Manual Testing Techniques and future of manual testing in the age of AI

Common Manual Testing Techniques:
As a tester in Software development process, we need to make sure that the software product works as intended and meets high quality. In order to achieve this, we use various testing techniques like

Boundary value a…


This content originally appeared on DEV Community and was authored by Indu Karthick kumar

Common Manual Testing Techniques:
As a tester in Software development process, we need to make sure that the software product works as intended and meets high quality. In order to achieve this, we use various testing techniques like

  • Boundary value analysis
  • Equivalence partitioning
  • Decision table testing
  • State transition Testing
  • Use case testing
  • Error guessing, etc These techniques enable us to cover all possible test scenarios and identify as many defects as possible, ensuring the delivery of a high-quality application.

Boundary value analysis (BVA): Input values near the boundaries are the place where the chances of defect occurrence are high. BVA focusses on testing the boundaries of the input range. For example,
if a "Name" textbox accepts minimum 10 characters and maximum 20 characters, then in BVA values are:
Boundary values for minimum input: 9, 10, 11
Boundary value for maximum input: 19, 20, 21.

Decision Table Testing: This testing technique is used to test complex applications using combinations of inputs and the corresponding outputs.
Example: Discount on clothes based on age and membership in the store/shop
Condition1: Above 60?
Condition 2: customer has membership in the shop?
and
Action 1: 20% discount
Action 2: 10 % discount
Action 3: No discount

Age Membership 20% disc 10% disc No disc
Above 60 Yes Yes No No
Above 60 No No Yes No
Below 60 Yes No Yes No
Below 60 No No No Yes

The Future of Manual Testing in the Age of AI:
Artificial Intelligence(AI) cannot entirely replace the manual testing. Instead, it should be integrated with manual testing. AI must be trained by manual testers utilizing the application's testing history. This training enables AI to manage test scenarios independently, relying on historical data without requiring human intervention. Meanwhile, manual testing remains essential in areas that demand critical thinking, human intuition, and specialized knowledge.


This content originally appeared on DEV Community and was authored by Indu Karthick kumar


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