22 papers · ranked by Valyu relevance
Tanja E. J. Vos, Tijs van der Storm, Alexander Serebrenik, Lionel C. Briand + 3 more
Software engineering is the invisible infrastructure of the digital age. Every breakthrough in artificial intelligence, quantum computing, photonics, and cybersecurity relies on advances in software engineering, yet the field is too often treated as a supportive digital component rather than as a strategic, enabling…
Rashina Hoda
Agentic AI is poised to usher in a seismic paradigm shift in Software Engineering (SE). As technologists rush head-along to make agentic AI a reality, SE researchers are driven to establish agentic SE as a research area. While early visions of agentic SE are primarily focused on code-related activities, early empirical…
Lanza Michele
In June 2024 I co-organized the FUSE (FUture of Software Engineering) symposium in Okinawa, Japan. Me, Andrian Marcus, Takashi Kobayashi and Shinpei Hayashi were general chairs, Nicole Novielli, Kevin Moran, Yutaro Kashiwa and Masanari Kondo were program chairs, some members of my group (Carmen Armenti, Stefano…
Mamdouh Alenezi
The rapid proliferation of large language models (LLMs) and agentic AI systems has created an unprecedented abundance of automatically generated code, challenging the traditional software engineering paradigm centered on manual authorship. This paper examines whether the discipline should be reoriented around…
Bertrand Meyer
Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ("prompt engineering" is a form of requirements engineering, one of the toughest disciplines of software engineering); and the hallucination phenomenon. Programs are only useful if…
Abdullah Almogahed, Hairulnizam Mahdin, Said Badreddine, Mazni Omar + 6 more
Software refactoring is pivotal in improving software quality and ensuring complex software systems’ long-term viability and sustainability. However, developers still face challenges in understanding how refactoring approaches influence software quality, as existing classifications largely overlook sustainability…
Sungmin Kang, Baishakhi Ray, Abhik Roychoudhury
As coding agents are rapidly changing software engineering, a natural question is: what are the core skills needed by future software engineers? To identify where software engineering is headed and thus what skills will be needed, we summarize the results of two round-tables with researchers and industrial…
Ihsan Tolga Medeni, Metehan Ünal, Roberto Galizi, Bryan Bartley + 4 more
Large language models have transformed software engineering practices. However, generated artefacts are not always developer-friendly and may partially meet complex requirements. As the need to standardise, integrate, and develop tools in engineering biology increases, novel approaches are needed to create and maintain…
Anže Mihelič, Tomaž Hovelja, Simon Vrhovec
Secure software engineering (SSE) is inevitably linked to DevSecOps which aims to embed security at every phase of the software development life cycle. The adoption of SSE practices is however poorly understood, especially in various adoption phases. This study aims to address this gap by exploring what motivates…
Douglas Moseley, Yang Kyun Park, Dongxu Wang
3.1### Dr. Moseley, for the proposition Radiation Oncology is an incredible specialty that administers one “drug” to cure cancer: radiation. Where, when and how much is the challenging part. As the first step, we digitize our patients into pixels. These pixels are sorted into piles with segmentation. Pixels are…
Wioleta Kijewska, Heather S. Packer, Simon Hettrick
The Research Software Engineering (RSE) Survey dataset contains longitudinal survey data collected by the Software Sustainability Institute between 2016 and 2022. The survey was initially conducted in the United Kingdom and expanded in subsequent years to include multiple countries. From 2018 onward, a single…
Arjumand Fatima, Onaiza Maqbool
Developer discussions particularly on programming related questions answering (Q&A) sites, contain useful information, which, if mined and analysed carefully can be transformed into insightful recommendations for developers about which software to use or prefer over others, matching with one’s requirements for…
Carolin Schwitalla, Luis Kuhn Cuellar, Matthias Hörtenhuber, Niklas Grote + 8 more
Research software is essential for modern data analysis but is often developed and maintained by a small number of researchers. When developers leave, software may become orphaned, limiting reuse and risking the loss of valuable domain knowledge and computational methods. While the FAIR Principles for Research Software…
Hashim Ali, Raja Sarath Kumar Boddu, Umer Tanveer, Aamir Saeed + 4 more
Software requirements classification remains one of the important challenges in requirements engineering. Engineering that affects the smoothness of project success about software development life cycles. in this paper, a novel hybrid solution is being presented that beats the benchmarks set by previous approaches…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Xiaopeng Xu, Chenjie Feng, Chao Zha, Wenjia He + 3 more
Computational protein design is often constrained by slow, complex, inaccessible, and highly sophiscated and expert-dependent workflows that hinder its transferrability and generalization power for broader applications. We present ProteinMCP, an agentic AI framework designed to accelerate and democratize protein…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Fabio Herrera-Rocha, David Medina-Ortiz, Fabian Mauz, Juergen Pleiss + 1 more
for Machine Learning-Assisted Protein Engineering Authors: Fabio Herrera-Rocha, David Medina-Ortiz, Fabian Mauz, Juergen Pleiss, Mehdi D. Davari Data-driven modeling based on machine learning (ML) is becoming a central component of protein engineering workflows. This perspective presents the elements necessary to…
Authors not listed
Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
Fang Chen, Gede Rasben Dantes, Kadek Rihendra Dantes, Dessy Seri Wahyuni
Engineering thinking has become a central goal of undergraduate engineering education, yet the psychological pathways through which it emerges in design-oriented course contexts are not well understood. This study examined how self-efficacy is associated with engineering thinking among engineering undergraduates in…