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Rayleigh model

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Software Quality Management, B.E. CSE Final Year, Anna University

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• Thank You. It was helpful to understand the Rayleigh model reading through your slides. Only exception was last graph showing the comparison between Weibull and Rayleigh models was hard to understand. Graph could have been more clearer and few inferences could be listed out.

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Rayleigh model

1. 1. 3/2/2011 Software Quality Management Unit – 3  Roy Antony Arnold G Asst. Prof./CSE GRAA• Software reliability models are when it is available to the customers.• The criterion variable under study is the number of  defects in specified time intervals (weeks, months,  etc.), or the time between failures.• Such an estimate is important for two reasons: p – (1) It is an objective statement of the quality of the product – (2) It is a resource planning tool for the software maintenance phase. GRAA 1
2. 2. 3/2/2011• Reliability models can be broadly classified into two categories: and (Conte et al., 1986).• A static model uses other attributes of the project or program modules to estimate the number of defects in the software. General Form : The number of defects (y) is dependant on the attributes (x) of the  product and the process by which it is produced,  plus some  error (e) due to unknowns which inherently exist.• A dynamic model, usually based on statistical distributions, uses the current development defect patterns to estimate end‐ end product reliability.• Dynamic Models are classified in two categories – those that model the entire development process (Rayleigh Model) – those that model the back‐end testing phase (Exponential Model  and Reliability Growth Models) GRAA• The Rayleigh model is a parametric model in the sense that it is based on a specific statistical distribution. It is a dynamic reliability model.• When the parameters of the statistical distribution are estimated based on the data from a software project, projections about the defect rate of the project can be made based on the model. GRAA 2
3. 3. 3/2/2011 • The Rayleigh model is a member of the family of the . • One of its marked characteristics is that the tail of its probability density function approaches zero asymptotically, but never reaches it. • Weibull distributions are used for predicting reliability and  probability distribution • Two standard functions for graphing Weibull Two standard functions for graphing Weibull GRAA• Rayleigh is a special case of the Weibull where the shape parameter (m) equals 2:• The formulas represent a standard distribution.• The total area under the curve is 1. GRAA 3
4. 4. 3/2/2011The defect rate observed during the development process ispositively correlated with the defect rate in the field. (Fig.) Assuming the d f removal effectiveness remains unchanged, then A i h defect l ff i i h d h a higher curve (more defects) during development means a higher defect injection rate and hence a higher field defect rate. GRAA Given the same error injection rate, if more defects are discovered and removed earlier then fewer will remain in later stages and the field quality will be better. – In the fig. the areas under the curves are the same but the curves  peak at varying points. Curves that peak earlier have smaller areas  at the tail, the GA phase. In short, “Do it right the first time.” This means that if each step of the development process is executed properly with minimum errors, the end products quality will be good. GRAA 4
5. 5. 3/2/2011• Most statistical software packages support  Weibull Distributions.• Applications can be developed due to the  clearly defined algorithms for Weibull.• COTS (Commercial Off The Shelf) products  can also be used: GRAA• Accuracy of model estimates.• Input data must be accurate and reliable.• To establish high Predictive Validity, and empirical validity must be established.• The validity of software reliability models . A certain model may work well for a specific organization or development structure but structure, not for others.• No universally good software reliability model exists. GRAA 5
6. 6. 3/2/2011• High‐level Design Review (I0), Low‐level Design Review (I1), Code  Inspection (I2), Unit Test (UT), Component Test (CT), System Test (ST),  and General Availability Phase (GA) and General Availability Phase (GA) GRAA GRAA 6