Suchergebnisse - (java OR jana) AND python (source OR resource) code*

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

Base, Instruct, and Fine-Tune: Evaluating LLMs for Cross-Language Flaky Test Detection

Autoren: Ahmad, Azeem Sun, Xin

Quelle: IEEE Access. 13:205254-205277

Schlagwörter: Codes, Java, Semantics, C plus plus languages, Python, Large language models, Vocabulary, Training, Adaptation models, Robustness, Flaky tests, non-deterministic tests, fine-tuning, software testing, large language models, base models

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-220548
https://doi.org/10.1109/ACCESS.2025.3639645

Git ADV: Improving Java & Python Source Code Merging using Abstract Data Structures

Autoren: Chaudhari, Nirmal Jain, Madhur Mosser, Sébastien et al.

Weitere Verfasser: Chaudhari, Nirmal Jain, Madhur Mosser, Sébastien et al.

Schlagwörter: source code, merge, tool, software engineering

Zugangs-URL: http://hdl.handle.net/11375/28838

Understanding Flaky Tests Through Linguistic Diversity: A Cross-Language and Comparative Machine Learning Study

Autoren: Ahmad, Azeem Sun, Xin Naeem, Muhammad Rashid et al.

Quelle: IEEE Access. 13:54561-54584

Schlagwörter: Codes, Accuracy, Vocabulary, Java, Feature extraction, Python, Training, Reproducibility of results, Random forests, Programming, Flaky tests, non-deterministic tests, machine learning, artificial intelligence, software testing

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-213193
https://doi.org/10.1109/ACCESS.2025.3553626

An Algorithm-Adaptive Source Code Converter to Automate the Translation from Python to Java

Autoren: Eric Jin Yu Sun

Quelle: Computer Science and Information Technology Trends. :215-229

Analysing Software Quality of AI-Translated Code: A Comparative Study of Large Language Models Using Static Analysis

Autoren: Bhutani Vikram Toosi Farshad Ghassemi Buckley Jim

Quelle: Applied Computer Systems, Vol 30, Iss 1, Pp 105-121 (2025)

Schlagwörter: artificial intelligence, chatgpt4.1, c++, deep learning, deepseek r1, java, machine learning, nmt, object oriented, programming languages translation, python, source code translation, smt, Computer software, QA76.75-76.765

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2255-8691

Zugangs-URL: https://doaj.org/article/ac1de08d4c5c4733b3ca9004305cf826

Design Pattern Prediction From Source Code Using LLM–Based Feature Engineering and SVM Classification.

Autoren: Komolov, Sirojiddin Mazzara, Manuel Bajwa, Imran Sarwar et al.

Quelle: IET Software (Wiley-Blackwell). 1/16/2026, Vol. 2026, p1-25. 25p.

Schlagwörter: *SUPPORT vector machines, *MACHINE learning, *LANGUAGE models, *SOURCE code, *FEATURE selection, *JAVA programming language, *PROGRAMMING languages, *SOFTWARE engineering

Implementation of Gated Graph Neural Network (GGNN) on Bug Prediction in Java, Python, and C++ Programming Languages.

Autoren: Juwono, Elroy Novarino Phoa, Matthew Farrell Wijaya, Michael et al.

Quelle: Procedia Computer Science. 2025, Vol. 269, p1171-1180. 10p.

Schlagwörter: Graph neural networks, Java programming language, Python programming language, C++, Data structures, Defect tracking (Computer software development), Software failures, Machine learning

A detection process to create awareness of source-code plagiarism among students using it to pass introductory programming.

Autoren: Smit, Imelda Naudé, Eduan Zulu, Busisiwe

Quelle: Independent Journal of Teaching & Learning; 2024, Vol. 19 Issue 1, p79-92, 14p

Schlagwörter: PLAGIARISM, STUDENTS, COVID-19 pandemic, PYTHON programming language, AWARENESS

Identification of Source Code Plagiarism Using a Natural Language Processing (NLP) Approach Based on Code Writing Style Analysis

Autoren: Muhammad Ilham Akbar Novita Kurnia Ningrum

Quelle: Journal of Applied Informatics and Computing, Vol 9, Iss 6, Pp 3079-3086 (2025)

Schlagwörter: code plagiarism, codebert, siamese network, deep learning, source code plagiarism, identification, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/11206; https://doaj.org/toc/2548-6861

Zugangs-URL: https://doaj.org/article/f40cbf64cc594c2e8ae97f26ed727c5a

Using ChatGPT as a Static Application Security Testing Tool.

