Software Reliability Growth Model with testing effort using learning function

Software Reliability Growth Models have been proposed in the literature to measure the quality of software and to release the software at minimum cost. Testing is an important part to find out faults during Software Development Life Cycle of integrated software. Testing can be defined as the execution of a program to find a fault which might have been introduced during the testing time under different assumptions. The testing team may not be able to remove the fault perfectly on the detection of the failure and the original fault may remain or get replaced by another fault. While the former phenomenon is known as imperfect fault removal, the latter is called error generation. In this paper, we have proposed a new SRGM with two types of imperfect debugging with testing effort using learning function reflecting the expertise gained by testing team depending on its complexity, the skills of the debugging team, the available manpower and the software development environment and it is estimated and compared other existing models on real time data sets. These estimation result shows compare performance and application of different SRGM with testing effort.