  Software project estimation is crucial aspect in delivering software on time
and on budget. Software size is an important metric in determining the effort,
cost, and productivity. Today, source lines of code and function point are the
most used sizing metrics. Backfiring is a well-known technique for converting
between function points and source lines of code. However when backfiring is
used, there is a high margin of error. This study introduces a method to
improve the accuracy of backfiring. Intelligent systems have been used in
software prediction models to improve performance over traditional techniques.
For this reason, a hybrid Neuro-Fuzzy is used because it takes advantages of
the neural networks learning and fuzzy logic human-like reasoning. This paper
describes an improved backfiring technique which uses Neuro-Fuzzy and compares
the new method against the default conversion ratios currently used by software
practitioners.
