A method for developing node probability table using qualitative value of software metrics

Author

Kumar, Chandan ; Yadav, Dilip Kumar

Author_Institution

Dept. of Comput. Applic., Nat. Inst. of Technol. Jamshedpur, Jamshedpur, India

fYear

2015

fDate

7-8 Feb. 2015

Firstpage

1

Lastpage

5

Abstract

Recently, Bayesian Belief Network (BBN) becomes one of the most popular choices for uncertainty modeling and has been widely used in software engineering such as defect prediction, reliability and quality prediction, testing effort prediction and software risk assessment. The Node Probability Tables (NPT) play a vital role in BBN. Failure data is not available in the early phases (i.e., phases which occur before testing phase) of software development life cycle (SDLC). However, metrics of early phases of SDLC can be assessed qualitatively. Therefore, an intelligent selection of software metrics also plays a vital role in developing a software defect prediction model using BBN. In this paper, a technique has been proposed to develop the NPT of a BBN using the qualitative value of software metrics.

Keywords

Bayes methods; graph theory; software development management; software metrics; Bayesian belief network; node probability table; qualitative value; software defect prediction model; software development life cycle; software engineering; software metrics; Bayes methods; Predictive models; Smart phones; Software; Software metrics; Uncertainty; Bayesian Belief Network; Node Probability Table; Software Metrics;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Communication, Control and Information Technology (C3IT), 2015 Third International Conference on

Conference_Location

Hooghly

Print_ISBN

978-1-4799-4446-0

Type

conf

DOI

10.1109/C3IT.2015.7060187

Filename

7060187