How Soft Computing Methodology Used For Developing A Model That Can Predict Autonomic Computing Based Software Systems Maintainability
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4. Methodology Used
Soft computing methodology can be used for developing a model that can predict autonomic computing based software systems maintainability according to the opinions of experts of this domain. Soft computing is different from conventional hard computing as in hard computing we require full truth but in soft computing we can solve a problem with vague values and with partial truth . Soft computing techniques are more suitable for real world problems and require very less computational time .Soft computing technologies includes neural networks, fuzzy logic, genetic algorithms etc. Xinghuo and Kaynak  explain briefly about soft computing and its technologies. Fuzzy logic works similar to biological systems as it mimics the human body for problem solving  so it can be used to generate a model for predicting maintainability of autonomic software system after the system is developed.
5. Technology Used
This model will work by taking inputs as the characteristics of autonomic computing that affect maintainability of these systems as input .These inputs are vague values so it would be better to use Fuzzy logic using MATLAB. Using Mamdani FIS (Fuzzy Inference system) in MATLAB a model can be developed.
6. Testing parameters
On the basis of inputs given to the model testing can be done. Inputs of this model would be the characteristics of autonomous system which affect the maintainability of the system. Autonomic software system may not have all the