Discrete software reliability measurement has a proper characteristic for describing a software reliability growth process which depends on a unit of the software fault-detection period, such as the number of test run...Discrete software reliability measurement has a proper characteristic for describing a software reliability growth process which depends on a unit of the software fault-detection period, such as the number of test runs, the number of executed test cases. This paper discusses discrete software reliability measurement based on a discretized nonhomogeneous Poisson process (NHPP) model. Especially, we use a bootstrapping method in our discrete software reliability measurement for discussing the statistical inference on parameters and software reliability assessment measures of our model. Finally we show numerical examples of interval estimations based on our bootstrapping method for the several software reliability assessment measures by using actual data.展开更多
Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped...Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions（TEFs）, i.e.,delayed S-shaped TEF（DS-TEF） and inflected S-shaped TEF（IS-TEF）, are proposed. Then these two TEFs are incorporated into various types（exponential-type, delayed S-shaped and inflected S-shaped） of non-homogeneous Poisson process（NHPP）SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs.The experimental results show that：（i） the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs;（ii） incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs;（iii） the inflected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.展开更多
As one of the most important indexes to evaluate the quality of software, software reliability experiences an increasing development in recent years. We investigate a software reliability growth model(SRGM). The appli...As one of the most important indexes to evaluate the quality of software, software reliability experiences an increasing development in recent years. We investigate a software reliability growth model(SRGM). The application of this model is to predict the occurrence of the software faults based on the non-homogeneous Poisson process(NHPP). Unlike the independent assumptions in other models, we consider fault dependency. The testing faults are divided into three classes in this model: leading faults, first-step dependent faults and second-step dependent faults. The leading faults occurring independently follow an NHPP, while the first-step dependent faults only become detectable after the related leading faults are detected. The second-step dependent faults can only be detected after the related first-step dependent faults are detected. Then, the combined model is built on the basis of the three sub-processes. Finally, an illustration based on real dataset is presented to verify the proposed model.展开更多
To ensure the safe operation of any software controlled critical systems,quality factors like reliability and safety are given utmost importance.In this paper,we have chosen to analyze the impact of logic error that i...To ensure the safe operation of any software controlled critical systems,quality factors like reliability and safety are given utmost importance.In this paper,we have chosen to analyze the impact of logic error that is one of the contributors to the above factors.In view of this,we propose a novel framework based on a data driven approach known as software failure estimation with logic error(SFELE).Here,the probabilistic nature of software error is explored by observing the operation of a safety critical system by injecting logic fault.The occurrence of error,its propagations and transformations are analyzed from its inception to end of its execution cycle through the hidden Markov model(HMM)technique.We found that the proposed framework SFELE supports in labeling and quantifying the behavioral properties of selected errors in a safety critical system while traversing across its system components in addition to reliability estimation of the system.Our attempt at the design level can help the design engineers to improve their system quality in a costeffective manner.展开更多
In this paper, an improved NHPP model is proposed by replacing constant fault removal time with time-varying fault removal delay in NHPP model, proposed by Daniel R Jeske. In our model, a time-dependent delay function...In this paper, an improved NHPP model is proposed by replacing constant fault removal time with time-varying fault removal delay in NHPP model, proposed by Daniel R Jeske. In our model, a time-dependent delay function is established to fit the fault removal process. By using two sets of practical data, the descriptive and predictive abilities of the improved NHPP model are compared with those of the NHPP model, G-O model, and delayed S-shape model. The results show that the improved model can fit and predict the data better.展开更多
Electromechanical product's reliability is affected by uncertainty as well as performance degeneration during its life cycle.The present reliability and performance integrating modeling methods have obvious defici...Electromechanical product's reliability is affected by uncertainty as well as performance degeneration during its life cycle.The present reliability and performance integrating modeling methods have obvious deficiencies in long period reliability analysis and assessment when applied to such system.A novel integrating modeling method based on physics of failure(PoF)and a simulation algorithm that considers uncertainty and degeneration are proposed in this paper to compute maintenance free operation period or maintenance free operation period survivability which is used to assess long period reliability of system.Furthermore,the concept design of this kind of software based on the above theory is also introduced.A case study of servo valve demonstrates the feasibility of the method and usability of the software in this research.展开更多
文摘Discrete software reliability measurement has a proper characteristic for describing a software reliability growth process which depends on a unit of the software fault-detection period, such as the number of test runs, the number of executed test cases. This paper discusses discrete software reliability measurement based on a discretized nonhomogeneous Poisson process (NHPP) model. Especially, we use a bootstrapping method in our discrete software reliability measurement for discussing the statistical inference on parameters and software reliability assessment measures of our model. Finally we show numerical examples of interval estimations based on our bootstrapping method for the several software reliability assessment measures by using actual data.
