Why It’s Predicted
Two profiles, two purposes
There are two defect profiles predicted in this step, each feeding a different downstream metric.
Profile
Used for
Predicted defects to be discoveredi, any severity
Used to predict MTTF
Predicted critical defectsi
Used to predict MTTCF, which then predicts reliability and availability
Inputs
What the defect profile needs
#
Input
Tab
1
Predict size
Required inputs, under the Survey tab
2
Predict defect density
All Survey tabs except Failure Modes
3
Fraction of defects affecting availability, installed sites, release schedule
Required inputs, under the Survey tab
4
Growth rate and growth period
Predicted from installed sites on Required Inputs
5
Months between major releases
Results only display for months until the next major release, since new code resets reliability growth
Go to the Required Inputs page and enter the following:
- Typical fraction of defects found in operation that affect availability. Determine this from past failures on a similar system, or from testing — e.g. 1,000 defects were found testing the last release, and 10 affected availability with no workaround, a fraction of 0.01.
- The number of installed sites that most closely matches how many installations of this version are planned.
- The schedule time in years for this release — the time from the start of development to field deployment.
- The size estimates.
- The development factors, per the survey instructions.
Calculations
Growth rate & growth period
The software computes the growth rate and growth period from the estimated number of installed sites.
Input
Definition
Growth rate — Q
How fast defects in the software become known or observed.
Growth period — TF
How long, in calendar time, defects are found in the software before there are no more observances of defects from this particular release.
Growth
Description
Nominal
Confidence bounds
Months of growth
% removed, year 1
Very Slow
Very slow deployment of systems
3.3
.4
96
31%
Slow
One-of-a-kind system (not more than 3 sites)
4.5
.6
64
57%
Medium
Several installed sites but not mass distributed
6
.8
48
78%
Fast
Mass distributed
9
1.1
32
97%
Growth rate vs. growth period
These move inversely: a very high growth rate means a very short growth period, and a very small growth rate means a very long growth period.
Dashboard Results
Defect discovery profile
The defect profiles are predicted by inserting the prediction inputs, where Q and TF are the growth rate and growth period. Interruptions are computed by multiplying predicted defects by the ratio of interruptions to defects. Critical defects are predicted by multiplying predicted defects by the percentage predicted to be critical.
Predicted defects between T1 and T2, any severityi
= N(Exp(−Q / TF × T1) − Exp(−Q / TF × T2))
Predicted critical defectsi between T1 and T2
= NC(Exp(−Q / TF × T1) − Exp(−Q / TF × T2))
Lower and upper bounds follow the relative error on size estimations — a 50% relative error means the upper bound is 50% higher than nominal and the lower bound is 50% lower.
Symbol
Meaning
T
Duty cycle in month i
Q
Growth rate
TF
Growth period
T1
Beginning of the interval being solved for — e.g. for month 3, T1 = 2.
T2
End of the interval being solved for — e.g. in the previous example, T2 = 3.
N
Number of inherent defects delivered.
NC
Number of critical defects delivered = N × percentage of defects that are critical.
The subscript i indicates this prediction is for a particular point in time during operation.
Reliability growth trends
The trend extends over eight years. Discovered defects and failure rate typically trend upward over that period — software systems get larger over time, and every new release resets reliability growth as a function of the new code added. The software is never done.
Continue to the next stage of the prediction.
The defect profile feeds directly into the failure rate and MTTF calculation.