Suchergebnisse - (( (statene OR state) python code analysis ) OR ( (statenet OR stateene) python code analysis ))

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autoren: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

Quelle: Future Internet. Sep2025, Vol. 17 Issue 9, p412. 28p.

Schlagwörter: *Experimental design, *Quantitative research, Language models, Python programming language, Generative pre-trained transformers, Benchmark problems (Computer science), Code generators

Numerical analysis of recovery stage with disappearing polymer layer RR-P3HT for the detection of DMMP based on diffusion equations.

Autoren: Hejczyk, Tomasz Wrotniak, Jarosław Powroźnik, Paulina et al.

Quelle: International Journal of Electronics & Telecommunications. 2025, Vol. 71 Issue 4, p1-7. 7p.

Schlagwörter: *NUMERICAL analysis, *SURFACE acoustic wave sensors, *ELECTRIC conductivity, *REACTION-diffusion equations, *GAS detectors, *POLYMERIC membranes, *SURFACE interactions

Quantifying cross-language code reuse via function-level clone detection

Autoren: Yi Rong Yan Zhou

Quelle: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 10, Pp 1-20 (2025)

Schlagwörter: Natural language processing, Code reuse detection, Function-level clone analysis, Java and python source code, Academic plagiarism detection, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Zugangs-URL: https://doaj.org/article/0e8d85656442482785bc981b326c25a4

Python API Misuse Mining and Classification Based on Hybrid Analysis and Attention Mechanism.

Autoren: He, Xincheng Liu, Xiaojin Xu, Lei

Quelle: International Journal of Software Engineering & Knowledge Engineering. Oct2023, Vol. 33 Issue 10, p1567-1597. 31p.

Schlagwörter: *COMPUTER software development, *APPLICATION program interfaces, PYTHONS, PYTHON programming language, CLASSIFICATION

A Study of Large Language Models in Detecting Python Code Violations

Autoren: Hekar A. Mohammed Salih Qusay I. Sarhan

Quelle: ARO-The Scientific Journal of Koya University, Vol 13, Iss 2 (2025)

Schlagwörter: Large language models, Software metrics, Software quality, Static code analysis, Technology, Science

Dateibeschreibung: electronic resource

Relation: https://aro.koyauniversity.org/index.php/aro/article/view/2395; https://doaj.org/toc/2410-9355; https://doaj.org/toc/2307-549X

Zugangs-URL: https://doaj.org/article/a66cf05353b54e19a03b46c0b089d1fc

Analysis of accretion disc structure and stability using open code for vertical structure.

Autoren: Tavleev, A S Lipunova, G V Malanchev, K L

Quelle: Monthly Notices of the Royal Astronomical Society. Sep2023, Vol. 524 Issue 3, p3647-3661. 15p.

Schlagwörter: *ACCRETION disks, *RADIATION, *COMPACT discs, *ACCRETION (Astrophysics), *SUPERMASSIVE black holes, *EQUATIONS of state, *STELLAR photospheres

Programming models to support data science workflows

Autoren: Ramón-Cortés Vilarrodona, Cristián

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Badia Sala, Rosa M. (Rosa Maria), Ejarque Artigas, Jorge

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Distributed computing, High-performance computing, Data science pipelines, Task-ba workflows, Dataflows, Containers (Computer sicience), COMPSs, PyCOMPSs, AutoParallel, Docker, Àrees temàtiques de la UPC::Informàtica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/669728
https://dx.doi.org/10.5821/dissertation-2117-330142

Modelling the positive and negative interaction between mood and thermal sensation in the built environment using a combined Markov Chain Monte Carlo algorithm and Morris method.

Autoren: Özbey, Mehmet Furkan Turhan, Cihan

Quelle: Building Services Engineering Research & Technology. Nov2025, Vol. 46 Issue 6, p737-752. 16p.

Schlagwörter: *MARKOV chain Monte Carlo, MOOD (Psychology), THERMAL comfort, SENSITIVITY analysis, PSYCHOLOGICAL factors, ENVIRONMENTAL psychology

Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning

Autoren: Zhao, Wenting Abdelaziz, Ibrahim Dolby, Julian et al.

