Symmetry (Mar 2022)
Decision Making of Software Release Time at Different Confidence Intervals with Ohba’s Inflection S-Shape Model
Abstract
Software developers need information for deciding the optimal time for software release with improved software reliability. However, it is not easy for them to decide when and how to release newly developed software to the market. For a decision, the reliability and test costs of the software need to be balanced carefully for avoiding unnecessary confusion and users’ complaints. To address this need, related research has been carried out to propose an appropriate tool for such decisions. In many studies, software reliability growth models (SRGMs) were applied using the concept of confidence intervals to estimate the reliability of software. Confidence intervals were calculated on the basis of the assumption of a normal distribution showing the symmetrical occurrence of data with the mean as a center. However, the reliability data of software do not always have such symmetry for assuming the normal distribution. Therefore, it is necessary to propose a method for overcoming the mean value randomness that causes asymmetry in the related data. In previous studies, estimating variance and mean of errors of software was not considered, which led to the unreliable estimation of the confidence intervals of the mean value for decision making. Previous studies also lacked practicability in applications due to statistics from the asymmetrical data distribution. As a result, software developers could not effectively evaluate the possible risk related to the software release time. To improve the estimation, we employ the inflection S-shape model to propose the SRGM on the basis of confidence intervals assumed to come from the normal distribution. The proposed model allows determining the optimal time for software release with the consideration of its potential risk. For efficient determination, the architecture and user interface of the computation system are also proposed.
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