I have a small confusion about decision table testing. We basically use decision tables to arrive at various possible combinations and then decide what conditions need to be tested and what need not be tested. But how decision table will help in checking invalid conditions? How do we decide how many invalid conditions have to be tested?

Assume I have below decision table. The requirement says if Blower State is OFF, AC request state shall be OFF and Air Condition state shall be OFF. Ambient temperature condition in this case is don't care. So obviously I need not test with more than one set of data when blower state is OFF. That is why I have considered only one case for blower state OFF condition.

Similarly if AC User Request State is OFF, temperature condition is don't care. So I have put only one case with AC user request OFF.

So totally I arrived at 4 test cases instead of 8 test cases, considering all combinations.

Now my question is: To check the robustness of the system, don't we need to keep the blower in OFF state and (Ambient temperature > user request temperature) and test that Air conditioning system is OFF?

Similarly don't we need to keep the ambient temperature > user request temperature and test for air conditioning system when AC User request is OFF?

There may be several other negative testing scenario like this. How do we select negative test scenario also using decision table?

x in below table indicates don't care condition.

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1 Answer 1


A decision table can help you come up with scenarios to test, but it can't help you decide whether those scenarios need to be tested or not.

To me this question isn't so much about decision tables as it is about asking "What happens if this is broken?". If the cooling control stops working, what happens? If the blower stops working, what happens? If the air conditioner unit starts blowing heat instead of cold, what happens?

Can we think of any conditions where we would need to signal for a repair technician, trigger a fire alarm, or some other notification? How urgent is the notification? Will work have to stop because it's too hot, losing the business money, or will there simply be staff complaints to deal with?

Once you identify the possible breakdowns in the system and the consequences for each, the decision to test for a particular scenario should be quite clear.

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