Applying Convolutional Neural Networks to Adjust Code Complexity Metrics
In the software development process, testing activities are responsible for identifying the presence of defects and allowing them to be repaired before delivery to the end user. Previous research on cost reduction strategies attributed to software testing, focused on test case prioritization techniq...
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| Format: | Online |
| Language: | Portuguese |
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Universidade Estadual de Campinas
2019
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| Online Access: | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/1833 |
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| author | Silva, Nykson da Vilela, Plinio |
| author_facet | Silva, Nykson da Vilela, Plinio |
| author_sort | Silva, Nykson da |
| collection | Portal de Eventos Científicos da UNICAMP |
| container_reference | Revista dos Trabalhos de Iniciação Científica da UNICAMP; n. 27 (2019): Congresso de Iniciação Científica UNICAMP; 1-1 |
| description | In the software development process, testing activities are responsible for identifying the presence of defects and allowing them to be repaired before delivery to the end user. Previous research on cost reduction strategies attributed to software testing, focused on test case prioritization techniques based on code size and complexity metrics in order to reduce the cost of software and still guarantee the ability to detect defects. However, these studies did not considered aspects related to the developer. |
| first_indexed | 2025-10-08T13:55:28Z |
| format | Online |
| id | ojs-article-1833 |
| institution | Universidade Estadual de Campinas |
| issn | 2596-1969 |
| language | por |
| last_indexed | 2025-10-08T13:55:28Z |
| publishDate | 2019 |
| publisher | Universidade Estadual de Campinas |
| record_format | ojs |
| spelling | ojs-article-18332025-09-26T14:39:16Z Applying Convolutional Neural Networks to Adjust Code Complexity Metrics Silva, Nykson da Vilela, Plinio Software testing Software defects Complexity metrics In the software development process, testing activities are responsible for identifying the presence of defects and allowing them to be repaired before delivery to the end user. Previous research on cost reduction strategies attributed to software testing, focused on test case prioritization techniques based on code size and complexity metrics in order to reduce the cost of software and still guarantee the ability to detect defects. However, these studies did not considered aspects related to the developer. Universidade Estadual de Campinas 2019-11-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artigo de convidado application/pdf https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/1833 10.20396/revpibic2720191833 Revista dos Trabalhos de Iniciação Científica da UNICAMP; n. 27 (2019): Congresso de Iniciação Científica UNICAMP; 1-1 2596-1969 por https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/1833/1892 Copyright (c) 2019 Revista dos Trabalhos de Iniciação Científica da UNICAMP http://creativecommons.org/licenses/by/4.0 |
| spellingShingle | Silva, Nykson da Vilela, Plinio Software testing Software defects Complexity metrics Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title | Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title_full | Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title_fullStr | Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title_full_unstemmed | Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title_short | Applying Convolutional Neural Networks to Adjust Code Complexity Metrics |
| title_sort | applying convolutional neural networks to adjust code complexity metrics |
| topic | Software testing Software defects Complexity metrics |
| url | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/1833 |
| work_keys_str_mv | AT silvanyksonda applyingconvolutionalneuralnetworkstoadjustcodecomplexitymetrics AT vilelaplinio applyingconvolutionalneuralnetworkstoadjustcodecomplexitymetrics |
