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[HTML][HTML] Research and application of machine learning for additive manufacturing
Additive manufacturing (AM) is poised to bring a revolution due to its unique production
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …
A software engineering perspective on engineering machine learning systems: State of the art and challenges
G Giray - Journal of Systems and Software, 2021 - Elsevier
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …
software development, where algorithms are hard-coded by humans, to ML systems …
A systematic literature review on source code similarity measurement and clone detection: Techniques, applications, and challenges
M Zakeri-Nasrabadi, S Parsa, M Ramezani… - Journal of Systems and …, 2023 - Elsevier
Measuring and evaluating source code similarity is a fundamental software engineering
activity that embraces a broad range of applications, including but not limited to code …
activity that embraces a broad range of applications, including but not limited to code …
Advances in machine learning modeling reviewing hybrid and ensemble methods
The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis
M Ayitey Junior, P Appiahene, O Appiah, CN Bombie - Journal of Big Data, 2023 - Springer
Background When you make a forex transaction, you sell one currency and buy another. If
the currency you buy increases against the currency you sell, you profit, and you do this …
the currency you buy increases against the currency you sell, you profit, and you do this …
[HTML][HTML] A survey on machine learning techniques applied to source code
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Code smell detection by deep direct-learning and transfer-learning
T Sharma, V Efstathiou, P Louridas… - Journal of Systems and …, 2021 - Elsevier
Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
A systematic literature review on the code smells datasets and validation mechanisms
M Zakeri-Nasrabadi, S Parsa, E Esmaili… - ACM Computing …, 2023 - dl.acm.org
The accuracy reported for code smell-detecting tools varies depending on the dataset used
to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a …
to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a …
Flakeflagger: Predicting flakiness without rerunning tests
When developers make changes to their code, they typically run regression tests to detect if
their recent changes (re) introduce any bugs. However, many tests are flaky, and their …
their recent changes (re) introduce any bugs. However, many tests are flaky, and their …