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The life of software is very short in the environment of perfect competition market. Therefore the software developers have to come up with multiple releases in order to survive in the market. But, enhancing the product and coming up with multiple releases puts a constant pressure on even the best organized engineering organizations. The reason being, up-grading a software application is a complex process. Up-grades of software introduce the risk that the new release will contain a bug, causing the program to fail. Therefore, to capture the effect of faults generated in the software with multiple release, we have developed a multi release software reliability model in this paper. The model uniquely take into account the faults of the current release and the remaining faults of just previous release. The multi release software reliability growth model treats the faults removal rate as a function of testing resources consumed. In addition, most of the debugging process in real life is not perfect. Due to complexity and incomplete understanding of the software, the testing team may not be able to remove/correct the fault perfectly on observation/ detection of a failure and the original fault may remain resulting in the phenomenon known as imperfect debugging, or get replaced by another fault causing error generation. The effects of both type of imperfect debugging during testing phase are incorporated in our proposed multi-release model. The model developed is validated on real data set with software which has been released in the market with new features four times [ABSTRACT FROM AUTHOR]