基金supported by the Pre-research Foundation of CPLA General Equipment Department
文摘Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions（TEFs）, i.e.,delayed S-shaped TEF（DS-TEF） and inflected S-shaped TEF（IS-TEF）, are proposed. Then these two TEFs are incorporated into various types（exponential-type, delayed S-shaped and inflected S-shaped） of non-homogeneous Poisson process（NHPP）SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs.The experimental results show that：（i） the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs;（ii） incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs;（iii） the inflected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.
基金the National Natural Science Foundation of China(No.71671016)the School Fund of Beijing Information Science&Technology University(No.1935004)
文摘As one of the most important indexes to evaluate the quality of software, software reliability experiences an increasing development in recent years. We investigate a software reliability growth model(SRGM). The application of this model is to predict the occurrence of the software faults based on the non-homogeneous Poisson process(NHPP). Unlike the independent assumptions in other models, we consider fault dependency. The testing faults are divided into three classes in this model: leading faults, first-step dependent faults and second-step dependent faults. The leading faults occurring independently follow an NHPP, while the first-step dependent faults only become detectable after the related leading faults are detected. The second-step dependent faults can only be detected after the related first-step dependent faults are detected. Then, the combined model is built on the basis of the three sub-processes. Finally, an illustration based on real dataset is presented to verify the proposed model.
文摘To ensure the safe operation of any software controlled critical systems,quality factors like reliability and safety are given utmost importance.In this paper,we have chosen to analyze the impact of logic error that is one of the contributors to the above factors.In view of this,we propose a novel framework based on a data driven approach known as software failure estimation with logic error(SFELE).Here,the probabilistic nature of software error is explored by observing the operation of a safety critical system by injecting logic fault.The occurrence of error,its propagations and transformations are analyzed from its inception to end of its execution cycle through the hidden Markov model(HMM)technique.We found that the proposed framework SFELE supports in labeling and quantifying the behavioral properties of selected errors in a safety critical system while traversing across its system components in addition to reliability estimation of the system.Our attempt at the design level can help the design engineers to improve their system quality in a costeffective manner.
基金the National High Technology Research and Development Program of China (863 Program) under Grant No. 2006AA01Z173.
文摘In this paper, an improved NHPP model is proposed by replacing constant fault removal time with time-varying fault removal delay in NHPP model, proposed by Daniel R Jeske. In our model, a time-dependent delay function is established to fit the fault removal process. By using two sets of practical data, the descriptive and predictive abilities of the improved NHPP model are compared with those of the NHPP model, G-O model, and delayed S-shape model. The results show that the improved model can fit and predict the data better.
基金National Natural Science Foundation of China(No.61304218)Beijing Natural Science Foundation,China(No.3153027)
文摘Electromechanical product's reliability is affected by uncertainty as well as performance degeneration during its life cycle.The present reliability and performance integrating modeling methods have obvious deficiencies in long period reliability analysis and assessment when applied to such system.A novel integrating modeling method based on physics of failure(PoF)and a simulation algorithm that considers uncertainty and degeneration are proposed in this paper to compute maintenance free operation period or maintenance free operation period survivability which is used to assess long period reliability of system.Furthermore,the concept design of this kind of software based on the above theory is also introduced.A case study of servo valve demonstrates the feasibility of the method and usability of the software in this research.
