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

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

Kazunori Iwata, Toyoshiro Nakasima, Yoshiyuki Anan, Naohiro Ishii
Copyright: © 2014 |Pages: 11
DOI: 10.4018/ijsi.2014070104
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Abstract

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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Estimating Error Interval Models

Original Data Sets

Using the following data, we created models to estimate a class to which the number of planning errors (Err) belongs.

  • Err: ``Number of errors'' in a project requiring the estimation of the interval to which it belongs.

  • Vnew: ``Volume of newly added'', which denotes the number of steps in the newly generated functions of the target project.

  • Vmodify: ``Volume of modification'' denoting the number of steps modified or added to existing functions to use the target project.

  • Vsurvey: ``Volume of original project'', which denotes the original number of steps in the modified functions.

  • Vreuse: ``Volume of reuse'' denoting the number of steps in functions of which only an external method has been confirmed and which are applied to the target project design without confirming the internal contents.

  • Type: The type of machine equipped with the developed software. In our case, there are 29 types of projects.

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