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A new fuzzy rule based algorithm for estimating software faults in early phase of development

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Abstract

Estimation of reliability and the number of faults present in software in its early development phase, i.e., requirement analysis or design phase is very beneficial for developing reliable software with optimal cost. Software reliability prediction in early phase of development is highly desirable to the stake holders, software developers, managers and end users. Since, the failure data are unavailable in early phase of software development, different reliability relevant software metrics and similar project data are used to develop models for early software fault prediction. The proposed model uses the linguistic values of software metrics in fuzzy inference system to predict the total number of faults present in software in its requirement analysis phase. Considering specific target reliability, weightage of each input software metrics and size of software, an algorithm has been proposed here for developing general fuzzy rule base. For model validation of the proposed model, 20 real software project data have been used here. The linguistic values from four software metrics related to requirement analysis phase have been considered as model inputs. The performance of the proposed model has been compared with two existing early software fault prediction models.

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Acknowledgments

The authors are thankful to ISM, Dhanbad, for providing necessary help. The authors are also thankful to the reviewers for their valuable comments and suggestions.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Indian School of Mines, Dhanbad, Jharkhand, India

    Subhashis Chatterjee & Bappa Maji

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  1. Subhashis Chatterjee
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  2. Bappa Maji
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Correspondence to Subhashis Chatterjee.

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Communicated by V. Loia.

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Chatterjee, S., Maji, B. A new fuzzy rule based algorithm for estimating software faults in early phase of development. Soft Comput 20, 4023–4035 (2016). https://doi.org/10.1007/s00500-015-1738-x

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  • DOI: https://doi.org/10.1007/s00500-015-1738-x

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