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Debunking Quality Myths SREERAM KISHORE CHAVALI

Quality myths

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Presentation used for discussion at Meetup on June 17 2013

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Page 1: Quality myths

Debunking Quality MythsSREERAM KISHORE CHAVALI

Page 2: Quality myths

About MeQA Strategy Consultant

QA Director - Satmetrix

Senior QA Manager - Informatica

Technical Manager - Ramco Systems India

- QA Winning Forumla: on SlideShare

- Product Management and QA Collboration - Meetup April 2013

Page 3: Quality myths

MythDefinition: An unproved or false collective belief that is used to justify a socialinstitution.

Why Talk about these?

- Pride in Profession

- Bring Clarity

- Establish realistic goals/objectives

- Don't waste your career

Page 4: Quality myths

Most Critical MythsDefinition of Quality

Automated Testing eliminates Manual Testing

Aim for 100% test automation

Testers need to know coding

More...

Page 5: Quality myths

Anatomy of an effective debunkingBringing all the different threads together, an effective debunking requires:

• Core facts—a refutation should emphasise the facts, not the myth. Present only key facts to avoid an Overkill Backfire Effect;

• Explicit warnings—beforeany mention of a myth, text or visual cues should warn that the upcoming information is false;

• Alternative explanation—any gaps left by the debunking need to be filled. This may be achieved by providing an alternative causal explanation for why the myth is wrong and, optionally, why the misinformers promoted the myth in the first place;

• Graphics – core facts should be displayed graphically if possible.

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Sample AnalogyNo two projects are same: Technology, complexity, people, cost, effort

Treat each variation of software project as a variation of a medical condition

Diagnose each project carefully.

Find out similarities

Find out differences

Apply what works based on known facts

Explore solutions for new challenges

Don't force fit a process, team to follow a rigid process. Establish guidelines, goals and leave flexibility.

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Establish Facts/GuidelinesDon't come to conclusion based on limited data and establish a broader rule

Factors that determine variations in 'Software Quality' discipline

- Type of Software: Business Application, Embedded Software, Operating System, Mobile App, Games

- Types of Industry: Internet, Healthcare, Insurance, Finance

- Cost of Bad Quality: Mostly High but $$$ varies based on Maturity of business.

- Evolving Vs Established: New Business, First year of Operation, 10 years of Operation, 30 years of Operation

e.g. Don't try to force a Start Up Practice on Mission Critical Software

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Matrix Example

Page 9: Quality myths

Quadrant Example

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MindMap Example

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Referenceshttp://softwaretestingfundamentals.com/software-testing-myths/

http://en.wikipedia.org/wiki/List_of_software_categories

http://www.flickr.com/photos/softwaretestingclub/7579063452/sizes/o/in/photostream/

http://www.flickr.com/photos/softwaretestingclub/8396776442/sizes/o/in/photostream/

http://blog.smartbear.com/process/how-to-improve-communication-between-qa-and-development/

http://www.skepticalscience.com/docs/Debunking_Handbook.pdf

http://en.wikipedia.org/wiki/Software_quality

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Our roleActively add your perspective to discussions that are myths

Promote material that debunks myths

establish forums specific to your domain/situation.

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DiscussionPick a topic

Know the group: Role, Type of Software

Develop a visual that bring clarity to 'Myth'

- Grid

- Quandrants

- Mindmaps

- etc.

Page 14: Quality myths

Recap/Wrap up