Autoren: Bakhshandeh, Atieh Keramatfar, Abdalsamad Norouzi, Amir et al.

Quelle: ISeCure; Nov2023, Vol. 15 Issue 3, p1-8, 8p

Schlagwörter: CHATGPT, ARTIFICIAL intelligence, SOURCE code, PYTHON programming language, NATURAL languages

CNN-BASED CODE READABILITY CLASSIFICATION AND BUG LOCALIZATION IN PROGRAMMING FRAMEWORK.

Autoren: BARRAMEDA, ROLANDO B. BALLERA, MELVIN A.

Quelle: TPM: Testing, Psychometrics, Methodology in Applied Psychology; 2025 Supplement, Vol. 32, p201-206, 6p

Towards a Block-Level ML-Based Python Vulnerability Detection Tool.

Autoren: Bagheri, Amirreza Hegedűs, Péter

Quelle: Acta Cybernetica; 2024, Vol. 26 Issue 3, p323-371, 49p

Schlagwörter: COMPUTER software, SOURCE code, SYSTEM failures, DEEP learning, MACHINE learning

A dataset for human-written and AI-generated code source classification.

Autoren: Boukili G Garouani SE Riffi J

Quelle: Data in brief [Data Brief] 2026 Jan 29; Vol. 65, pp. 112527. Date of Electronic Publication: 2026 Jan 29 (Print Publication: 2026).

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Elsevier B.V Country of Publication: Netherlands NLM ID: 101654995 Publication Model: eCollection Cited Medium: Internet ISSN: 2352-3409 (Electronic) Linking ISSN: 23523409 NLM ISO Abbreviation: Data Brief Subsets: PubMed not MEDLINE

Legal freshwater turtle meat trade in Indonesia only marginally contributes to collectors' livelihoods.

Autoren: Nijman, Vincent Shepherd, Chris R.

Quelle: Discover Animals (3004-894X). Dec2025, Vol. 2 Issue 1, p1-9. 9p.

Schlagworte: Wild animal trade, Income, Nature conservation, Indonesians, Trade regulation, Turtles

Geografische Kategorien: Indonesia

Enhancing Code Summarization with Graph Embedding and Pre-Trained Model.

Autoren: Li, Lixuan Li, Jie Xu, Yihui et al.

Quelle: International Journal of Software Engineering & Knowledge Engineering. Nov/Dec2023, Vol. 33 Issue 11/12, p1765-1786. 22p.

Schlagwörter: *PROGRAMMING languages, *INFORMATION resources, LANGUAGE models, SOURCE code, PYTHON programming language

GNPSum: A code summarization enhancement framework based on Graph Node Position.

Autoren: Cheng, Haogang Xu, Ling Huangfu, Luwen et al.

Quelle: Information & Software Technology. Nov2025, Vol. 187, pN.PAG-N.PAG. 1p.

Schlagwörter: JAVA programming language, PYTHON programming language, GRAPH theory, REPRESENTATIONS of graphs

Digital Capability, Open-Source Use, and Interoperability Standards Within the National Health Service in England: Survey of Health Care Trusts.

Autoren: Bennion, Matthew Russell Spencer, Ross Moore, Roger K et al.

Quelle: JMIR Human Factors; 2025, Vol. 12, p1-14, 14p

Schlagwörter: OPEN source software, DIGITAL technology, NATIONAL health services, HEALTH facilities, DATA management, ENGINEERING standards, DIGITAL transformation

Geografische Kategorien: ENGLAND

Firma/Körperschaft: GREAT Britain. National Health Service

FastHPOCR: pragmatic, fast, and accurate concept recognition using the human phenotype ontology.

Autoren: Groza, Tudor Gration, Dylan Baynam, Gareth et al.

Quelle: Bioinformatics. Jul2024, Vol. 40 Issue 7, p1-8. 8p.

Schlagwörter: *LANGUAGE models, *HUMAN phenotype, *SOURCE code, *NATURAL languages, *PHENOTYPES

Comprehending C codes with LLMs: Effective comment generation through retrieval and reasoning.

Autoren: Majumdar, Srijoni Deshpande, Adwita Das, Partha Pratim et al.

Quelle: Pattern Recognition Letters. Jan2026, Vol. 199, p295-302. 8p.

Schlagwörter: *C (Computer program language), *LANGUAGE models, *EVALUATION methodology, *SOFTWARE maintenance, *ANNOTATIONS, *NATURAL language processing, *MACHINE learning