International Journal of Mathematical, Engineering and Management Sciences Vol. 3, No. 2, 177–194, 2018 https://dx.doi.org/10.33889/IJMEMS.2018.3.2-014 177 Optimal Release Time Estimation of Software System using Box-Cox Transformation and Neural Network Momotaz Begum, Tadashi Dohi Department of Information Engineering Hiroshima University 1-4-1 Kagamiyama, Higashi-Hiroshima 739–8527, Japan * Corresponding author: momotaz.2k3@gmail.com (Received June 27, 2017; Accepted September 27, 2017) Abstract The determination of the software release time for a new software product is the most critical issue for designing and controlling software development processes. This paper presents an innovative technique to predict the optimal software release time using a neural network. In our approach, a three-layer perceptron neural network with multiple outputs is used, where the underlying software fault count data are transformed into the Gaussian data by means of the well-known Box-Cox power transformation. Then the prediction of the optimal software release time, which minimizes the expected software cost, is carried out using the neural network. Numerical examples with four actual software fault count data sets are presented, where we compare our approach with conventional Non-Homogeneous Poisson Process (NHPP) -based Software Reliability Growth Models (SRGMs). Keywords- Software cost model, Optimal software release time, Software reliability, Artificial neural network, Data transformation, Long-term prediction, Fault count data, Empirical validation. 1. Introduction Software testing is an important feature in software development processes and plays an imperative role in defining the quality of software. Moreover, due to huge competitions in the market, software can be seldom survived during the long lifetime due to the competitions and always faces the version up. At the same time, newly added feature in software increases the complexity, which leads to the software faults if not evaluated appropriately. On the other hand, the main concern in software process management by practitioners is to determine when to stop software testing and release the software to the market or users. The determination of the optimal timing to stop software testing is called the optimal software release problem, which is directly related to software testing costs. The total testing cost is reduced successfully if the volume of software test work is less. The debugging cost is more significant in the operational phase than that in the testing phase after releasing software. On the contrary, the higher the software reliability desired, the longer testing period, which further accumulates higher testing cost. Hence, it is important to find as appropriate software release time taking account of the expected software cost. Many authors have discussed in the past on when to stop software testing and to release it for use. The recent trend shows that the quantitative software reliability assessment processes and the efficient software testing methodologies are becoming a firm prerequisite for software developers. Towards achieving the prerequisite, a great number of SRGMs have been developed in the literature (see Goel and Okumoto,1979; Yamada et al., 1983; Ohba, 1984; Littlewood, 1984; Goel, 1985; Abdel-Ghaly et al., 1986; Lyu, 1996; Achcar et al., 1998; Cai, 1998; Gokhale and Trivedi, 1998; Pham, 2000; Ohishi et al., 2009; Okamura et al., 2013).