Search Results - Python code analysis

DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS

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

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

Smart Compiler Assistant: An AST based Python Code Analysis

Authors: Ch Aneesh Gembali Saumik Kvv Varun et al.

Source: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). :1-6

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

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

Index Terms: 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.

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

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

Subject Terms: *SOURCE code, *PYTHONS, *PYTHON programming language, *CORPORA, *ROBBERS

DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS

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

Source: 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

Subject Terms: abstract syntax tree, control flow graph, graphviz, python, SDLC

File Description: 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

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

Static Analysis for AWS Best Practices in Python Code

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

Index Terms: 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)

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

Authors: Neilson, W.D. Murphy, S.T.

Index Terms: Journal Article, PeerReviewed

URL: https://doi.org/10.1016/j.commatsci.2022.111434
https://eprints.lancs.ac.uk/id/eprint/170551/
https://eprints.lancs.ac.uk/id/eprint/170551
https://doi.org/10.1016/j.commatsci.2022.111434

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

Authors: Neilson, W.D. Murphy, S.T.

Index Terms: Journal Article, PeerReviewed

URL: https://eprints.lancs.ac.uk/id/eprint/170551/
https://eprints.lancs.ac.uk/id/eprint/170551

Static Analysis for AWS Best Practices in Python Code

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

Index Terms: 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

pycefr: Python Competency Level through Code Analysis

Authors: Robles, Gregorio Kula, Raula Gaikovina Ragkhitwetsagul, Chaiyong et al.

Index Terms: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2203.15990

Understanding Code Quality: A Qualitative Evaluation of LLM-Generated vs. Human-Written Code.

Authors: Naqvi, Abiha Jain, Apeksha Goyal, Avisha et al.

Source: International Journal of Performability Engineering. Oct2025, Vol. 21 Issue 10, p559-571. 13p.

Subject Terms: Artificial intelligence, Computer software quality control, Code generators, Computer software development, Python programming language, Software measurement, C++

A Comparison of the Effectiveness of ChatGPT and Co-Pilot for Generating Quality Python Code Solutions

Authors: Nikolaidis, Nikolaos Flamos, Karolos Gulati, Khanak et al.

Source: Nikolaidis, N, Flamos, K, Gulati, K, Feitosa, D, Ampatzoglou, A & Chatzigeorgiou, A 2024, A Comparison of the Effectiveness of ChatGPT and Co-Pilot for Generating Quality Python Code Solutions. in 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C). IEEE, pp. 93-101, 31st International Conference on Software Analysis, Evolution and Reengineering, Rovaniemi, Finland, 12/03/2024.

Index Terms: contributionToPeriodical

URL: https://research.rug.nl/en/publications/71a61522-bda9-4af2-a4fe-0883b069a07c
https://doi.org/10.1109/SANER-C62648.2024.00018
https://hdl.handle.net/11370/71a61522-bda9-4af2-a4fe-0883b069a07c
https://pure.rug.nl/ws/files/1145083793/A_Comparison_of_the_Effectiveness_of_ChatGPT_and_Co-Pilot_for_Generating_Quality_Python_Code_Solutions.pdf
https://www.scopus.com/pages/publications/85202625127
info:eu-repo/semantics/altIdentifier/doi/10.1109/SANER-C62648.2024.00018
info:eu-repo/semantics/altIdentifier/hdl/https://hdl.handle.net/11370/71a61522-bda9-4af2-a4fe-0883b069a07c
info:eu-repo/semantics/altIdentifier/isbn/979-8-3503-5157-6

Applications of Python in Solving Physical Chemistry Problems.

Authors: Singh, Jyoti Passey, Sarita Basu, Debasmi et al.

Source: Resonance: Journal of Science Education. Dec2025, Vol. 30 Issue 12, p1643-1663. 21p.

Subject Terms: Physical & theoretical chemistry, Python programming language, Maxwell-Boltzmann distribution law, Simulation methods & models, Potentiometry, Data analysis, Noble gases, Atmospheric pressure

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

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

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

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

Company/Entity: OPENAI Inc.

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

Authors: Trieu Hung Tran, Elvis Diep, Erik

Index Terms: 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

Authors: Midolo, Alessandro Di Penta, Massimiliano

Index Terms: Computer Science - Software Engineering, text

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

Analysis of Concrete Air Voids: Comparing OpenAI-Generated Python Code with MATLAB Scripts and Enhancing 2D Image Processing Using 3D CT Scan Data

Authors: Asadi, Iman Shpak, Andrei Jacobsen, Stefan

Availability: https://hdl.handle.net/11250/3166074

Polyglot AST: Towards Enabling Polyglot Code Analysis

Authors: Houdaille, P. Khelladi, D. E. Briend, R. et al.

Source: Proc IEEE Int Conf Eng Complex Comput Syst ICECCS. :116-125

Subject Terms: code analysis, development tooling, polyglot programming, Codes (symbols), High level languages, Python, Abstract Syntax Trees, Design time, Java Native Interfaces, Javascript, Runtimes, Software complexity, Web development, Trees (mathematics)

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-65153

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

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

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

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

Towards Vulnerability Injection using Artificial Intelligence

Rumo à injeção de vulnerabilidades em Python com Inteligência Artificial

Authors: Bogaerts, Frédéric Christophe Gabriel

Subject Terms: 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

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