316 ◾ Simple Statistical Methods for Software Engineering
Review Questions
1. What settings will make a Weibull curve behave like a Rayleigh distribution?
2. What is the role played by location parameter?
3. What is the formula connecting the scale shape and scale factor of Weibull curve?
4. Who invented the Weibull distribution?
5. Who applied the Weibull distribution to software projects for the first time?
Exercises
1. e median value of a certain data set is 4.5. e data are suspected to have
standard Weibull distribution. Calculate the scale shape.
2. Plot a Weibull curve with a shape factor of 3 and a scale factor of 15, mak-
ing use of the Excel function WEIBULL.DIST. (Clue: set the cumulative
value = 0.)
3. In software review, defect discovery follows the Weibull model with a shape
of 2 and a scale of 15 days. Find the remaining defects in the code if review is
terminated on day 20.
4. Software productivity data (lines of code [LOC] per person day) is fitted to
Weibull with the following parameters: location = 30, shape = 3, and scale =
50. Find the probability that productivity will go above 70 LOC/person-day.
5. Fit Putnam’s software reliability model to BSPIN data (graphs in Figure 19.8)
and predict the percentage of postrelease defect.
References
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Conference, pp. 463–468, ACM New York, 1998.
4. H. D. Grissino-Mayer, Modeling fire interval data from the American southwest with
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1181, 2008.
6. L. Robert, T. Bailey and R. Dell, Quantifying diameter distributions with the Weibull
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7. W. Weibull, A statistical distribution function of wide applicability, Journal of Applied
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