3. BusinessKnow-How Asymmetry
Changing Requirements
ImproperRisk Management
Tool Dependence
Insufficient Time
UntestableCode
Test AutomationAnti-Patterns
Problematic Data Management
Monolithic Applications
Technical Debt
Over Expectations
Unclear Duties
Challenges
in
Test Automation
4. Any Test Automation ACTIVITY should address
Manual Testing Efforts
Long feedback times
Operatıonal Blındness
Error-Prone Actıvıtıes
13. Test Automation BEST Practices
Software Testıng Ice-Cone Antı-Pattern
vs
Ideal Software testıng pyramıd
IMAGE, www.thoughtworks.com/insights/blog/architecting-continuous-delivery
14. Four Design Techniques for Successful
Test Automation Data Management
A typical maturity level of data management for test
automationprocess is outlinedhere;
FullyIntegrated Test Data
PartiallyIndependentTest Data
StoringTest Datainan External Source
DynamicTest Data Management (MicroServices, GUI ?)
16. Learn more about Data Virtualization
It makes test data management easier
An added advantage here is thatif the data in any environmentis
corrupted – let’s say after a round of testing- it is very easy to
revert the data back to original state.
20. BDDfocuses on obtaining
a clear understandingof
desiredsoftware
behaviorthrough
discussion with
stakeholders.
Martin Fowler’s Business Readable, Domain Specific
Language Blog Post
21. Another crucial point is to provide an
abstraction layer between automation
tool and test sUite.
Selenium, Sahi, UFT, Coded UI
whatever tool underlying
should not be concern
for automator
23. A Test Architect is responsiblefor
FRAMEWORK LAYER, whichprovides
utility functionsto upper layers
It is heavily one-timeeffort, and not
addressedin the project iterations
25. Testers are responsiblefor TEST LAYER, which is
Better To BE BDD, to create business value to each
stakeholder
Analystsare responsible for detailedand
correct acceptance-criteria thatBDD Scripts
base on
26. ALSO %50 of THE MAINTENANCEEFFORTCOMES
FROM CHANgING OBJECT IDENTIFIERS
LET’S MAKEIT EVERYONE’SJOB IN THE TEAM
NOT ONLY SOMEONe