Suchergebnisse - (stavebna OR state) python code analysis*

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

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

AI-Driven Analysis of Drug Marketing Efficiency: Unveiling FDA Approval to Market Release Dynamics.

Autoren: Takefuji Y; Faculty of Data Science, Musashino University, 3-3-3 Ariake Koto-Ku, Tokyo, 135-8181, Japan. takefuji@keio.jp.

Quelle: The AAPS journal [AAPS J] 2025 Feb 20; Vol. 27 (2), pp. 48. Date of Electronic Publication: 2025 Feb 20.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: American Association of Pharmaceutical Scientists Country of Publication: United States NLM ID: 101223209 Publication Model: Electronic Cited Medium: Internet ISSN: 1550-7416 (Electronic) Linking ISSN: 15507416 NLM ISO Abbreviation: AAPS J Subsets: MEDLINE

MeSH-Schlagworte: United States Food and Drug Administration* , Drug Approval* , Drug Industry*/methods , Drug Industry*/legislation & jurisprudence , Marketing*/methods , Artificial Intelligence*, United States ; Humans ; Time Factors

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

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

Schlagwörter: FOS: Computer and information sciences, Computer Science - Programming Languages, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Programming Languages (cs.PL)

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

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

State-Space Kinetic Ising Model Code and Data for Neuronal Spiking Analysis

Autoren: ISHIHARA, KEN

Schlagwörter: State-Space Kinetic Ising Model, Neuronal Spiking, Nonequilibrium, Spike Train Analysis, Computational Neuroscience

Relation: https://zenodo.org/records/15205014; oai:zenodo.org:15205014; https://doi.org/10.5281/zenodo.15205014

Verfügbarkeit: https://doi.org/10.5281/zenodo.15205014
https://zenodo.org/records/15205014

A Study of Large Language Models in Detecting Python Code Violations.

Autoren: Mohammed Salih, Hekar A. Sarhan, Qusay I.

Quelle: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 2, p215-225, 11p

Schlagwörter: LANGUAGE models, QUALITY assurance, COMPUTER software quality control, NATURAL language processing

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

Autoren: Xincheng He Xiaojin Liu Lei Xu

Quelle: International Journal of Software Engineering and Knowledge Engineering. 33:1567-1597

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Verbatim Data Transcription Failures in LLM Code Generation: A State-Tracking Stress Test

Autoren: Haque, Mohd Ariful Gupta, Kishor Datta Rahman, Mohammad Ashiqur et al.

Schlagwörter: Software Engineering, Cryptography and Security

Relation: http://arxiv.org/abs/2601.03640

Verfügbarkeit: http://arxiv.org/abs/2601.03640

A Practical Guide to Static and Dynamic Econometric Modelling ; Examples and Analysis with Python Code Embedded

Autoren: Maitra, Sarit

Quelle: Contributions to Economics ; ISSN 1431-1933 2197-7178 ; ISBN 9783031868610 9783031868627

Verfügbarkeit: https://doi.org/10.1007/978-3-031-86862-7
https://link.springer.com/content/pdf/10.1007/978-3-031-86862-7.pdf
https://link.springer.com/content/pdf/10.1007/978-3-031-86862-7

Evolutionary Insights from Sequence Analysis of Interleukin 17A (IL17A).

Autoren: Santos JC; Department of Biological Sciences, College of Liberal Arts and Sciences, St. John's University, Jamaica, Queens, NY, USA. santosj@stjohns.edu.

Quelle: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2026; Vol. 2983, pp. 397-447.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE

MeSH-Schlagworte: Evolution, Molecular* , Interleukin-17*/genetics , Sequence Analysis, DNA*/methods , Computational Biology*/methods, Phylogeny ; Humans ; Software ; Sequence Alignment

What does this Python code do? An exploratory analysis of novice students’ code explanations

Autoren: van der Werf, Vivian Aivaloglou, Efthimia Hermans, Felienne et al.

Quelle: The 10th Computer Science Education Research Conference ; page 94-107

Verfügbarkeit: https://doi.org/10.1145/3507923.3507956
https://dl.acm.org/doi/10.1145/3507923.3507956
https://dl.acm.org/doi/pdf/10.1145/3507923.3507956

Identification of Novel Microcystins Using High-Resolution MS and MS ⁿ with Python Code.

Autoren: Baliu-Rodriguez D Peraino NJ Premathilaka SH et al.

Quelle: Environmental science & technology [Environ Sci Technol] 2022 Feb 01; Vol. 56 (3), pp. 1652-1663. Date of Electronic Publication: 2022 Jan 12.

Publikationsart: Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.

Info zur Zeitschrift: Publisher: American Chemical Society Country of Publication: United States NLM ID: 0213155 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1520-5851 (Electronic) Linking ISSN: 0013936X NLM ISO Abbreviation: Environ Sci Technol Subsets: MEDLINE

MeSH-Schlagworte: Microcystins*/analysis , Tandem Mass Spectrometry*, Chromatography, Liquid ; Fresh Water ; Harmful Algal Bloom

DefAP: A Python code for the analysis of point defects in crystalline solids

Autoren: Neilson, William D. Murphy, Samuel T. Engineering and Physical Sciences Research Council

Weitere Verfasser: Neilson, William D. Murphy, Samuel T. Engineering and Physical Sciences Research Council

Quelle: Computational Materials Science ; volume 210, page 111434 ; ISSN 0927-0256

Verfügbarkeit: http://dx.doi.org/10.1016/j.commatsci.2022.111434
https://api.elsevier.com/content/article/PII:S0927025622002002?httpAccept=text/xml
https://api.elsevier.com/content/article/PII:S0927025622002002?httpAccept=text/plain

Comparative Analysis of AI Models for Python Code Generation: A HumanEval Benchmark Study.

Autoren: Bayram, Ali Menekse Dalveren, Gonca Gokce Derawi, Mohammad

Quelle: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 18, p9907, 17p

Schlagwörter: ARTIFICIAL intelligence, PYTHON programming language, COMPARATIVE studies, EVALUATION methodology, BENCHMARK problems (Computer science), GENERATIVE pre-trained transformers, MACHINE learning, COMPUTER software development

Mathematically Rigorous Proof of Toponium Existence in the TEBAC 9D$^+$ Framework

Autoren: Karadzhov, Tosho Lazarov orcid:0009-0008-1699-

Schlagwörter: toponium, heavy quarkonium, QCD, TEBAC 9D+, LHC, spectral analysis, Python code, threshold resonance

Relation: https://zenodo.org/records/16762156; oai:zenodo.org:16762156; https://doi.org/10.5281/zenodo.16762156

Verfügbarkeit: https://doi.org/10.5281/zenodo.16762156
https://zenodo.org/records/16762156

Concrete examples of the rate of convergence of Chernoff approximations: numerical results for the heat semigroup and open questions on them (with appendix: full list of pictures and Python code)

Autoren: Katalova, K. A. Nikbakht, N. Remizov, I. D.

Schlagwörter: Numerical Analysis, Functional Analysis, 65M12 (primary) 47D06, 35K05, 35E15, 35C99 (secondary)

Relation: http://arxiv.org/abs/2301.05284

Verfügbarkeit: http://arxiv.org/abs/2301.05284

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

Benchmarking Large Language Models for Bio-Image Analysis Code Generation

Autoren: Robert Haase Christian Tischer Jean-Karim Hériché et al.

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