Software Reliability Growth Modeling with Burr Type XII using Fuzzy Logic

Software reliability modeling is used to detect and correct software errors. The accurate reliability prediction is the main challenges of software engineers. It is also an important task to develop software with high reliability. The precise quantification of parameter is not always possible, nor is it always necessary. When the values of parameters and variables cannot be precisely specified, they are said to be uncertain or fuzzy. To make the model more reliable, developer need to introduce some degree of uncertainty in the models. In this paper we discuss software reliability growth model considering Burr Type-XII testing effort function and fuzzy logic. Further, we consider the certain uncertainty level that involves in the testing-effort (TE) consumption and reliability parameters. We estimate the TE and reliability parameters of software reliability growth model (SRGM) by using method of least square and maximum likelihood techniques. Several reliability measures are calculated at different level of uncertainty. We compare the results with existing models from the literature. We also calculate cost of software under fuzzy environment and the results are compared with other published work.