Index Begriffe: Computer Science - Programming Languages, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2301.05108

Analysis of accretion disc structure and stability using open code for vertical structure

Autoren: Tavleev, A. S. Lipunova, G. V. Malanchev, K. L.

Index Begriffe: Astrophysics - High Energy Astrophysical Phenomena, text

URL: http://arxiv.org/abs/2303.02184

MoveApps: a serverless no-code analysis platform for animal tracking data.

Autoren: Kölzsch, Andrea Davidson, Sarah C. Gauggel, Dominik et al.

Quelle: Movement Ecology. 7/18/2022, Vol. 10 Issue 1, p1-12. 12p.

Analyzing LLM-Generated Code According to Four ISO/IEC 5055:2021 Categories

Autoren: Rasmus Krebs Somnath Mazumdar

Quelle: IEEE Access, Vol 13, Pp 202482-202499 (2025)

Schlagwörter: Analysis, ISO, LLMs, maintainability, performance, Python, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11269792/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/3faae1da4e0b47beb1e1ac9da1ee6b78

Fast robust methods for singular state-space models.

Autoren: Jonker, Jonathan Aravkin, Aleksandr Burke, James V. et al.

Quelle: Automatica. Jul2019, Vol. 105, p399-405. 7p.

Schlagwörter: *STATE-space methods, *TIME series analysis, *KALMAN filtering, *CONSTRAINED optimization, *SOURCE code

DeVAIC: A tool for security assessment of AI-generated code.

Autoren: Cotroneo, Domenico De Luca, Roberta Liguori, Pietro

Quelle: Information & Software Technology. Jan2025, Vol. 177, pN.PAG-N.PAG. 1p.

Schlagwörter: *COMPUTER software development, *ARTIFICIAL intelligence, *SECURITY management, CODE generators, SOURCE code

Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data.

Autoren: Tulpan, Dan¹

Quelle: Journal of Animal Science. 2024 Supplement, Vol. 102, p68-68. 1/4p.

Schlagworte: Machine learning, Personal computers, Animal science, Data modeling, Python programming language

The state of the late Quaternary megafauna extinction debate: a systematic review and analysis.

Autoren: Stewart, Mathew Peters, Carli Ziegler, Michael J. et al.

Quelle: Frontiers in Mammal Science. 2025, p1-27. 27p.

TESTING THE DYNAMIC EXECUTION OF PYTHON PROGRAM CODE DURING THE CERTIFICATION TESTING (DEVELOPMENT) STAGE IN THE CERTIFICATION SYSTEM OF THE MINISTRY OF DEFENSE OF RUSSIA

Autoren: V.V. Samarov

Quelle: Надежность и качество сложных систем, Iss 2 (2023)

Schlagwörter: certification tests of software products, dynamic code analysis of python programs, control of completeness and lack of redundancy at the level of files and functional objects, code profiling for dynamic analysis, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2307-4205

Zugangs-URL: https://doaj.org/article/17c480a498a44ff5b1681dc8eb177136

Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.

Autoren: Jobarteh, Bubacarr Mincu-Iorga, Madalina Gavojdian, Dinu et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Application of Artificial Intelligence Technologies in Livestock Management.

Alternate Title: Hayvancılıkta Yapay Zekâ Teknolojilerinin Uygulanması.

Autoren: DİLAVER, Hatice DİLAVER, Kamil Fatih

Quelle: Journal of Animal Science & Economics. Jul2025, Vol. 4 Issue 2, p64-74. 11p.

Schlagworte: Natural language processing, Artificial neural networks, Supervised learning, Artificial intelligence, Agriculture

Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records.

Autoren: Kong, Chun Yin Vasquez, Picasso Farhoodimoghadam, Makan et al.

Quelle: BMC Veterinary Research. 10/2/2025, Vol. 21 Issue 1, p1-12. 12p.

Schlagworte: Machine learning, Electronic health records, Open source software, Patient care, Veterinary medicine, Diagnosis, Classification algorithms, Synchronization