Bayesian updating of optimal release time for software systems

Abstract

In this paper, a Bayesian method dealing with software reliability growth with consideration of the learning effect is proposed to determine an optimal release time for software systems with regard to the testing cost and experts' prior judgments. Such an approach is able to devise an appropriate software-debugging scheme which has the best arrangement of available resources and personnel with a minimal software testing cost when lacking sufficient information for decision making. Past research on software reliability emphasized the estimation of the number of cumulative software errors or the software reliability with respect to a specific time period, yet it neglected the determination of software release time with consideration of the software testing cost, meaning that existing approaches are not entirely practical. Accordingly, the proposed method is concerned with the evaluation of the software testing cost incurred during the testing period based on experts' prior judgments and the software testing data collected within a given duration, and is thus characterized by its practicality as well as meaningfulness with consideration of the learning effect. Finally, a numerical example is given to verify the effectiveness of the proposed approach, and sensitivity and risk analyses are performed on this example.

Multi‐upgradation software reliability growth model with dependency of faults under change point and imperfect debugging

“…One can always get a new version of the software with improved functionality and increased ease of use. [37][38][39] Release of software without proper debugging may cause failure and dissatisfaction to the customer.…”

A general modeling and analysis framework for software fault detection and correction process

“…One of the most significant applications of software reliability models is the determination of software release time. Some cost models have been proposed in previous works . Considering with FCP, the cost model can be written as where and are the expected cost of finding and removing a fault during test phase, since both of the works are carried on separately.…”

Economic Impact of Software Patching and Optimal Release Scheduling

“…As a result of learning curve and the economies of scale a larger market share can lead to reduce cost per product. Considering such scenarios the cost of late release can be considered as a convex function of release time and thus here, including the ideology of researchers like: Dalal and Mallows, Singpurwalla and Wilson, McDaid and Wilson and Chiu et al, the market opportunity cost has been considered as a convex function of release time. And so, this cost component is assumed to be monotonically increasing, twice continuously differentiable convex function of τ .…”