Optimal Release Time Estimation of Software System using Box-Cox Transformation and Neural Network

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). KeywordsSoftware cost model, Optimal software release time, Software reliability, Artificial neural network, Data transformation, Long-term prediction, Fault count data, Empirical validation.

[1]  M. Bartlett.  The Square Root Transformation in Analysis of Variance , 1936 .

[2]  Yiu-Wing Leung,et al.  Optimum software release time with a given cost budget , 1992, J. Syst. Softw..

[3]  Bev Littlewood,et al.  Evaluation of competing software reliability predictions , 1986, IEEE Transactions on Software Engineering.

[4]  Amrit L. Goel,et al.  Software Reliability Models: Assumptions, Limitations, and Applicability , 1985, IEEE Transactions on Software Engineering.

[5]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[6]  Hoang Pham,et al.  A Software Cost Model with Warranty and Risk Costs , 1999, IEEE Trans. Computers.

[7]  S. K. Singal,et al.  Software Application for Data Driven Prediction Models for Intermittent Streamflow for Narmada River Basin , 2015 .

[8]  Tadashi Dohi,et al.  Prediction Interval of Cumulative Number of Software Faults Using Multilayer Perceptron , 2016 .

[9]  Shigeru Yamada,et al.  S-Shaped Reliability Growth Modeling for Software Error Detection , 1983, IEEE Transactions on Reliability.

[10]  Tadashi Dohi,et al.  Software reliability growth models with normal failure time distributions , 2013, Reliab. Eng. Syst. Saf..

[11]  Siddhartha R. Dalal,et al.  When to Stop Testing for Large Software Systems with Changing Code , 1994, IEEE Trans. Software Eng..

[12]  Dipak K. Dey,et al.  A Bayesian Approach Using Nonhomogeneous Poisson Process for Software Reliability Models , 2007 .

[13]  Tadashi Dohi,et al.  SRATS: Software reliability assessment tool on spreadsheet (Experience report) , 2013, 2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE).

[14]  Tadashi Dohi,et al.  Software Reliability Modeling and Evaluation under Incomplete Knowledge on Fault Distribution , 2013, 2013 IEEE 7th International Conference on Software Security and Reliability.

[15]  F. J. Anscombe,et al.  THE TRANSFORMATION OF POISSON, BINOMIAL AND NEGATIVE-BINOMIAL DATA , 1948 .

[16]  Bahar Sennaroglu,et al.  Performance comparison of box-cox transformation and weighted variance methods with weibull distribution , 2015 .

[17]  Tadashi Dohi,et al.  A Neuro-Based Software Fault Prediction with Box-Cox Power Transformation , 2017 .

[18]  Tadashi Dohi,et al.  Optimal software release scheduling based on artificial neural networks , 1999, Ann. Softw. Eng..

[19]  Swapna S. Gokhale,et al.  Log-logistic software reliability growth model , 1998, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No.98EX231).

[20]  Bev Littlewood.  Rationale for a Modified Duane Model , 1984, IEEE Transactions on Reliability.

[21]  Jongmoon Baik,et al.  On the Long-Term Predictive Capability of Data-Driven Software Reliability Model: An Empirical Evaluation , 2014, 2014 IEEE 25th International Symposium on Software Reliability Engineering.

[22]  Amrit L. Goel,et al.  Optimum release time for software systems based on reliability and cost criteria , 1984, J. Syst. Softw..

[23]  Amrit L. Goel,et al.  Time-Dependent Error-Detection Rate Model for Software Reliability and Other Performance Measures , 1979, IEEE Transactions on Reliability.

[24]  Hoang Pham,et al.  A software cost model with error removal times and risk costs , 1998, Int. J. Syst. Sci..

[25]  J. Tukey.  On the Comparative Anatomy of Transformations , 1957 .

[26]  Tadashi Dohi,et al.  Software Reliability Assessment via Non-Parametric Maximum Likelihood Estimation , 2015, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[27]  Hoang Pham,et al.  Software reliability and cost models: Perspectives, comparison, and practice , 2003, Eur. J. Oper. Res..

[28]  Tadashi Dohi,et al.  Gompertz software reliability model: Estimation algorithm and empirical validation , 2009, J. Syst. Softw..

[29]  Hoang Pham.  Software Reliability , 1999 .

[30]  Tadashi Dohi,et al.  Optimal stopping time of software system test via artificial neural network with fault count data , 2018 .

[31]  Tadashi Dohi,et al.  Wavelet Shrinkage Estimation for Non-Homogeneous Poisson Process Based Software Reliability Models , 2013, IEEE Transactions on Reliability.

[32]  Mitsuru Ohba,et al.  Inflection S-Shaped Software Reliability Growth Model , 1984 .

[33]  Kai-Yuan Cai,et al.  Software Defect and Operational Profile Modeling , 1998, The Kluwer International Series in Software Engineering.

[34]  Michael R. Lyu,et al.  Handbook of software reliability engineering , 1996 .

[35]  Tadashi Dohi,et al.  Optimal Software Release Decision Based on Nonparametric Inference Approach , 2016 .

[36]  M. Fisz.  The limiting distribution of a function of two independent random variables and its statistical application , 1955 .