Unified framework to assess software reliability and determine optimal release time in presence of fault reduction factor, error generation and fault removal efficiency

Reliability of software products can be affected by several factors faced during the testing phase such as the generation of additional faults during the fault removal process, inefficiency or inaccuracy of team in completely removing faults, probability by which faults are removed, and difference between the number of failures and faults removed. These conditions have been termed as error generation, fault removal efficiency (FRE), imperfect debugging parameter, and fault reduction factor (FRF) respectively. In this paper, we have proposed a unified software reliability growth model (SRGM) to assess the impact of these parameters on the reliability and release schedule software. The error generation, imperfect debugging, and FRE parameters have been assumed to be constant while FRF is time-dependent modeled by exponential, Weibull, and delayed s-shaped distribution functions. These models can be represented using a single unified SRGM that reduces the difficulty of model selection. The special cases have been validated on two real-life fault datasets of Tandem computers and radar systems. Performance measures, the goodness of fit, and boxplot analysis show that the model fits the dataset very well. Further, the model that gives the best fit has been used for release planning for determining release and warranty time that minimizes development cost. The paper also analyses the sensitivity of cost parameters, the impact of change in error generation, FRE, FRF, and the reliability constraint on optimal timings. The results are highly encouraging for software managers and engineers and add value to the existing literature.