Sentence examples for test derivations from inspiring English sources

Competing latent variable models were identified in previous studies and a priori model modifications were made to test derivations of the nine base models.

Model based test derivation is now widely used for deriving functional tests for various systems including communication protocols and other reactive systems.

For instance, in test derivation, checking if a transition of the black-box Implementation Under Test (IUT) transfers wrongly from a current state involves distinguishing a next reference configuration from some other configurations of the specification EFSM as described in (Bochmann & Petrenko 1994; Bourhfir et al. 2001; Ramalingom et al. 2003; Petrenko et al. 2004; El-Fakih et al. 2008).

We propose an automatic test derivation method for testing interoperability of communication protocols.

The work can be applied in various domains such as EFSM-based test derivation, mutation testing, and fault diagnosis.

Many EFSM based testing problems, such as mutation testing, fault diagnosis, and test derivation involve the derivation of input sequences that distinguish configurations of a given EFSM specification.

In one way or another, almost all related work for EFSM based test derivation relies on distinguishing two or more configurations of the specification EFSM.

Although such techniques work very well with regard to the speed of the test derivation, they leave the tester with one important task that influences the quality of the overall testing process: test purposes have to be formulated manually.

EFSM based related testing problems, test derivation approaches, and applications domains are given in several papers such as (Bochmann & Petrenko 1994; Bourhfir et al. 2001; Cavalli et al. 2003; Ramalingom et al. 2003; El-Fakih et al. 2003; Petrenko et al. 2004; El-Fakih et al. 2008; Sugeta et al. 2004; Jia & Harman 2011; Keum et al. 2006; Wong et al. 2009).

Conversely, err⁡·OOBt is the number of misclassifications tested on a tree t whose input was the nonpermuted values of variable x i. Validity of permutation test derivation of VIM in the RF algorithm operates on the premise that if a variable is "important," then permuting its values (realistically) leads to reduced accuracy of class prediction.

Some of the people tested have derivations of the Merisi family name.