Testing techniques
**Common testing techiques**
Different testing techniques are used in software testing, which helps us **design effective test cases and test coverage**.
The common testing techniques we used are as follows:
- Equivalent partitioning
- Boundary value analysis
- Decision table testing
- Static transition testing
- Error guessing
Each testing technique has different **goals/objectives**.
Let say
1. Equivalent partitioning:
It reduces the number of test cases but maximizes the test coverage
2. Boundary value analysis (BVA)
It focuses on boundary/edge values, where we can find common bugs.
3. Decision table testing (DTT)
It uses the table technique for various input combinations
4. State transition testing (STT)
The name itself says transition, so it tests behavior when the system changes.
5. Error guessing
It is based on experience to find bugs
**2) Boundary value analysis (BVA)**
It is the technique that is which we include boundary/edge values to write the test cases.
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It is used when the input field has a maximum and minimum value
Use case 1: Amount fields that accept values from 10–1000 rupees
Test case 1 (minimum value) — 9(invalid) 10(valid) 11(valid)
Test case 2 (maximum value) — 999 (valid) 1000(valid) 1001(invalid)
**3) Decision table testing (DTT)**
This technique can be used when there are multiple input conditions.
When there are more than 2 fields then the results will be based only by the combinations of those fields.
Use case 1: Registration form for voter ID where Age should be above 18, nationality is indian, and Aadhar number is mandatory, then the form is submitted.
Age above 18? Nationality indian? Aadharnumber Registration form
success/error
Yes yes yes Success
No Yes Yes Error
Yes No yes Error
Yes yes No Error
yes No No Error
No No yes Error
No Yes No Error
NO No No Error
**4) The future of manual testing in the age of AI**
Yes, AI is changing the software industry as it plays a major role in software development, but it won’t impact manual testing it evolving
AI cannot replace manual testing, it helps the testers to create more test scenarios and test cases.
Manual testing is always considered. As AI cannot solve the issues that are not in the testcases, like UI issues, layout issues, and business logics. Also, when the requirements are not clear, only manual testing helps in validating ideas.
However, manual tester should upskill their knowledge in AI. Learn generative AI and prompt engineering to write more test cases or corner cases suggestions, which helps testers execute more test cases so that the product is bug-free.
