Suchergebnisse - (( (staten OR state) python code analysis ) OR ( skriftene python code analysis ))*

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

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

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

Measurement and Development for Automated Secure Coding Solutions

Autoren: Frantz, Miles Eugene

Thesis Advisors: Computer Science and#38; Applications, Yao, Danfeng, Rajagopalan, Raj, Meng, Na, Chung, Taejoong Tijay, Brown, Dwayne Christian

Schlagwörter: Large Language Models, Machine Learning, Static Code Analysis, Python, Java, Benchmark

Dateibeschreibung: ETD; application/pdf

Verfügbarkeit: https://hdl.handle.net/10919/121100

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

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

Static Analysis of Corpus of Source Codes of Python Applications.

Autoren: Kapustin, D. A. Shvyrov, V. V. Shulika, T. I.

Quelle: Programming & Computer Software. Aug2023, Vol. 49 Issue 4, p302-309. 8p.

Schlagwörter: *SOURCE code, *PYTHONS, *PYTHON programming language, *CORPORA, *ROBBERS

Numerical Analyses of a SAW Gas Sensor in a Non-Steady State

Autoren: T. Hejczyk J. Wrotniak P. Powroźnik et al.

Quelle: International Journal of Electronics and Telecommunications, Vol vol. 71, Iss No 4 (2025)

Schlagwörter: gas sensors, numerical modeling, ingebrigtsen’s formula, dmmp, (rr)-p3ht, acoustoelectric analysis (naa), Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Telecommunication, TK5101-6720

Dateibeschreibung: electronic resource

Relation: https://journals.pan.pl/Content/136909/6-5168-Hejczyk_sk.pdf; https://doaj.org/toc/2081-8491; https://doaj.org/toc/2300-1933

Zugangs-URL: https://doaj.org/article/c9d170a1144c4d9f86026066ca8dbfea

Python code analysis and figures - intensity zones

Autoren: Fredrik Mentzoni

Schlagwörter: Sports science and exercise not elsewhere classified, sports scienes

Verfügbarkeit: https://doi.org/10.6084/m9.figshare.28562558.v1
https://figshare.com/articles/software/Python_code_analysis_and_figures_-_intensity_zones/28562558

Smart Compiler Assistant: An AST based Python Code Analysis

Autoren: Aneesh, Ch Saumik, Gembali Varun, Kvv et al.

Quelle: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) ; page 1-6

Verfügbarkeit: https://doi.org/10.1109/icccnt61001.2024.10724220
http://xplorestaging.ieee.org/ielx8/10723818/10723316/10724220.pdf?arnumber=10724220

ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.

Autoren: Ruta, Michael R Gaidici, Tony Irwin, Chase et al.

Quelle: Journal of Medical Internet Research. 2025, Vol. 27, p1-9. 9p.

Schlagwörter: *Data analysis, *Data management, ChatGPT, Inferential statistics, Medical care research, Statistical software, Univariate analysis, Descriptive statistics

Firma/Körperschaft: OpenAI Inc.

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

CLAVE: A deep learning model for source code authorship verification with contrastive learning and transformer encoders.

Autoren: Álvarez-Fidalgo, David Ortin, Francisco

Quelle: Information Processing & Management. May2025, Vol. 62 Issue 3, pN.PAG-N.PAG. 1p.

Schlagwörter: *Transformer models, Language models, Source code, Dispute resolution, Python programming language

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

LMs: Understanding Code Syntax and Semantics for Code Analysis

Autoren: Ma, Wei Liu, Shangqing Lin, Zhihao et al.

Index Begriffe: Computer Science - Software Engineering, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2305.12138

MLtool Python Code

Autoren: Nikolai A Zarkevich Nishan Senanayake Joshua Stuckner et al.

Schlagwörter: Computer Programming and Software

Relation: MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Zugangs-URL: https://ntrs.nasa.gov/citations/20230005458

User guide for Social Determinants of Health Survey data in the All of Us Research Program.

Autoren: Koleck, Theresa A Dreisbach, Caitlin Zhang, Chen et al.

Quelle: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3032-3041. 10p.

Schlagwörter: Social determinants of health, Health equity, Research personnel, Sociometry, Source code

A Firm's Operational Risk: Data Set and Empirical Evidence.

Autoren: Astvansh, Vivek Simpson, Joseph J.

Quelle: Manufacturing & Service Operations Management (M&SOM). Jan/Feb2026, Vol. 28 Issue 1, p326-341. 16p.

Schlagwörter: *OPERATIONAL risk, *TRANSFORMER models, *STAKEHOLDER theory, *LEGAL liability, *FINANCIAL disclosure, *EMPIRICAL research, NUMERICAL analysis

Geografische Kategorien: UNITED States

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

Utilizing Deep Learning and Object-Based Image Analysis to Search for Low-Head Dams in Indiana, USA.

Autoren: Crookston, Brian M. Arnold, Caitlin R.

Quelle: Water (20734441); Mar2025, Vol. 17 Issue 6, p876, 24p

Schlagwörter: IMAGE analysis, WATER supply, DAMS, MODEL validation, LEARNING ability