SOFTWARE RELIABILITY GROWTH MODELLING FOR ERRORS OF DIFFERENT SEVERITY USING CHANGE POINT

Abstract

During the last two decades many researchers have analyzed the reliability growth of software during the testing and operational phases and proposed the mathematical models to estimate and predict the reliability measures. During the software testing on the detection of a failure the fault that has caused the failure is isolated and removed. Most of the existing research in this area considers that similar testing efforts and strategy are required on each debugging effort. However this may not be true in practice. Different faults may require different amount of testing efforts and testing strategy for their removal. In software reliability modeling in order to incorporate this phenomenon faults are classified into different categories as simple, hard and/or complex faults. This categorization is also extended to n-types of faults. Some of the existing research incorporates this phenomenon considering that the fault removal rate is different for different types of faults and remains constant during the overall period of testing. However this assumption may not apply in general testing environment in practice. It is a common observation that as the testing progresses the fault detection and/or removal rate changes. This change can be due to a number of reasons. The changing testing environment, testing strategy, skill, motivation and constitution of the testing and debugging personnel etc. are some of the major reasons behind this change. In this paper we have formulated the model for the software system developed for safety critical application under a specific testing environment. The model is validated on real life data sets.