Early Warning System in the Improvement of Software Quality |
Author(s): |
| Riddhi Mehta , Nirma University; Asha Faldu , Nirma University; Meera Bhadania, Nirma University |
Keywords: |
| Fuzzification, linguistic variable, Fuzzy Inference System |
Abstract |
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Basic reason behind failure in software development projects is delay in correction of problems even if they are detected within reasonable time. This raises need of a concrete system which can warn against such potential risks. This paper highlights such early warning system based on fuzzy logic using integrated set of software matric. Such system helps accessing risks associated with being schedule. This handles incomplete, inaccurate and non-précised information, and resolves conflicts in an uncertain environment. Process, product, and organizational metrics are collected or computed based on solid software models. The intelligent risk assessment process consists of the following steps: fuzzification of software metrics, rule firing, derivation and aggregation of resulted risk fuzzy sets, and defuzzification of linguistic risk variables. |
Other Details |
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Paper ID: IJSRDV2I2154 Published in: Volume : 2, Issue : 2 Publication Date: 01/05/2014 Page(s): 245-248 |
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