Suchergebnisse - ((static OR statnic) OR stati) python code analysis

Evaluating Python Static Code Analysis Tools Using FAIR Principles

Autoren: Hassan Bapeer Hassan Qusay Idrees Sarhan Arpad Beszedes

Quelle: IEEE Access, Vol 12, Pp 173647-173659 (2024)

Schlagwörter: FAIR principles, IoT, python, software quality, static code analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/10758651/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/e2009f2e1b79423fb89e96c292f8c36a

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

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

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

A Static Analysis Approach for Detecting Array Shape Errors in Python.

Autoren: YUNG YU ZHUANG CHIEN-WEN KAO WEI-HSIN YEN

Quelle: Journal of Information Science & Engineering. Jan2025, Vol. 41 Issue 1, p97-119. 23p.

Schlagwörter: Computational linguistics, Human error, Machine learning, Labor costs, Pythons, Python programming language, Deep learning

Exploring the relation between source code commit information and SonarQube issues.

Autoren: Berciu, Liviu-Marian Motogna, Simona Picus, Oskar et al.

Quelle: Procedia Computer Science. 2025, Vol. 270, p841-850. 10p.

Schlagwörter: Computer software quality control, Best practices, Source code, Python programming language, Software refactoring

Security Evaluation of AI-Generated Code: A Comparative Study of ChatGPT, Copilot, And Gemini through Static and Dynamic Analysis.

Autoren: Ceran, Onur

Quelle: Gazi Journal of Engineering Sciences (GJES) / Gazi Mühendislik Bilimleri Dergisi; Aug2025, Vol. 11 Issue 2, p304-320, 17p

Schlagwörter: GENERATIVE artificial intelligence, COMPUTER software security, CHATGPT, COMPUTER software development, WEB-based user interfaces

A Systematic Survey on Large Language Models for Static Code Analysis.

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

Quelle: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 1, p251-265, 15p

Schlagwörter: LANGUAGE models, ARTIFICIAL intelligence, SOFTWARE measurement, COMPUTER software quality control, EVIDENCE gaps

DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS

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

Quelle: JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer); Vol. 10 No. 3 (2025): JITK Issue February 2025; 690-697 ; 2527-4864 ; 2685-8223 ; 10.33480/jitk.v10i3

Schlagwörter: abstract syntax tree, control flow graph, graphviz, python, SDLC

Dateibeschreibung: application/pdf

Relation: https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177/1353; https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177

Verfügbarkeit: https://ejournal.nusamandiri.ac.id/index.php/jitk/article/view/6177

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

Towards Vulnerability Injection using Artificial Intelligence

Rumo à injeção de vulnerabilidades em Python com Inteligência Artificial

Autoren: Bogaerts, Frédéric Christophe Gabriel

Schlagwörter: Injeção de Vulnerabilidades, Redes Neurais Recorrentes, Inteligência Artificial, Deep Learning, Análise Estática de Código Python, Vulnerability Injection, Recurrent Neural Networks, Artificial Intelligence, Static Python Code Analysis

Verfügbarkeit: https://hdl.handle.net/10316/103014

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 for AWS Best Practices in Python Code

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

Index Begriffe: Python, Type inference, AWS, Cloud, Boto3, Best practices, Static analysis, InProceedings, Text, doc-type:ResearchArticle, publishedVersion

URL: https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2022.14
Is Part Of LIPIcs, Volume 222, 36th European Conference on Object-Oriented Programming (ECOOP 2022)

Static Analysis for AWS Best Practices in Python Code

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

Index Begriffe: Computer Science - Programming Languages, Computer Science - Formal Languages and Automata Theory, Computer Science - Logic in Computer Science, text

URL: http://arxiv.org/abs/2205.04432

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

User-Centric Study and Enhancement of Python Static Code Analysers

Autoren: Chen, Steven Söderberg, Emma McCabe, Alan et al.

Weitere Verfasser: Chen, Steven Söderberg, Emma McCabe, Alan et al.

Quelle: Proceedings of the 34th Annual Workshop of the Psychology of Programming Interest Group PPIG: 34th Annual Meeting of the Psychology of Programming Interest Group.

Schlagwörter: Natural Sciences, Computer and Information Sciences, Software Engineering, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Programvaruteknik

Zugangs-URL: https://www.ppig.org/files/2023-PPIG-34th-chen.pdf

Security Flaws In Generative AI Code : Evaluating Prompt Strategies and Model Parameters in Python

Autoren: Trieu Hung Tran, Elvis Diep, Erik

Index Begriffe: LLM, Temperature, Top-P, Security, Prompt Engineering, Computer and Information Sciences, Data- och informationsvetenskap, Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-367688
TRITA-EECS-EX ; 2025:347

Automated Refactoring of Non-Idiomatic Python Code: A Differentiated Replication with LLMs

Autoren: Midolo, Alessandro Di Penta, Massimiliano

Index Begriffe: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2501.17024

Leveraging Static Analysis for Feedback-Driven Security Patching in LLM-Generated Code.

Autoren: Alrashedy, Kamel Aljasser, Abdullah Tambwekar, Pradyumna et al.

Quelle: Journal of Cybersecurity & Privacy; Dec2025, Vol. 5 Issue 4, p110, 29p

Schlagwörter: COMPUTER security vulnerabilities, LANGUAGE models, PROGRAM transformation, BENCHMARK problems (Computer science), SOFTWARE maintenance, SOURCE code

Analysing the Analysers: An Investigation of Source Code Analysis Tools.

Autoren: Bhutani, Vikram Toosi, Farshad Ghassemi Buckley, Jim

Quelle: Applied Computer Systems; Jun2024, Vol. 29 Issue 1, p98-111, 14p

Schlagwörter: ARTIFICIAL intelligence, COMPUTER software quality control, PROGRAMMING languages, SOURCE code, SYSTEMS software