scholarly journals Simulation and embedded software development for Anton, a parallel machine with heterogeneous multicore ASICs

2008 ◽  
Author(s):  
J. P. Grossman ◽  
Cliff Young ◽  
Joseph A. Bank ◽  
Kenneth Mackenzie ◽  
Douglas J. Ierardi ◽  
...  
Keyword(s):  
Software Development ◽  
Parallel Machine ◽  
Embedded Software ◽  
Heterogeneous Multicore

Application of Error Estimating Model to Control Quality in Embedded Software Development

2010 ◽  
Vol 130 (3) ◽  
pp. 496-502
Author(s):  
Yoshiyuki Anan ◽  
Toyoshiro Nakashima ◽  
Kazunori Iwata ◽  
Hiroshi Yonemitsu ◽  
Tetsu Yoshioka ◽  
...  
Keyword(s):  
Software Development ◽  
Embedded Software ◽  
Control Quality

Design Patterns Reuse for Real Time Embedded Software Development

2009 ◽  
Author(s):  
Gabriel de Souza Pereira Moreira ◽  
Denis Ávila Montini ◽  
Daniela América da Silva ◽  
Felipe Rafael Motta Cardoso ◽  
Luiz Alberto Vieira Dias ◽  
...  
Keyword(s):  
Software Development ◽  
Real Time ◽  
Design Patterns ◽  
Embedded Software

Successfully outsourcing embedded software development

Computer ◽  
2006 ◽  
Vol 39 (1) ◽  
pp. 55-61 ◽  
Author(s):  
J.W. Rottman
Keyword(s):  
Software Development ◽  
Embedded Software

Estimating Interval of the Number of Errors for Embedded Software Development Projects

2014 ◽  
Vol 2 (3) ◽  
pp. 40-50 ◽  
Author(s):  
Kazunori Iwata ◽  
Toyoshiro Nakasima ◽  
Yoshiyuki Anan ◽  
Naohiro Ishii
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Software Development ◽  
Previous Investigation ◽  
Interval Estimation ◽  
Embedded Software ◽  
Point Estimation ◽  
Support Vector ◽  
Development Projects ◽  
Artificial Neural Network Ann

Previous investigation focused on the prediction of total and errors for embedded software development projects using an artificial neural network (ANN). However, methods using ANNs have reached their improvement limits, since an appropriate value is estimated using what is known as point estimation in statistics. This paper proposes a method for predicting the number of errors for embedded software development projects using interval estimation provided by a support vector machine and ANN.

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