Software Quality Management Unit – 4 y y G Roy Antony Arnold Asst. Prof./CSE
• It is important to or when development work is complete. p p• It is more important when it is under development.• For these activities, the S f h i ii h Software are needed.
• On the one h d quality management h hand, li models or so that .• On the other hand, they can be and .• They .
• Th reliability growth models, which are The li bilit th d l hi h , therefore, as for reliability y assessment.• The reliability growth models are useful for quality management in terms of for a specific predetermined quality goal .
• Iceberg analogy describes the Testing Defect Rate Field Field . Defect Rate• The and .• The size of the iceberg is Total Error Injected in the Software .
• By the time , the and .• The . To reduce the submerged part, of the iceberg above the water.
• P h Perhaps the most important principle in software h i i i l i f engineering is " .“• O i t Our interpretation of the principle, in the context t ti f th i i l i th t t of software quality management, is threefold: – The best scenario is The best scenario is . – When errors are introduced, , . – the phase of h h f
• The Rayleigh model is a . • Based on the model, if the error injection rate is j reduced, .• Also, more defect removal at the front end of the development process will lead . • Myers (1979) states that the .
• Thi This can serve as the basis for quality th b i f lit improvement strategy—especially 1. Plans and actions to reduce error injection 1 Plans and actions to reduce error injection include the laboratory‐wide implementation of the the laboratory‐wide implementation of the y p defect prevention process; the use of CASE tools for development; the use of CASE tools for development; focus on communications among teams to focus on communications among teams to f i i prevent interface defects; and others. prevent interface defects; and others.
2. To facilitate early defect removal, actions implemented 2 T f ilit t l d f t l ti i l t d include • The bidirectional quality improvement strategy is illustrated in the next Fig. by the Rayleigh model.
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User Expectation Software DefectThis software will help me Desired software accomplish a task. li h k functionality is missing. f i li i i iClicking on the button Clicking on the button does performs the task i want to nothing or not what i want it f th t k tt thi t h ti t itdo. to do.A file can be successfullyA file can be successfully The file becomes corrupted The file becomes corruptedcopied to another location. during the copy process.Calling a method in the API The API fails due to anCalling a method in the API The API fails due to anwill perform as documented undocumented change to g y the registry.
• 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 p never knows where he may cast. – Leonardo da Vinci• E Experience will answer a question, and a question i ill i d i 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 The key is that the phase‐based defect b dd f t removal targets are set to reflect an earlier defect removal pattern compared to the defect removal pattern compared to the baseline. • Then action plans should be implemented to Then action plans should be implemented to achieve the targets.• As can be seen from the curves, the shifting As 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: When setting d f i defect removal targets f a project, error i j i l for j injection rates can be estimated based on previous experience.• However, 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, lower actual d f l l defect removal could b the result of l l ld be h l f lower error injection or poor reviews and inspections.• In contrast, higher actual defect removal could be the result of higher error injection or better reviews and inspections.• H How d we k do know which scenario (b hi h i (better d f defect removal,l higher error injection, lower error injection, or poorer defect removal) fits the project? ) p j
• To solve this problem, an additional indicator, , is incorporated into the context of the model for better interpretation of the data.