Výsledky vyhledávání - ((java OR jana) OR jan) AND python resource code

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

Autoři: Ahmad, Azeem Sun, Xin

Zdroj: IEEE Access. 13:205254-205277

Témata: 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

Popis souboru: print

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

Quantifying cross-language code reuse via function-level clone detection

Autoři: Yi Rong Yan Zhou

Zdroj: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 10, Pp 1-20 (2025)

Témata: 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

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Přístupová URL adresa: https://doaj.org/article/0e8d85656442482785bc981b326c25a4

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

Autoři: Bhutani Vikram Toosi Farshad Ghassemi Buckley Jim

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

Témata: 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

Popis souboru: electronic resource

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

Přístupová URL adresa: https://doaj.org/article/ac1de08d4c5c4733b3ca9004305cf826

Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data

Autoři: Jakub Idkowiak Jonas Dehairs Jana Schwarzerová a další

Zdroj: Nature Communications, Vol 16, Iss 1, Pp 1-19 (2025)

Témata: Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2041-1723

Přístupová URL adresa: https://doaj.org/article/4e901a73a34347ffbef54049de5ac663

Advancing Code Translation With Context-Aware Pre-Training in Data-Scarce Environments

Autoři: M. V. Deepak Naik J. Swaminathan

Zdroj: IEEE Access, Vol 14, Pp 16717-16730 (2026)

Témata: Automated code translation, BLEU score, CodeBLEU score, CodeT5, contextual code completion, developer productivity, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11367628/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/0e52e140942046b982272989fc43a235

Evaluating AI-generated code for C++, Fortran, Go, Java, Julia, Matlab, Python, R, and Rust

Autoři: Diehl, Patrick Nader, Noujoud Brandt, Steve a další

Témata: Computer Science - Software Engineering, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2405.13101

Neural Network in Java using DeepLearning4J framework vs. Python using TensorFlow framework: Trade-offs Between Execution Speed, Resource Consumption, and Developer Efficiency : A Comparative Benchmark and User Evaluation Study

Additional Titles: Neuronnät i Java (med DeepLearning4J) vs. Python (med TensorFlow): Avvägningar mellan exekveringshastighet, resursförbrukning och utvecklareffektivitet : En Jämförande Prestandamätning och Användarutvärdering

Autoři: Haidari, Marvin Abdi Salah, Salahudin

Témata: Artificial intelligence, Machine learning, Neural network, Convolutional neural network, Performance benchmarking, Execution speed, Model accuracy, Python, Java, Deeplearning4j, TensorFlow, Modified National Institute of Standards and Technology database (MNIST), Image recognition., Artificiell intelligens, Maskininlärning, Artificiellt neuronnät, Konvolutionellt neuralt nätverk, Prestandamätning, Exekveringshastighet, Modellnoggrannhet, DeepLearning4J, Bildigenkänning, 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-368035
TRITA-EECS-EX ; 2025:467

NESTML: a generic modeling language and code generation tool for the simulation of spiking neural networks with advanced plasticity rules.

Autoři: Linssen, Charl Babu, Pooja N. Eppler, Jochen M. a další

Zdroj: Frontiers in Neuroinformatics; 2025, p1-21, 21p

Témata: ARTIFICIAL neural networks, MODELING languages (Computer science), SYNAPSES, C++, SYNTAX (Grammar)

Context‐based transfer learning for low resource code summarization.

Autoři: Guo, Yi Chai, Yu Zhang, Lehuan a další

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

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

ISEV2025 Abstract Book.

Zdroj: Journal of Extracellular Vesicles; Oct2025 Supplement 1, Vol. 14, p1-555, 555p

Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems.

Autoři: Sun, Zhensu Du, Xiaoning Song, Fu a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Jan2025, Vol. 34 Issue 1, p1-22, 22p

Témata: LANGUAGE models, NEURAL codes, POWER resources, DEEP learning, SCIENTIFIC community

Cross-Language Code Smell Detection via Transfer Learning.

Autoři: Sandouka, Rana Aljamaan, Hamoud

Zdroj: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 17, p9293, 23p

Témata: JAVA programming language, PYTHON programming language, TRANSFER of training, PROGRAMMING languages, ENSEMBLE learning, COMPUTER software quality control

Benchmarking WebAssembly for Embedded Systems.

Autoři: MORON, KONARD WALLENTOWITZ, STEFAN

Zdroj: ACM Transactions on Architecture & Code Optimization; Sep2025, Vol. 22 Issue 3, p1-21, 21p

PyFibers: An open-source NEURON-Python package to simulate responses of model nerve fibers to electrical stimulation.

Autoři: Marshall, Daniel P. Farah, Elie S. Musselman, Eric D. a další

Zdroj: PLoS Computational Biology; 12/12/2025, Vol. 21 Issue 12, p1-30, 30p

Témata: NERVE fibers, ELECTRIC stimulation, OPEN source software, PYTHON programming language, COMPUTER simulation, NEURONS, NEUROMODULATION

Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning

Autoři: Puccioni, Laura Farshin, Alireza Scazzariello, Mariano a další

Zdroj: Digital Futures Proceedings of IEEE/ACM International Workshop on Large Language Models for Code 2025, LLM4Code 2025.

Témata: Large Language Models, LLMs, pruning, code

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-374905
https://kth.diva-portal.org/smash/get/diva2:2025739/FULLTEXT01.pdf

Assessing and Analyzing the Correctness of GitHub Copilot's Code Suggestions.

Autoři: Mo, Ran Wang, Dongyu Zhan, Wenjing a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Sep2025, Vol. 34 Issue 7, p1-32, 32p

Témata: PROGRAMMING languages, CODE generators, STATISTICAL accuracy, FAILURE analysis, EMPIRICAL research, COMPUTER software development

Korporace: GITHUB Inc.

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

Autoři: Komolov, Sirojiddin Mazzara, Manuel Bajwa, Imran Sarwar a další

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

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

Resource-Efficient & Effective Code Summarization

Autoři: Afrin, Saima Call, Joseph Nguyen, Khai-Nguyen a další

Zdroj: 2025 IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering (Forge). :224-235

Témata: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering

Přístupová URL adresa: http://arxiv.org/abs/2502.03617

Selecting Suitable Programming Languages for Beginner-Level Instruction.

Autoři: Kadams, Adaiti Allen Oyelere, Solomon Sunday

Zdroj: International Journal of Technology in Education & Science; 2026, Vol. 10 Issue 1, p133-161, 29p

Témata: PYTHON programming language, JAVA programming language, HIGHER education, STUDENT interests, C++, TECHNOLOGY Acceptance Model, PROGRAMMING languages, TEACHING aids

Creating a Python platform for students to learn full-stack development of financial applications.

Autoři: Tang, Song

Zdroj: Financial Innovation; 1/21/2026, Vol. 12 Issue 1, p1-29, 29p

Témata: PYTHON programming language, COMPUTER software development, FINANCE education, EMPLOYABILITY, FINANCE software