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A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software

A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software

Subhashis Chatterjee, Bappa Maji
Copyright: © 2020 |Volume: 11 |Issue: 4 |Pages: 13
ISSN: 1947-959X|EISSN: 1947-9603|EISBN13: 9781799806363|DOI: 10.4018/IJSSMET.2020100103
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MLA

Chatterjee, Subhashis, and Bappa Maji. "A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software." IJSSMET vol.11, no.4 2020: pp.45-57. http://doi.org/10.4018/IJSSMET.2020100103

APA

Chatterjee, S. & Maji, B. (2020). A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 11(4), 45-57. http://doi.org/10.4018/IJSSMET.2020100103

Chicago

Chatterjee, Subhashis, and Bappa Maji. "A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) 11, no.4: 45-57. http://doi.org/10.4018/IJSSMET.2020100103

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Abstract

In this study, a fuzzy logic-based framework has been proposed to predict the situation of the software modules in the earlier phases of software lifecycle. The proposed model has taken into account domain experts' opinions and the available state of different software metrics as inputs. On the basis of dependability measures of software, different modules have been ranked earlier in the development process. Effect of the modules on the reliability, security, and availability of software has been judged by the proposed technique based on Mahalanobis distance metric. The study of software dependability in early phase assists the software developers to take corrective actions, which leads to minimize the testing efforts as well as development time. The proposed technique has been implemented on the promise software engineering repository data set. Performance of the proposed methodology is promising in identifying the fault-prone software modules. The result has also been compared with some known methodologies.

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