Abstract
Many software systems have been produced under host-concentrated development environment. However, at present, the software development environment has been changing into distributed development environment because of the progress of network computing technology[1, 4]. Software systems produced in such distributed one tend to increase in size and complexity. Many software reliability growth models (SRGM's) based on a nonhomogeneous Poisson process (NHPP) have been proposed by many researchers. Most of all SRGM's which have been proposed up to the present treat the event of fault-detection in the testing and operational phase of software development as a counting process. However, if the size of the software system is large, the number of faults detected during the testing phase becomes large, and the change of the number of faults which are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing. Therefore, as mentioned above, we can use a model based on a stochastic process with a continuous state space in such distributed development environment. In this paper, we propose an SRGM describing a fault-detection process during the system testing phase of the distributed development environment by applying a mathematical technique of stochastic differential equations of Itô type[5, 6]. We also derive the maximum likelihood estimators of the unknown parameters of the model. Furthermore, we compare our model based on stochastic differential equations with the existing SRGM's in terms of goodness-of-fit for actual data sets.
