CK Metrics as a Software Fault-Proneness Predictor - 8 Angebote vergleichen
Bester Preis: Fr. 4.61 (€ 4.71)¹ (vom 01.07.2018)1
CK Metrics as a Software Fault-Proneness Predictor (1991)
DE NW EB DL
ISBN: 9783743872325 bzw. 3743872323, in Deutsch, Bookrix, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Versandkostenfrei.
CK Metrics as a Software Fault-Proneness Predictor: Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-proneness of the software. `Classic` set of metrics was planned by Chidamber and Kemerer in 1991. Chidamber and Kemerer (CK) metrics suite is the most widely used metrics suite for the purpose of object-oriented software fault-proneness prediction. CK metrics?are used for numerous function of study, e.g. defect prediction. CK metrics are the good predictor of fault-proneness of classes.C5.0 algorithm is one of the classification techniques of data mining. It is necessarily selected to partition data set into several smaller subsets in every recursion of creating decision tree. Object-oriented metrics play a very important role to quantify the effect of key factors to determine the fault-proneness. For fault-prediction model CK Metrics: Weighted Methods for Class (WMC), Depth of Inheritance Tree (DIT), Number of Children (NOC), Lack of Cohesion of Methods (LCOM), Response for Class (RFC), and Coupling Between Objects (CBO), are used as a independent variables. Englisch, Ebook.
CK Metrics as a Software Fault-Proneness Predictor: Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-proneness of the software. `Classic` set of metrics was planned by Chidamber and Kemerer in 1991. Chidamber and Kemerer (CK) metrics suite is the most widely used metrics suite for the purpose of object-oriented software fault-proneness prediction. CK metrics?are used for numerous function of study, e.g. defect prediction. CK metrics are the good predictor of fault-proneness of classes.C5.0 algorithm is one of the classification techniques of data mining. It is necessarily selected to partition data set into several smaller subsets in every recursion of creating decision tree. Object-oriented metrics play a very important role to quantify the effect of key factors to determine the fault-proneness. For fault-prediction model CK Metrics: Weighted Methods for Class (WMC), Depth of Inheritance Tree (DIT), Number of Children (NOC), Lack of Cohesion of Methods (LCOM), Response for Class (RFC), and Coupling Between Objects (CBO), are used as a independent variables. Englisch, Ebook.
2
CK Metrics as a Software Fault-Proneness Predictor Sunil Sikka Author (1991)
~EN NW EB DL
ISBN: 9783743872325 bzw. 3743872323, vermutlich in Englisch, BookRix, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd.
Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-proneness of the software. Classic set of metrics was planned by Chidamber and Kemerer in 1991. Chidamber and Kemerer (CK) metrics suite is the most widely used metrics suite for the purpose of object-oriented software fault-proneness prediction. CK metrics are used for numerous function of study, e.g. defect prediction. CK metrics are the good predictor of fault-proneness of classes.C5.0 algorithm is one of the classification techniques of data mining. It is necessarily selected to partition data set into several smaller subsets in every recursion of creating decision tree. Object-oriented metrics play a very important role to quantify the effect of key factors to determine the fault-proneness. For fault-prediction model CK Metrics: Weighted Methods for Class (WMC), Depth of Inheritance Tree (DIT), Number of Children (NOC), Lack of Cohesion of Methods (LCOM), Response for Class (RFC), and Coupling Between Objects (CBO), are used as a independent variables.
Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-proneness of the software. Classic set of metrics was planned by Chidamber and Kemerer in 1991. Chidamber and Kemerer (CK) metrics suite is the most widely used metrics suite for the purpose of object-oriented software fault-proneness prediction. CK metrics are used for numerous function of study, e.g. defect prediction. CK metrics are the good predictor of fault-proneness of classes.C5.0 algorithm is one of the classification techniques of data mining. It is necessarily selected to partition data set into several smaller subsets in every recursion of creating decision tree. Object-oriented metrics play a very important role to quantify the effect of key factors to determine the fault-proneness. For fault-prediction model CK Metrics: Weighted Methods for Class (WMC), Depth of Inheritance Tree (DIT), Number of Children (NOC), Lack of Cohesion of Methods (LCOM), Response for Class (RFC), and Coupling Between Objects (CBO), are used as a independent variables.
3
CK Metrics as a Software Fault-Proneness Predictor (2018)
EN NW EB DL
ISBN: 9783743872325 bzw. 3743872323, in Englisch, BookRix, BookRix, BookRix, neu, E-Book, elektronischer Download.
Lieferung aus: Australien, in-stock.
Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-p.
Predicting Fault-proneness of software modules is essential for cost-effective test planning. Fault-proneness could play a key role in quality control of software. Various studies have shown the importance of software metrics in predicting fault-p.
6
CK Metrics as a Software Fault-Proneness Predictor
DE NW EB
ISBN: 9783743872325 bzw. 3743872323, in Deutsch, BookRix, neu, E-Book.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
CK Metrics as a Software Fault-Proneness Predictor
DE NW
ISBN: 9783743872325 bzw. 3743872323, in Deutsch, BookRix, neu.
Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
8
CK Metrics as a Software Fault-Proneness Predictor
~EN NW EB DL
ISBN: 9783743872325 bzw. 3743872323, vermutlich in Englisch, BookRix, neu, E-Book, elektronischer Download.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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