quality management models
DESCRIPTION
Software Quality ManagementAnna University SyllabusB.E. IV CSEAbout Quality Management ModelsTRANSCRIPT
Software Quality ManagementUnit – 4
G Roy Antony Arnoldy yAsst. Prof./CSE
• It is important to
orwhen development work is complete.p p
• It is more importantwhen it is underwhen it is under
development.h i i i h S f• For these activities, the Software
are needed.
h h d li• On the one hand, quality managementmodels
or so that.
• On the other hand, they can beand
.• They• They
.
Th li bilit th d l hi h• The reliability growth models, which are
,therefore,
as for reliabilityyassessment.
• The reliability growth models are useful forquality management in terms of
for a specific predetermined qualityfor a specific predetermined qualitygoal .
• Iceberg analogy describes• Iceberg analogy describesthe Testing Defect Rate
Field.
• The
Field Defect RateThe
and.
• The size of the iceberg is
Total Error Injectedin the Software
.
• By the time , theand
.• The• The
. To reduce the submerged part,
of the iceberg above the water.
P h h i i i l i f• Perhaps the most important principle in software engineering is " .“O i t t ti f th i i l i th t t• Our interpretation of the principle, in the context of software quality management, is threefold:
The best scenario is– The best scenario is .
– When errors are introduced, ,
.h h f– the phase of
• The Rayleigh model is a .
• Based on the model, if the error injection rate is jreduced,
.• Also, more defect removal at the front end of the
development process will lead .
• Myers (1979) states that the
.
Thi th b i f lit• This can serve as the basis for quality improvement strategy—especially
1 Plans and actions to reduce error injection1. Plans and actions to reduce error injection include
the laboratorythe laboratory‐‐wide implementation wide implementation of the of the yy ppdefect prevention process; defect prevention process; the the use of CASE tools for development; use of CASE tools for development; ff i ii ifocus focus on on communications among communications among teams to teams to prevent interface defects; and othersprevent interface defects; and others..
2 T f ilit t l d f t l ti i l t d2. To facilitate early defect removal, actions implemented include
• The bidirectional quality improvement strategy is illustrated in the next Fig. by the Rayleigh model.
Greek Biographer and Moralist (AD 46 – 120)Greek Biographer and Moralist (AD 46 120)
User Expectation Software DefectThis software will help me
li h kDesired software f i li i i iaccomplish a task. functionality is missing.
Clicking on the button f th t k i t t
Clicking on the button does thi t h t i t itperforms the task i want to
do.nothing or not what i want it to do.
A file can be successfully The file becomes corruptedA file can be successfully copied to another location.
The file becomes corruptedduring the copy process.
Calling a method in the API The API fails due to anCalling a method in the API will perform as documented
The API fails due to anundocumented change to the registry. g y
• It is theory that decides what can be observed Albert Einstein– Albert Einstein
• He who loves practice without theory is like the sailor who boards ship without a rudder and compass and p pnever knows where he may cast.
– Leonardo da VinciE i ill i d i• Experience will answer a question, and a question comes from theory. –W Edwards Deming (Father of Process Improvement).
• A framework, like a theory, provides a means to ask questions.
• A process framework provides the skeleton of a theory that can be filled in by the user of the framework.
Th k i th t th h b d d f t• The key is that the phase‐based defect removal targets are set to reflect an earlier defect removal pattern compared to thedefect removal pattern compared to the baseline.
• Then action plans should be implemented toThen action plans should be implemented to achieve the targets.
• As can be seen from the curves, the shiftingAs can be seen from the curves, the shifting of the defect removal patterns does reflect improvement in the two directions of (1) earlier peaking of the defect curves, and (2) lower overall defect rates.( )
• Problem is in assumption of the error injection rate: Wheni d f l f j i j isetting defect removal targets for a project, error injection
rates can be estimated based on previous experience.• However, there is no way to determine how accurate suchHowever, there is no way to determine how accurate such
estimates are when applied to the current release.• When tracking the defect removal rates against the model,
l l d f l ld b h l f llower actual defect removal could be the result of lowererror injection or poor reviews and inspections.
• In contrast, higher actual defect removal could be theIn contrast, higher actual defect removal could be theresult of higher error injection or better reviews andinspections.H d k hi h i (b d f l• How do we know which scenario (better defect removal,higher error injection, lower error injection, or poorerdefect removal) fits the project?) p j
• To solve this problem, an additional indicator,is incorporated into the context of the, is incorporated into the context of the
model for better interpretation of the data.