22 papers · ranked by Valyu relevance
Jia Li, Zhi Jin, Huangzhao Zhang, Kechi Zhang + 2 more
Software development automation is a long-term goal in software engineering. With the development of artificial intelligence (AI), more and more researchers are exploring approaches to software automation. They view AI systems as tools or assistants in software development, still requiring significant human…
Johannes Wachs, Xiangnan Feng, Simone Daniotti, Frank Neffke
With the rise of new industries, often new jobs emerge. Evolutionary Economic Geography and in particular Industry Life Cycle perspectives predict that these activities first emerge in a limited number of cities to then diffuse to other locations as job descriptions become more standardized. Here, we focus on a…
Lorena Soto Zenteno, Carlos Cayahuallpa, Alex Pacheco
* Background Grade management in Peruvian educational institutions faces significant challenges due to the widespread use of Excel spreadsheets, which often lead to delays, errors, and fragmented information during registration, consultation, and report card preparation processes. National studies indicate that…
Strassler, Daniel, Elkin, Gabe + 14 more
— Software plays an ever-increasing role in complex system development and prototyping, and in recent years, MIT Lincoln Laboratory has sought to improve both the effectiveness and culture surrounding software engineering in execution of its mission. The Homeland Protection and Air Traffic Control Division conducted an…
Feisal Alaswad, Eswaran Poovammal, Batoul Aljaddouh
Software effort estimation has traditionally been grounded in the assumption that development cost is primarily driven by human labor, approximated through proxies such as code size, functional complexity, or perceived task difficulty. The increasing adoption of large language models (LLMs) as software development…
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…
Miklós Koren, Gábor Békés, Julian Hinz, Aaron Lohmann
Generative AI is changing how software is produced and used. In vibe coding, an AI agent builds software by selecting and assembling open-source software (OSS), often without users directly reading documentation, reporting bugs, or otherwise engaging with maintainers. We study the equilibrium effects of vibe coding on…
Mingyu Chen, Yakun Zhang, Zihao Xie, Yixing Luo + 4 more
In modern software development, the rapid advancement of Large Language Models (LLMs) has made the end-to-end transformation of Natural Language Requirements (NLRs) into executable repository-level code increasingly feasible. However, existing approaches typically rely on simplified instructions (e.g., single-sentence…
Stephanie A. Besser, Eric A. Jensen, Daniel S. Katz
Title: Structured Abstract Background Generative artificial intelligence is spreading rapidly across academic research, yet its role in the development and maintenance of research software remains insufficiently characterized. Methods A six week, institutional review board approved, anonymized online survey of faculty…
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…
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…
Denesa Zyberaj, Pascal Hirmer, Marco Aiello, Stefan Wagner
The automotive domain is shifting to software-centric development to meet regulation, market pressure, and feature velocity. This shift increases embedded systems' complexity and strains testing capacity. Despite relevant standards, a coherent system-testing methodology that spans heterogeneous, legacy-constrained…
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…
Authors not listed
Here, we present MolPic, an open-source Python-based software that can be used to generate high-resolution, publication-quality molecular figures directly from compound names or SMILES strings. MolPic supports single-molecule rendering, batch processing, and automated multi-panel 2D figure generation, which are…
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…
Vikas Mishra, Rajkumar Verma, Paruvathanahalli Siddalingam Rajinikanth, Ravinder K. Kaundal
Quantitative analysis of rodent behaviour is fundamental to neuroscience, preclinical drug discovery and neurotoxicology research. Although several commercial and open-source software packages are available for behavioural assessment, some are expensive, some require programming expertise, and some provide limited…
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…
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…
Zhimeng Zhou, Yang Nan, Minjie Mou, Yuntao Qian + 16 more
Artificial intelligence (AI) is increasingly permeating the drug development pipeline. Numerous algorithms for accelerating this multi-stage and multi-task process have been constructed, which depends heavily on expert design and labor-intensive task-specific optimization. Given that AI-driven acceleration of drug…
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.…
Harsh Vijaykumar Patel, Gail P. Jarvik, Taryn Hall, David Veenstra + 2 more
The lack of user-centered design principles in the current landscape of commonly-used bioinformatics software tools poses challenges for novice genomics researchers (NGRs) entering the genomics ecosystem. Comparing the usability of one analysis software to that of another is a non-trivial task and requires evaluation…
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…