Comparing between Maximum Likelihood Estimator and Non-linear Regression Estimation Procedures for NHPP Software Reliability Growth Modelling

Software Reliability Growth Models (SRGMs) have been used by engineers and managers for tracking and managing the reliability change of software to ensure required standard of quality is achieved before the software is released to the customer. SRGMs can be used during the project to help make testing resource allocation decisions and/ or it can be used after the testing phase to determine the latent faults prediction to assess the maturity of software artifact. A number of SRGMs have been proposed and to apply a given reliability model, defect inflow data is fitted to model equations. Two of the widely known and recommended techniques for parameter estimation are maximum likelihood and method of least squares. In this paper we compare between the two estimation procedures for their applicability in context of NHPP SRGMs. We also highlight a couple of practical considerations, reliability practitioners must be aware of when applying SRGMs.

[1]  Bijamma Thomas,et al.  Software reliability growth models , 2014 .

[2]  Arne Henningsen,et al.  maxLik: A package for maximum likelihood estimation in R , 2011, Comput. Stat..

[3]  Miroslaw Staron,et al.  Predicting weekly defect inflow in large software projects based on project planning and test status , 2008, Inf. Softw. Technol..

[4]  I. Secretary,et al.  IEEE Std 1633TM-2008, IEEE Recommended Practice on Software Reliability , 2009 .

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

[6]  Michael R. Lyu.  Software Reliability Engineering: A Roadmap , 2007, Future of Software Engineering (FOSE '07).

[7]  John E. Gaffney,et al.  On predicting software reliability , 1989, [1989] Proceedings of the Thirteenth Annual International Computer Software & Applications Conference.

[8]  K Okumoto,et al.  TIME-DEPENDENT ERROR-DETECTION RATE MODEL FOR SOFTWARE AND OTHER PERFORMANCE MEASURES , 1979 .

[9]  Magne Jørgensen,et al.  A comparison of software project overruns - flexible versus sequential development models , 2005, IEEE Transactions on Software Engineering.

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

[11]  Taghi M. Khoshgoftaar,et al.  Software reliability model selection: a cast study , 1991, Proceedings. 1991 International Symposium on Software Reliability Engineering.

[12]  Stephen H. Kan,et al.  Metrics and Models in Software Quality Engineering , 1994, SOEN.

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

[14]  Michael R. Lyu,et al.  What is software reliability? , 1994, Proceedings of COMPASS'94 - 1994 IEEE 9th Annual Conference on Computer Assurance.

[15]  Franklin A. Graybill,et al.  Introduction to the Theory of Statistics, 3rd ed. , 1974 .

[16]  M. Camuffo,et al.  Automatic software test generation , 1990 .

[17]  Tarak Goradia.  Dynamic impact analysis: a cost-effective technique to enforce error-propagation , 1993, ISSTA '93.

[18]  M. Xie,et al.  Software Reliability Models - Past, Present and Future , 2000 .

[19]  Tharam S. Dillon,et al.  Software Complexity and Its Impact on Software Reliability , 1988, IEEE Trans. Software Eng..

[20]  N. Nakagawa,et al.  Method to estimate parameter values in software prediction models , 1991 .

[21]  Xiaolin Teng,et al.  Considering fault removal efficiency in software reliability assessment , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[22]  Michiel van Genuchten,et al.  Using Software Reliability Growth Models in Practice , 2007, IEEE Software.

[23]  Hoang Pham,et al.  Quasi-Renewal Time-Delay Fault-Removal Consideration in Software Reliability Modeling , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[24]  Matthew Zook.  Code/Space: Software and Everyday Life , 2012 .

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

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

[27]  Chin-Yu Huang,et al.  Enhancing and measuring the predictive capabilities of testing-effort dependent software reliability models , 2008, J. Syst. Softw..

[28]  Hoang Pham.  Software Reliability , 1999 .

[29]  J. Wolfowitz,et al.  An Introduction to the Theory of Statistics , 1951, Nature.

[30]  Maurizio Morisio,et al.  A Comparative Analysis of Software Reliability Growth Models using Defects Data of Closed and Open Source Software , 2012, 2012 35th Annual IEEE Software Engineering Workshop.

[31]  J. Wolfowitz,et al.  Introduction to the Theory of Statistics. , 1951 .

[32]  Kapil Sharma,et al.  Selection of Optimal Software Reliability Growth Models Using a Distance Based Approach , 2010, IEEE Transactions on Reliability.

[33]  Michael R. Lyu,et al.  A Unified Scheme of Some Nonhomogenous Poisson Process Models for Software Reliability Estimation , 2003, IEEE Trans. Software Eng..

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

[35]  Catherine Stringfellow,et al.  An Empirical Method for Selecting Software Reliability Growth Models , 2002, Empirical Software Engineering.

[36]  Rakesh Rana,et al.  Evaluating long-term predictive power of standard reliability growth models on automotive systems , 2013, 2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE).