Answer:
i. When applying equivalence partitioning, the goal is to divide the input values into groups or partitions that are expected to behave in a similar way. This technique helps reduce the number of test cases needed to achieve sufficient coverage.
In this case, we can divide the score range into the following partitions:
- Partition 1: Scores below 50 (e.g., 0, 1, 49)
- Partition 2: Scores between 50 and 59 (e.g., 50, 55, 59)
- Partition 3: Scores between 60 and 69 (e.g., 60, 65, 69)
- Partition 4: Scores between 70 and 79 (e.g., 70, 75, 79)
- Partition 5: Scores between 80 and 89 (e.g., 80, 85, 89)
- Partition 6: Scores between 90 and 100 (e.g., 90, 95, 100)
To achieve the minimum test coverage, you need to test one representative value from each partition. So, in this case, you would need 6 test cases.
ii. Boundary value analysis focuses on testing the boundaries or edges of input partitions. The idea is to test the minimum and maximum values of each partition, as well as values just below and above those boundaries.
Using the same partitions as before, let's consider the boundaries:
- Partition 1: Minimum value: 0, Maximum value: 49
- Partition 2: Minimum value: 50, Maximum value: 59
- Partition 3: Minimum value: 60, Maximum value: 69
- Partition 4: Minimum value: 70, Maximum value: 79
- Partition 5: Minimum value: 80, Maximum value: 89
- Partition 6: Minimum value: 90, Maximum value: 100
To achieve the minimum test coverage with boundary value analysis, you need to test the minimum and maximum values of each partition, as well as values just below and above those boundaries. In this case, you would need 9 test cases.
It's important to note that these numbers represent the minimum test cases needed for coverage. Depending on the complexity of the system and the specific requirements, additional test cases may be necessary for thorough testing.
Step-by-step explanation:
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