Search Results - (java OR jana) AND python resource code*
-
1
Additional Titles: Neuronnät i Java (med DeepLearning4J) vs. Python (med TensorFlow): Avvägningar mellan exekveringshastighet, resursförbrukning och utvecklareffektivitet : En Jämförande Prestandamätning och Användarutvärdering
Authors:
Index Terms: 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 -
2
Authors:
Source: IEEE Access. 13:205254-205277
Subject Terms: 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
File Description: print
-
3
Authors: et al.
Source: ACM Transactions on Software Engineering & Methodology; Jan2025, Vol. 34 Issue 1, p1-22, 22p
Subject Terms: LANGUAGE models, NEURAL codes, POWER resources, DEEP learning, SCIENTIFIC community
-
4
Authors:
Source: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 17, p9293, 23p
-
5
Authors: et al.
Source: 2025 IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering (Forge). :224-235
Subject Terms: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering
Access URL: http://arxiv.org/abs/2502.03617
-
6
Authors: et al.
Source: ACM Transactions on Software Engineering & Methodology; Sep2025, Vol. 34 Issue 7, p1-32, 32p
Subject Terms: PROGRAMMING languages, CODE generators, STATISTICAL accuracy, FAILURE analysis, EMPIRICAL research, COMPUTER software development
Company/Entity: GITHUB Inc.
-
7
Authors:
Source: ACM Transactions on Software Engineering & Methodology; Nov2025, Vol. 34 Issue 8, p1-39, 39p
-
8
Authors: et al.
Source: Software: Practice & Experience; Mar2024, Vol. 54 Issue 3, p465-482, 18p
-
9
Authors: et al.
Source: ICSE: International Conference on Software Engineering; 2024, p1-12, 12p
Subject Terms: CODE generators, PRAGMATICS, BENCHMARKING (Management), MANUSCRIPTS, PYTHON programming language
-
10
Authors: et al.
Source: International Journal of Software Engineering & Knowledge Engineering; Nov/Dec2023, Vol. 33 Issue 11/12, p1765-1786, 22p
-
11
Authors:
Source: Frontiers in Computer Science; 2025, p1-14, 14p
-
12
Authors: et al.
-
13
Authors:
Source: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 2, p83-99, 17p
-
14
Authors:
Source: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 10, Pp 1-20 (2025)
Subject Terms: 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
File Description: electronic resource
-
15
Authors:
Source: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7472, 27p
-
16
Authors:
Source: Journal of Information Processing Systems; Aug2025, Vol. 21 Issue 4, p401-412, 12p
-
17
Authors: et al.
Source: Proceedings of the ACM on Programming Languages. 8:677-708
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Programming Languages, Programming Languages (cs.PL), Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2308.09895
-
18
Authors:
Source: ACM Transactions on Architecture & Code Optimization; Sep2025, Vol. 22 Issue 3, p1-21, 21p
-
19
Authors: et al.
Source: ACM Transactions on Software Engineering & Methodology; Jul2025, Vol. 34 Issue 6, p1-39, 39p
-
20
Authors: et al.
Source: ICSE: International Conference on Software Engineering; 2024, p1-13, 13p
Subject Terms: LANGUAGE models, PYTHON programming language, C++, EMPIRICAL research, SOURCE code
Nájsť tento článok vo Web of Science
Full Text Finder