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Refinado por: assunto: Machine Learning remover
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Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data
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Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data

Qiu, Yue ; Garg, Deepak ; Kim, Sung-Min ; Mudawar, Issam ; Kharangate, Chirag R.

International journal of heat and mass transfer, 2021-10, Vol.178, p.121607, Article 121607 [Periódico revisado por pares]

Elsevier Ltd

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2
A catalog of metrics at source code level for vulnerability prediction: A systematic mapping study
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A catalog of metrics at source code level for vulnerability prediction: A systematic mapping study

Codabux, Zadia ; Zakia Sultana, Kazi ; Chowdhury, Md Naseef‐Ur‐Rahman

Journal of software : evolution and process, 2024-07, Vol.36 (7), p.n/a [Periódico revisado por pares]

Chichester: Wiley Subscription Services, Inc

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3
Deriving thresholds of software metrics to predict faults on open source software: Replicated case studies
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Deriving thresholds of software metrics to predict faults on open source software: Replicated case studies

Arar, Ömer Faruk ; Ayan, Kürşat

Expert systems with applications, 2016-11, Vol.61, p.106-121 [Periódico revisado por pares]

Elsevier Ltd

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4
Comparison of threshold identification techniques for object-oriented software metrics
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Comparison of threshold identification techniques for object-oriented software metrics

Shatnawi, Raed

IET software, 2020-12, Vol.14 (6), p.727-738 [Periódico revisado por pares]

The Institution of Engineering and Technology

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5
Developers’ perception matters: machine learning to detect developer-sensitive smells
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Developers’ perception matters: machine learning to detect developer-sensitive smells

Oliveira, Daniel ; Assunção, Wesley K. G. ; Garcia, Alessandro ; Fonseca, Baldoino ; Ribeiro, Márcio

Empirical software engineering : an international journal, 2022-12, Vol.27 (7), Article 195 [Periódico revisado por pares]

New York: Springer US

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6
Detecting Java software similarities by using different clustering techniques
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Detecting Java software similarities by using different clustering techniques

Capiluppi, Andrea ; Di Ruscio, Davide ; Di Rocco, Juri ; Nguyen, Phuong T. ; Ajienka, Nemitari

Information and software technology, 2020-06, Vol.122, p.106279, Article 106279 [Periódico revisado por pares]

Elsevier B.V

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7
Quality assessment framework to rank software projects
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Quality assessment framework to rank software projects

Alqmase, Mohammed ; Alshayeb, Mohammad ; Ghouti, Lahouari

Automated software engineering, 2022-11, Vol.29 (2), p.41, Article 41 [Periódico revisado por pares]

New York: Springer US

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8
An insight into topological, machine and Deep Learning-based approaches for influential node identification in social media networks: a systematic review
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An insight into topological, machine and Deep Learning-based approaches for influential node identification in social media networks: a systematic review

Rashid, Yasir ; Bhat, Javaid Iqbal

Multimedia systems, 2024-02, Vol.30 (1), Article 57 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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9
FCP2Vec: Deep Learning-Based Approach to Software Change Prediction by Learning Co-Changing Patterns from Changelogs
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FCP2Vec: Deep Learning-Based Approach to Software Change Prediction by Learning Co-Changing Patterns from Changelogs

Ahmed, Hamdi Abdurhman ; Lee, Jihwan

Applied sciences, 2023-05, Vol.13 (11), p.6453 [Periódico revisado por pares]

Basel: MDPI AG

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10
Automatic detection of code smells using metrics and CodeT5 embeddings: a case study in C#
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Automatic detection of code smells using metrics and CodeT5 embeddings: a case study in C#

Kovačević, Aleksandar ; Luburić, Nikola ; Slivka, Jelena ; Prokić, Simona ; Grujić, Katarina-Glorija ; Vidaković, Dragan ; Sladić, Goran

Neural computing & applications, 2024-06, Vol.36 (16), p.9203-9220 [Periódico revisado por pares]

London: Springer London

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