Software Reliability Growth Model for Imperfect Debugging Process Considering Testing-Effort and Testing Coverage
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摘要
Because of the inevitable debugging lag,imperfect debugging process is used to replace perfect debugging process in the analysis of software reliability growth model.Considering neither testing-effort nor testing coverage can describe software reliability for imperfect debugging completely,by hybridizing testing-effort with testing coverage under imperfect debugging,this paper proposes a new model named GMW-LO-ID.Under the assumption that the number of faults is proportional to the current number of detected faults,this model combines generalized modified Weibull(GMW)testing-effort function with logistic(LO)testing coverage function,and inherits GMW's amazing flexibility and LO's high fitting precision.Furthermore,the fitting accuracy and predictive power are verified by two series of experiments and we can draw a conclusion that our model fits the actual failure data better and predicts the software future behavior better than other ten traditional models,which only consider one or two points of testing-effort,testing coverage and imperfect debugging.
Because of the inevitable debugging lag,imperfect debugging process is used to replace perfect debugging process in the analysis of software reliability growth model.Considering neither testing-effort nor testing coverage can describe software reliability for imperfect debugging completely,by hybridizing testing-effort with testing coverage under imperfect debugging,this paper proposes a new model named GMW-LO-ID.Under the assumption that the number of faults is proportional to the current number of detected faults,this model combines generalized modified Weibull(GMW)testing-effort function with logistic(LO)testing coverage function,and inherits GMW's amazing flexibility and LO's high fitting precision.Furthermore,the fitting accuracy and predictive power are verified by two series of experiments and we can draw a conclusion that our model fits the actual failure data better and predicts the software future behavior better than other ten traditional models,which only consider one or two points of testing-effort,testing coverage and imperfect debugging.
Because of the inevitable debugging lag,imperfect debugging process is used to replace perfect debugging process in the analysis of software reliability growth model.Considering neither testing-effort nor testing coverage can describe software reliability for imperfect debugging completely,by hybridizing testing-effort with testing coverage under imperfect debugging,this paper proposes a new model named GMW-LO-ID.Under the assumption that the number of faults is proportional to the current number of detected faults,this model combines generalized modified Weibull(GMW)testing-effort function with logistic(LO)testing coverage function,and inherits GMW's amazing flexibility and LO's high fitting precision.Furthermore,the fitting accuracy and predictive power are verified by two series of experiments and we can draw a conclusion that our model fits the actual failure data better and predicts the software future behavior better than other ten traditional models,which only consider one or two points of testing-effort,testing coverage and imperfect debugging.
引文
[1]PENG R,LI Y F,ZHANG W J,et al.Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction[J].Reliability Engineering and System Safety,2014,126:37-43.
[2]YANG X,FANG Z,TAO L.Life evaluation GERTnetwork model of equipment reliability test[J].Journal of Nanjing University of Aeronautics and Astronautics,2016,48(5):689-695.(in Chinese)
[3]KAPUR P K,GOSWAMI D N,BARDHAN A,et al.Flexible software reliability growth model with testing effort dependent learning process[J].Applied Mathematical Modelling,2015,32(7):1298-1307.
[4]HUANG C Y,KUO S Y.Analysis of incorporating logistic testing-effort function into software reliability modeling[J].IEEE Transactions on Reliability,2002,51(3):261-270.
[5]ZHANG N,CUI G,LIU H W.A finite queuing model with generalized modified Weibull testing effort for software reliability[C]//Proceedings of International Conference on Computer Science and Network Technology(ICCSNT 2011).Harbin,China:IEEE,2011:401-406.
[6]LIN C T.Enhancing the accuracy of software reliability prediction through quantifying the effect of test phase transition[J].Applied Mathematics and Computation,2012,219(5):2478-2492.
[7]PACHAURI B,KUMAR A,DHAR J.Software reliability growth modeling with dynamic faults and release time optimization using GA and MAUT[J].Applied Mathematics and Computation,2014,242:500-509.
[8]CAI X,LYU M R.Software reliability modeling with test coverage:Experimentation and measurement with a fault-tolerant software project[C]//Proceedings of the18th IEEE International Symposium on Software Reliability.Trollhattan,Sweden:IEEE,2007:17-26.
