  Maintenance is the last and the most critical phase of the software
development life cycle. It involves debugging of errors and different types of
enhancements which are requested by the user. Software reliability regarding
maintenance is the most crucial part as it depends upon the time and cost to
correct the errors and make enchantements. It is often felt that software
errors or correction takes time to be removed. The maintenance time depends
upon the nature of the occurred errors and requested enhancements. In this
research work we predict the software reliability in terms of time taken to
maintain the errors and enhancements. Artificial Neural Network is used to
analyze and predict the software reliability of the maintenance phase. At the
end statistical results and proposed neural network results are also compared
to make sure that forecasted results are equal to the output results. These
results are compared to show that the ANN can understand the relationship
between data in a better way. This research work also shows how much it is
difficult to understand the nature of maintenance data.
