Suchergebnisse - java and python (source OR resource) code~

Context‐based transfer learning for low resource code summarization.

Autoren: Guo, Yi Chai, Yu Zhang, Lehuan et al.

Quelle: Software: Practice & Experience; Mar2024, Vol. 54 Issue 3, p465-482, 18p

Schlagwörter: SOFTWARE maintenance, TRANSFER of training, LANGUAGE models, JAVA programming language, SOURCE code, NEURAL circuitry

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

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

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

Context-Enriched Logging for Intelligent Code Fix Suggestions Using Large Language Models.

Autoren: Kurapati, Maheswara

Quelle: Journal of Computer Science & Technology Studies; 2025, Vol. 7 Issue 11, p15-22, 8p

Schlagwörter: METADATA, MACHINE learning, COMPUTER software, FAILURE analysis, DATA analytics, DATA logging

Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs

Autoren: Federico Cassano John Gouwar Francesca Lucchetti et al.

Quelle: Proceedings of the ACM on Programming Languages. 8:677-708

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Programming Languages, Programming Languages (cs.PL), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2308.09895

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

Multi-Label Classification of Pure Code.

Autoren: Gao, Bin Qin, Hongwu Ma, Xiuqin

Quelle: International Journal of Software Engineering & Knowledge Engineering; Oct2024, Vol. 34 Issue 10, p1641-1659, 19p

Schlagwörter: PROGRAMMING languages, SOURCE code, CLASSIFICATION, INSTITUTIONAL repositories, ENCODING

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

Context‐based transfer learning for low resource code summarization

Autoren: Yi Guo Yu Chai Lehuan Zhang et al.

Quelle: Software: Practice and Experience. 54:465-482

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

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

Measuring Cyclomatic Complexity of Source Code Using Machine Learning.

Autoren: Odeh, Ayman Hussein Odeh, Munther Odeh, Hussein et al.

Quelle: Revue d'Intelligence Artificielle; Feb2024, Vol. 38 Issue 1, p183-191, 9p

Schlagwörter: SOURCE code, MACHINE learning, PROGRAMMING languages, COMPUTER software development, C++, PYTHON programming language

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

SBOM generation based on code-level external component trees.

Autoren: Kong X Zhuo H Miao X et al.

Quelle: Scientific reports [Sci Rep] 2025 Nov 24; Vol. 15 (1), pp. 45277. Date of Electronic Publication: 2025 Nov 24.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

RIOS: A Task Scheduler in Source Code for Teaching and Implementing Concurrent or Real-Time Software.

Autoren: Vahid, Frank Givargis, Tony

Quelle: Proceedings of the ASEE Annual Conference & Exposition; 2022, p1-14, 14p

Schlagwörter: SOURCE code, MICROPROCESSOR programming, REAL-time computing, EMBEDDED computer systems, COMPUTER operating systems

Cross-lingual Performance of CodeGPT on the Code Completion Task

Autoren: Kuo, Nadine (author)

Index Begriffe: Code completion, Large Language Models (LLMs), Transformers, CodeGPT, Self-attention, Autocompletion, bachelor thesis

URL: http://resolver.tudelft.nl/uuid:2b2386e8-f9a9-4d77-9a4a-a4e7a5208d38
https://github.com/AISE-TUDelft/CodeShop
https://github.com/AISE-TUDelft/CodeShop

AVATAR: A Parallel Corpus for Java-Python Program Translation

Autoren: Ahmad, Wasi Uddin Tushar, Md Golam Rahman Chakraborty, Saikat et al.

Index Begriffe: Computer Science - Software Engineering, Computer Science - Computation and Language, text

URL: http://arxiv.org/abs/2108.11590

Program Code Generation with Generative AIs.

Autoren: Idrisov, Baskhad Schlippe, Tim

Quelle: Algorithms; Feb2024, Vol. 17 Issue 2, p62, 19p

Schlagwörter: GENERATIVE artificial intelligence, TIME complexity, CHATGPT, GENERATIVE pre-trained transformers, PROBLEM solving

Implementation of python source code comparison results with Java using bubble sort method

Autoren: Entik Insanudin

Quelle: Journal of Physics: Conference Series. 1280:032027

Schlagwörter: 0103 physical sciences, 01 natural sciences

Zugangs-URL: https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002225554210639
https://ui.adsabs.harvard.edu/abs/2019JPhCS1280c2027I/abstract