[9]LI H F,LI Q Y,LU M Y.Software reliability modeling with logistic test coverage function[J].Journal of Computer Research and Development,2011,48(2):232-240.(in Chinese)
[10]LI H F,WANG S Q,LIU C,et al.Software reliability model considering both testing effort and testing coverage[J].Journal of Software,2013,24(4):749-760.(in Chinese)
[11]CHATTERJEE S,SINGH J B.A NHPP based software reliability model and optimal release policy with logistic-exponential test coverage under imperfect debugging[J].International Journal of System Assurance Engineering and Management,2014,5(3):399-406.
[12]ZHANG C,CUI G C,LIU H W,et al.A unified and flexible framework of imperfect debugging dependent SRGMs with testing-effort[J].Journal of Multimedia,2014,9(2):310-317.
[13]WANG J Y,WU Z B,SHU Y J,et al.An imperfect software debugging model considering log-logistic distribution fault content function[J].Journal of Systems and Software,2015,100:167-181.
[14]HUANG C Y,KU S Y,LYU M R.An assessment of testing-effort dependent software reliability growth models[J].IEEE Transactions on Reliability,2007,56(2):198-211.
[15]SAGAR B B,SAKET R K,SINGH C G.Exponentiated Weibull distribution approach based inflection S-shaped software reliability growth model[J].AINShams Engineering Journal,2016,7(3):973-991.
[16]JIN C,JIN S W.Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization[J].Applied Soft Computing,2016,40(C):283-291.
[2]YANG X,FANG Z,TAO L.Life evaluation GERTnetwork model of equipment reliability test[J].Journal of Nanjing University of Aeronautics and Astronautics,2016,48(5):689-695.(in Chinese)
[3]KAPUR P K,GOSWAMI D N,BARDHAN A,et al.Flexible software reliability growth model with testing effort dependent learning process[J].Applied Mathematical Modelling,2015,32(7):1298-1307.
[4]HUANG C Y,KUO S Y.Analysis of incorporating logistic testing-effort function into software reliability modeling[J].IEEE Transactions on Reliability,2002,51(3):261-270.
[5]ZHANG N,CUI G,LIU H W.A finite queuing model with generalized modified Weibull testing effort for software reliability[C]//Proceedings of International Conference on Computer Science and Network Technology(ICCSNT 2011).Harbin,China:IEEE,2011:401-406.
[6]LIN C T.Enhancing the accuracy of software reliability prediction through quantifying the effect of test phase transition[J].Applied Mathematics and Computation,2012,219(5):2478-2492.
[7]PACHAURI B,KUMAR A,DHAR J.Software reliability growth modeling with dynamic faults and release time optimization using GA and MAUT[J].Applied Mathematics and Computation,2014,242:500-509.
[8]CAI X,LYU M R.Software reliability modeling with test coverage:Experimentation and measurement with a fault-tolerant software project[C]//Proceedings of the18th IEEE International Symposium on Software Reliability.Trollhattan,Sweden:IEEE,2007:17-26.
[9]LI H F,LI Q Y,LU M Y.Software reliability modeling with logistic test coverage function[J].Journal of Computer Research and Development,2011,48(2):232-240.(in Chinese)
[10]LI H F,WANG S Q,LIU C,et al.Software reliability model considering both testing effort and testing coverage[J].Journal of Software,2013,24(4):749-760.(in Chinese)
[11]CHATTERJEE S,SINGH J B.A NHPP based software reliability model and optimal release policy with logistic-exponential test coverage under imperfect debugging[J].International Journal of System Assurance Engineering and Management,2014,5(3):399-406.
[12]ZHANG C,CUI G C,LIU H W,et al.A unified and flexible framework of imperfect debugging dependent SRGMs with testing-effort[J].Journal of Multimedia,2014,9(2):310-317.
[13]WANG J Y,WU Z B,SHU Y J,et al.An imperfect software debugging model considering log-logistic distribution fault content function[J].Journal of Systems and Software,2015,100:167-181.
[14]HUANG C Y,KU S Y,LYU M R.An assessment of testing-effort dependent software reliability growth models[J].IEEE Transactions on Reliability,2007,56(2):198-211.
[15]SAGAR B B,SAKET R K,SINGH C G.Exponentiated Weibull distribution approach based inflection S-shaped software reliability growth model[J].AINShams Engineering Journal,2016,7(3):973-991.
[16]JIN C,JIN S W.Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization[J].Applied Soft Computing,2016,40(C):283-291.