Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386492380> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W4386492380 abstract "Abstract Malicious software detection is the most prominent process required by various industries to avoid server failure. It is required to detect malicious software accurately to avoid time and cost wastage. Various research works have been introduced earlier for the detection of malicious software. In the existing work Support Vector Machine (SVM) is introduced for malicious software detection. However, existing works cannot perform well where there are error modules in the software. It is addressed in this suggested study by developing Coupling and Cohesion Metrics based Fault Detection (CCMFD). In this research work, structural measures are mainly examined which come under the cohesion measures and comprise deficient cohesion in approaches (LCOM), and Conceptual Coupling between Object Classes (CCBO). Failure situ- ations and measures relating to information flow are used in other techniques. A high-quality service has a low coupling and a high cohesiveness. These extracted features will be given as input to the enhanced Convolutional Neural Network (CNN) for software mistake forecasting. A complete study analysis is done in a Java simulator, indicating that the suggested approach tends to have superior fault prediction outcomes than the current method." @default.
- W4386492380 created "2023-09-07" @default.
- W4386492380 creator A5091733704 @default.
- W4386492380 date "2023-09-06" @default.
- W4386492380 modified "2023-10-16" @default.
- W4386492380 title "An Enhanced Convolutional Neural Network Schema for Structural Class-based Software Fault Prediction" @default.
- W4386492380 cites W1980851144 @default.
- W4386492380 cites W2012319196 @default.
- W4386492380 cites W2012477002 @default.
- W4386492380 cites W2048456683 @default.
- W4386492380 cites W2111235104 @default.
- W4386492380 cites W2127623179 @default.
- W4386492380 cites W2154446978 @default.
- W4386492380 cites W2903239790 @default.
- W4386492380 cites W2949068118 @default.
- W4386492380 cites W3084008846 @default.
- W4386492380 cites W3141989311 @default.
- W4386492380 cites W3148651721 @default.
- W4386492380 cites W4221019549 @default.
- W4386492380 cites W4283026613 @default.
- W4386492380 doi "https://doi.org/10.21203/rs.3.rs-3322386/v1" @default.
- W4386492380 hasPublicationYear "2023" @default.
- W4386492380 type Work @default.
- W4386492380 citedByCount "0" @default.
- W4386492380 crossrefType "posted-content" @default.
- W4386492380 hasAuthorship W4386492380A5091733704 @default.
- W4386492380 hasConcept C104054115 @default.
- W4386492380 hasConcept C111919701 @default.
- W4386492380 hasConcept C117447612 @default.
- W4386492380 hasConcept C124101348 @default.
- W4386492380 hasConcept C152745839 @default.
- W4386492380 hasConcept C154945302 @default.
- W4386492380 hasConcept C172707124 @default.
- W4386492380 hasConcept C178790620 @default.
- W4386492380 hasConcept C185592680 @default.
- W4386492380 hasConcept C2777904410 @default.
- W4386492380 hasConcept C41008148 @default.
- W4386492380 hasConcept C529173508 @default.
- W4386492380 hasConcept C79403827 @default.
- W4386492380 hasConcept C81363708 @default.
- W4386492380 hasConcept C82214349 @default.
- W4386492380 hasConceptScore W4386492380C104054115 @default.
- W4386492380 hasConceptScore W4386492380C111919701 @default.
- W4386492380 hasConceptScore W4386492380C117447612 @default.
- W4386492380 hasConceptScore W4386492380C124101348 @default.
- W4386492380 hasConceptScore W4386492380C152745839 @default.
- W4386492380 hasConceptScore W4386492380C154945302 @default.
- W4386492380 hasConceptScore W4386492380C172707124 @default.
- W4386492380 hasConceptScore W4386492380C178790620 @default.
- W4386492380 hasConceptScore W4386492380C185592680 @default.
- W4386492380 hasConceptScore W4386492380C2777904410 @default.
- W4386492380 hasConceptScore W4386492380C41008148 @default.
- W4386492380 hasConceptScore W4386492380C529173508 @default.
- W4386492380 hasConceptScore W4386492380C79403827 @default.
- W4386492380 hasConceptScore W4386492380C81363708 @default.
- W4386492380 hasConceptScore W4386492380C82214349 @default.
- W4386492380 hasLocation W43864923801 @default.
- W4386492380 hasOpenAccess W4386492380 @default.
- W4386492380 hasPrimaryLocation W43864923801 @default.
- W4386492380 hasRelatedWork W1587188900 @default.
- W4386492380 hasRelatedWork W1673130894 @default.
- W4386492380 hasRelatedWork W2153523286 @default.
- W4386492380 hasRelatedWork W2168351820 @default.
- W4386492380 hasRelatedWork W2187580475 @default.
- W4386492380 hasRelatedWork W2533633698 @default.
- W4386492380 hasRelatedWork W2605262174 @default.
- W4386492380 hasRelatedWork W3151530686 @default.
- W4386492380 hasRelatedWork W4211211670 @default.
- W4386492380 hasRelatedWork W2359946800 @default.
- W4386492380 isParatext "false" @default.
- W4386492380 isRetracted "false" @default.
- W4386492380 workType "article" @default.