Suchergebnisse - ((static OR statu) OR state) python code analysis*

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

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

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

Autoren: Sarit Maitra

Quelle: Contributions to Economics ISBN: 9783031868610

Tailoring Static Code Analysis for Top 25 CWE in Python

Autoren: Ali Shihab Mafaz Alanezi

Quelle: Al-Noor Journal for Information Technology and Cybersecurity. 1

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

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: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS

Autoren: Bayu Samodra Vebby Amelya Nora Fitra Arifiansyah et al.

Quelle: JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer). 10:690-697

Yusuf Suresinin Anlam İlişkileri ve Hikâye Birleşenlerinin Pyhton Kodlu Matematiksel Görselleştirmelerle Tahlili. (Turkish)

Alternate Title: Analysis of the Meaning Relations and Story Components of Surah Yusuf Via Python Coded Mathematical Visualizations. (English)

Autoren: Yücel, Doğan Er, Ülkü Aysel, Metin et al.

Quelle: International Journal of Social Sciences (IJSS) / Uluslararası Sosyal Bilimler Dergisi; 2025, Vol. 9 Issue 41, p1-42, 42p

Schlagwörter: TIME series analysis, THEMATIC maps, GRAPH theory, PYTHON programming language, QUR'ANIC criticism

Security Analysis of Python Code Using Bandit: A Streamlit-Based Git Repository Scanner

Autoren: Deeksha D R Prajna M R SAVITHA C K et al.

Quelle: International Journal of Computer Science and Mobile Computing. 14:12-14

Generative AI for Geospatial Analysis: Fine-Tuning ChatGPT to Convert Natural Language into Python-Based Geospatial Computations.

Autoren: Sherman, Zachary Sharma Dulal, Sandesh Cho, Jin-Hee et al.

Quelle: ISPRS International Journal of Geo-Information; Aug2025, Vol. 14 Issue 8, p314, 21p

Schlagwörter: GEOSPATIAL data, LANGUAGE models, PYTHON programming language, GENERATIVE artificial intelligence, GEODATABASES, CHATGPT, SMART cities

Firma/Körperschaft: OPENAI Inc.

Effect of Deep Recurrent Architectures on Code Vulnerability Detection: Performance Evaluation for SQL Injection in Python.

Autoren: Slotkienė, Asta Poška, Adomas Stefanovič, Pavel et al.

Quelle: Electronics (2079-9292); Sep2025, Vol. 14 Issue 17, p3436, 19p

Schlagwörter: DEEP learning, COMPUTER software security, PYTHON programming language

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

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

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

GPU-accelerated on-the-fly nonadiabatic semiclassical dynamics.

Autoren: Myers, Christopher A. Miyazaki, Ken Trepl, Thomas et al.

Quelle: Journal of Chemical Physics; 8/28/2024, Vol. 161 Issue 8, p1-11, 11p

Schlagwörter: ELECTRONIC structure, CONDENSED matter, EXCITED states, ACETONITRILE, PYTHON programming language

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

RepoGraph: A Novel Semantic Code Exploration Tool for Python Repositories Based on Knowledge Graphs and Deep Learning

Autoren: Williams, Christopher Filgueira, Rosa Papadopoulos, George Angelos et al.

Weitere Verfasser: Williams, Christopher Filgueira, Rosa Papadopoulos, George Angelos et al.

Quelle: 2023 IEEE 19th International Conference on e-Science (e-Science). :1-10

Schlagwörter: Knowledge graph, MCC, QA75, QA75 Electronic computers. Computer science, Function summarization, Code understanding, Static code analysis, 3rd-DAS, Transfer learning, QA76, QA76 Computer software, Code exploration, Deep learning models, Semantic code search

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/10023/28672

PyAnalyzer: An Effective and Practical Approach for Dependency Extraction from Python Code.

Autoren: Jin, Wuxia Xu, Shuo Chen, Dawei et al.

Quelle: ICSE: International Conference on Software Engineering; 2024, p1-12, 12p

Schlagwörter: PYTHON programming language, DYLAN (Computer program language), RECALL (Information retrieval), PRECISION (Information retrieval), SOFTWARE engineering

Static Analysis for AWS Best Practices in Python Code

Autoren: Mukherjee, Rajdeep Tripp, Omer Liblit, Ben et al.

Weitere Verfasser: Mukherjee, Rajdeep Tripp, Omer Liblit, Ben et al.

Schlagwörter: FOS: Computer and information sciences, Best practices, Computer Science - Logic in Computer Science, Computer Science - Programming Languages, Formal Languages and Automata Theory (cs.FL), Boto3, Computer Science - Formal Languages and Automata Theory, 02 engineering and technology, Static analysis, Logic in Computer Science (cs.LO), AWS, 0202 electrical engineering, electronic engineering, information engineering, Type inference, ddc:004, Cloud, Python, Programming Languages (cs.PL)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2205.04432
https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2022.14

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