Early software reliability analysis using reliability relevant software metrics

The early software reliability analysis is very useful for improving the quality of software at reduced testing effort. Software defect density indicator predicted in the early phases (requirement analysis, design and coding phases) provides an opportunity for the early identification of cost overrun, software development process issues and optimal development strategies. Failure data is not available in the early phases of the software development life cycle (SDLC). However, qualitative values of software metrics are available in the early phases of SDLC. Therefore, in this paper, a model is proposed to predict the software defect density indicator of early phases of SDLC using fuzzy logic and the reliability relevant software metrics of early artifacts. The proposed model is applied on twenty real software projects. It is observed that the requirement analysis phase defect density indicator value is relatively greater than that of the design and coding artifacts. The model is validated with the existing literature. Validation result is satisfactory.

[1]  Neeraj Kumar Goyal,et al.  A Fuzzy Model for Early Software Fault Prediction Using Process Maturity and Software Metrics , 2009 .

[2]  Dilip Kumar Yadav,et al.  A Multistage Model for Defect Prediction of Software Development Life Cycle Using Fuzzy Logic , 2013, SocProS.

[3]  Shunzhi Zhu,et al.  Combining the requirement information for software defect estimation in design time , 2014, Inf. Process. Lett..

[4]  Lotfi A. Zadeh,et al.  Knowledge Representation in Fuzzy Logic , 1996, IEEE Trans. Knowl. Data Eng..

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

[6]  Ashok Deshpande,et al.  Fuzzy Description of Air Quality: A Case Study , 2011, RSKT.

[7]  John D. Musa,et al.  Software reliability - measurement, prediction, application , 1987, McGraw-Hill series in software engineering and technology.

[8]  Norman E. Fenton,et al.  A Critique of Software Defect Prediction Models , 1999, IEEE Trans. Software Eng..

[9]  Rajib Mall,et al.  A technique for early prediction of software reliability based on design metrics , 2011, Int. J. Syst. Assur. Eng. Manag..

[10]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[11]  James A McCall,et al.  Software Reliability, Measurement, and Testing Software Reliability and Test Integration , 1992 .

[12]  William Marsh,et al.  Predicting software defects in varying development lifecycles using Bayesian nets , 2007, Inf. Softw. Technol..

[13]  Kai-Yuan Cai,et al.  A critical review on software reliability modeling , 1991 .

[14]  Richard Torkar,et al.  Software fault prediction metrics: A systematic literature review , 2013, Inf. Softw. Technol..

[15]  Ming Li,et al.  A Ranking of Software Engineering Measures Based on Expert Opinion , 2003, IEEE Trans. Software Eng..

[16]  Banu Diri,et al.  A systematic review of software fault prediction studies , 2009, Expert Syst. Appl..

[17]  Cagatay Catal,et al.  Software fault prediction: A literature review and current trends , 2011, Expert Syst. Appl..

[18]  Stephen G. MacDonell,et al.  What accuracy statistics really measure , 2001, IEE Proc. Softw..

[19]  D. K. Yadav,et al.  Forecasting time-between-failures of software using fuzzy time series approach , 2012, 2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS).

[20]  Hoang Pham,et al.  System Software Reliability (Springer Series in Reliability Engineering) , 2007 .

[21]  Dilip Kumar Yadav,et al.  Early Software Defects Prediction Using Fuzzy Logic , 2012 .

[22]  Carol S. Smidts,et al.  Ranking software engineering measures related to reliability using expert opinion , 2000, Proceedings 11th International Symposium on Software Reliability Engineering. ISSRE 2000.

[23]  Barry W. Boehm,et al.  Bayesian Analysis of Empirical Software Engineering Cost Models , 1999, IEEE Trans. Software Eng..

[24]  Hoang Pham,et al.  System Software Reliability , 1999 .

[25]  Li Juelong,et al.  A new model for software defect prediction using Particle Swarm Optimization and support vector machine , 2013, 2013 25th Chinese Control and Decision Conference (CCDC).

[26]  Hoang Pham,et al.  An analysis of factors affecting software reliability , 2000, J. Syst. Softw..

[27]  William Marsh,et al.  On the effectiveness of early life cycle defect prediction with Bayesian Nets , 2008, Empirical Software Engineering.

[28]  William M. Evanco,et al.  Projecting Software Defects From Analyzing Ada Designs , 1992, IEEE Trans. Software Eng..

[29]  L. A. Zedeh Knowledge representation in fuzzy logic , 1989 .

[30]  Reda Alhajj,et al.  A clustering algorithm with genetically optimized membership functions for fuzzy association rules mining , 2003, The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03..

[31]  Olcay Taner Yildiz,et al.  Software defect prediction using Bayesian networks , 2012, Empirical Software Engineering.

[32]  Rajib Mall,et al.  An approach for early prediction of software reliability , 2010, SOEN.

[33]  Carol-Sophie Smidts,et al.  Software reliability modeling: an approach to early reliability prediction , 1998 .

[34]  Tsutomu Ishida,et al.  Metrics and Models in Software Quality Engineering , 1995 .

[35]  M.A. Friedman,et al.  Reliability techniques for combined hardware/software systems , 1992, Annual Reliability and Maintainability Symposium 1992 Proceedings.