Software maintenance is an important phase of life cycle process. It is a transforming of a software process after receiver receives and if fault occurs then to modify software products and remove extra bugs. The phase is much important phase which starts with customer end. Therefore predicting the efforts like-cost, size has become one of an important issues which is to be analyzed for effective resource allocation. In view of these issues ,we have developed text mining techniques using machine learning method name BPA(Back Propagation Algorithm).The intended model ratified using ‘browser ‘application pack of android operated system. ROC (Receiver Operating Characteristics) curve is a graphical representation that describes the working of a binary classified system. The performance of model rely on the words count taken for classification which shows best result as the word number increases which describes its accuracy. More the words count more the accuracy.

Software maintenance,Machine learning,BPA,Software Prediction,Neural network

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