SQE(Lecture 8)
Transcript of SQE(Lecture 8)
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Customer Problems Metric
It is a type ofproduct quality metric that measures
the problems customer encounter when using the
products.
There are two types of customers problem is there.
1) Non-defect oriented problem.
2) Defect problem.
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Non-defects-oriented problems:
1) Not the valid defects.
2) May be the usability problems ( Uncleardocumentation or information).
3) Duplicates of valid defects( defects that
where reported by other customers and fixes where
available but the current customer did not know ofthem.)
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Defect problems:
Problems with the software defects.
Therefore the customer problem metric is usually
expressed in terms of problems per user
month(PUM).
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PUM = Totalproblemsthatcustomersreported(valid
defectsandnon-defect-orientedproblems)foratime
period Totalnumberoflicense-monthsofthe
softwareduringtheperiod.Example:
For 1 month number of license copy is 1000
Therefore for a certain period (Say 12 month)there willbe 12*1000=12000 license copy of the product.
So, PUM= Total Problem/12000.
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How to minimized Problem per user
month (PUM) metric ?
Improve the development process and reduce the
product defects.
Reduce the non-defects-oriented problems by
improving all aspects of the products (Such as
usability, documentation), customer education and
support.
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Difference between Defect rate and
Customer Problem metric.
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Customer Satisfaction Metrics
Often measured by customer survey data via five
point scale:
Very satisfied
Satisfied
Neutral
Dissatisfied
Very dissatisfied
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Basedonthesefivepointscaledataseveralmetrics
canbeconstructed.
Percentageofcompletelysatisfiedcustomer.
percentageofsatisfiedcustomer.
Percentofdissatisfiedcustomers.
Percentofnonsatisfied(neutral,dissatisfied,and
completelydissatisfied)
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Forthesemetrics weightingindexapproachcanbe
use(Knownasnetsatisfactionindex)
Completelysatisfied = 100%
Satisfied = 75%
Neutral = 50%
Dissatisfied = 25%
Completelydissatisfied = 0%
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In-Process Quality Metrics
In-Process quality metrics usedtomeasureproduct
duringdevelopmentprocess.
Inthismetricswewilldiscussthefollowing.
1. Defectarrivalpatternduringmachinetesting.
2. Phasebaseddefectremovalpattern.
3. Defectremovaleffectiveness.
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Defect arrival pattern during
machine testing
To measure defect arrival pattern, we have to
consider three different metrics.
The defect arrivals (defects reported) during the
testing phase by time interval (e.g., week). These arethe total arrival defects, not all of which are valid
defects.
The pattern of valid defect arrivals.
Thepatternofdefectbacklog(Processallthedefects
attheendofthedevelopmentcycle. Generally
retesting(regression test)isneededto ensurethat
targetedproduct qualitylevelsarereached.
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Phase based defect removal pattern
It requires the tracking of defects at all phases of the
development cycle, including the design reviews,
code inspections, and formal verifications beforetesting.
The pattern of phase-based defect removal reflects the
overall defect removal ability of the development
process.
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Project A
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Project B
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Defect Removal effectiveness
Defect removal effectiveness (or efficiency) can be
defined as follows:
DRE= (Defects removed during a developing process)/(Total defects in the product) *100.
The denominator of the metric can only be approximated. It
is usually estimated by:
Defects removed during the phase + defects found
later
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The higher the value of the metric, the more effective
the development process and the fewer the defects
escape to the next phase or to the field.
Based on this metric, action plans to improve the
effectiveness of these phases were established and
deployed.
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Phase effectiveness of a software project