously by interpreting user input and responding to environmental feedback. While various agent architectures have demonstrated strong empirical performance, the internal decision-making worfklows that drive their behavior remain poorly understoo…

How Developers Use AI Agents: When They Work, When They Don't, and Why
Aayush Kumar, Yasharth Bajpai, Sumit Gulwani, Gustavo Soares, Emerson Murphy-Hill
https://arxiv.org/abs/2506.12347

How Developers Use AI Agents: When They Work, When They Don't, and Why
Software Engineering Agents (SWE agents) can autonomously perform development tasks on benchmarks like SWE Bench, but still face challenges when tackling complex and ambiguous real-world tasks. Consequently, SWE agents are often designed to allow interactivity with developers, enabling collaborative problem-solving. To understand how developers collaborate with SWE agents and the communication challenges that arise in such interactions, we observed 19 developers using an in-IDE agent to resolve…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs
htt…

MBTModelGenerator: A software tool for reverse engineering of Model-based Testing (MBT) models from clickstream data of web applications
Sasidhar Matta, Vahid Garousi
https://arxiv.org/abs/2506.08179

MBTModelGenerator: A software tool for reverse engineering of Model-based Testing (MBT) models from clickstream data of web applications
Automated testing has become a standard practice in software engineering, yet the creation of test models and suites remains labor-intensive. To reduce this effort, we developed an open-source tool that automatically generates Model-Based Testing (MBT) models from clickstream data collected during user interaction with web applications. The tool captures UI events, transforms them into state-transition models, and exports the result in a format compatible with the GraphWalker MBT tool. This ena…

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution
Yibo Wang, Zhihao Peng, Ying Wang, Zhao Wei, Hai Yu, Zhiliang Zhu
https://arxiv.org/abs/2506.12728

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution
LLMs demonstrate strong performance in auto-mated software engineering, particularly for code generation and issue resolution. While proprietary models like GPT-4o achieve high benchmarks scores on SWE-bench, their API dependence, cost, and privacy concerns limit adoption. Open-source alternatives offer transparency but underperform in complex tasks, especially sub-100B parameter models. Although quality Chain-of-Thought (CoT) data can enhance reasoning, current methods face two critical flaws:…

Towards Lean Research Inception: Assessing Practical Relevance of Formulated Research Problems
Anrafel Fernandes Pereira, Marcos Kalinowski, Maria Teresa Baldassarre, J\"urgen B\"orstler, Nauman bin Ali, Daniel Mendez
https://arxiv.org/abs/2506.12669

Towards Lean Research Inception: Assessing Practical Relevance of Formulated Research Problems
[Context] The lack of practical relevance in many Software Engineering (SE) research contributions is often rooted in oversimplified views of industrial practice, weak industry connections, and poorly defined research problems. Clear criteria for evaluating SE research problems can help align their value, feasibility, and applicability with industrial needs. [Goal] In this paper, we introduce the Lean Research Inception (LRI) framework, designed to support the formulation and assessment of prac…

Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers
Mohammed Mehedi Hasan, Hao Li, Emad Fallahzadeh, Bram Adams, Ahmed E. Hassan
https://arxiv.org/abs/2506.13538

Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers
Although Foundation Models (FMs), such as GPT-4, are increasingly used in domains like finance and software engineering, reliance on textual interfaces limits these models' real-world interaction. To address this, FM providers introduced tool calling-triggering a proliferation of frameworks with distinct tool interfaces. In late 2024, Anthropic introduced the Model Context Protocol (MCP) to standardize this tool ecosystem, which has become the de facto standard with over eight million weekly SD…

This https://arxiv.org/abs/2505.23674 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Quantum-Based Software Engineering
Quantum computing has demonstrated potential for solving computationally intensive problems more efficiently than classical methods. Many software engineering tasks, such as test case selection, static analysis, code clone detection, and defect prediction, involve complex optimization, search, or classification, making them candidates for quantum enhancement. In this paper, we propose Quantum-Based Software Engineering (QBSE), a potential research direction for applying quantum computing to cla…