CH05.L02.BBT-1-Equivalence Partitioning
Summary
TLDRThe video script introduces the Equivalence Partitioning (EP) technique, a black box testing method used to efficiently test software by dividing input data into valid and invalid partitions. It emphasizes the importance of selecting representative samples from each partition to minimize the number of test cases needed. The script demonstrates how to apply EP to a range of numerical inputs, highlighting its effectiveness in reducing test case volume while maintaining coverage. It also mentions the technique's compatibility with boundary value analysis, setting the stage for the next video.
Takeaways
- 📚 Equivalence Partitioning (EP) is a black box testing technique used to determine the probability of user input within a specific range.
- 🔍 EP avoids writing extensive test cases by dividing inputs into valid and invalid partitions, reducing the number of tests needed.
- 📈 The valid partition includes numbers within the specified range, while the invalid partition includes numbers outside this range.
- 🌐 Choosing a sample from each partition is sufficient to represent the entire group for testing purposes.
- 🎯 If a test case for a number within a partition passes, it is highly likely that all other numbers in the same partition will also pass.
- 🐛 Conversely, if a test case fails, it is probable that all numbers in the same partition will fail, indicating a bug.
- 📝 The example given in the script involves testing a text field that accepts numbers from 1 to 100, dividing the inputs into three partitions: in-range, above-range, and below-range.
- 📉 The number of test cases is minimized to the most effective number that can represent each part of the data range.
- 🔑 EP is not used in isolation but is often combined with boundary value analysis for more comprehensive testing.
- 🔄 The division of inputs into partitions is not always into three; it depends on the nature of the input, such as number of sets or Boolean values.
- 📌 For inputs requiring specific values, one valid partition is created for the identified value, with two invalid partitions for values outside this range.
- 🔍 The script concludes by emphasizing the importance of using EP in conjunction with boundary value analysis for effective software testing.
Q & A
What is the abbreviation for Equivalence Partitioning?
-The abbreviation for Equivalence Partitioning is EP.
Why is Equivalence Partitioning used in software testing?
-Equivalence Partitioning is used to test the probability that the user's input falls within a specific range of data, reducing the number of test cases needed.
How does Equivalence Partitioning reduce the number of test cases?
-It divides the data inputs into valid and invalid partitions, and only one sample from each partition is used in the test cases, representing the entire group.
What is the purpose of dividing the data into partitions in Equivalence Partitioning?
-The purpose is to cover all possible input scenarios with the least number of test cases, ensuring that the test results can be generalized to all numbers within the same partition.
What are the three partitions created in the example provided in the script?
-The three partitions are: valid partition for numbers within the range of data (1 to 100), invalid partition for numbers greater than 100, and another invalid partition for numbers less than 1.
How does testing one number in a partition represent the entire group in Equivalence Partitioning?
-Testing one number in a partition is assumed to be representative of all numbers in that partition because the logic or behavior is expected to be the same for all numbers within the range.
What is the significance of choosing one number from each partition for testing?
-Choosing one number from each partition ensures that all possible input scenarios are covered, which helps in identifying potential bugs or issues that might affect the entire group.
Can Equivalence Partitioning be used independently in software testing?
-Equivalence Partitioning is not used separately; it is typically used in conjunction with boundary value analysis.
What is the relationship between Equivalence Partitioning and boundary value analysis?
-Equivalence Partitioning is often used together with boundary value analysis to ensure that both the range and the boundaries of the input data are thoroughly tested.
How does Equivalence Partitioning apply to inputs like Boolean values or specific values?
-For Boolean values, two partitions are created: one for the true value and one for all other values. For specific values, one valid partition is created for the identified value and two invalid partitions for values outside the specified range.
Outlines
🔍 Introduction to Equivalence Partitioning (EP)
The video script introduces the Equivalence Partitioning (EP) technique, a black box testing method used to determine the probability of user input within a given range. It explains that instead of creating numerous test cases for every possible input, EP divides the input into 'valid' and 'invalid' partitions. The 'valid' partition includes inputs within the specified range, while the 'invalid' partition accounts for inputs outside this range. The script uses the example of a text field that accepts numbers from 1 to 100, suggesting that testing a single number from each partition is sufficient to represent the entire group within that partition. The technique is illustrated with three partitions: one for numbers within the range, one for numbers greater than 100, and one for numbers less than 1. The script emphasizes that if a test case from a group passes, it is highly likely that all numbers in that group will pass, and vice versa for failures. The video concludes by noting that EP is not used in isolation but in conjunction with boundary value analysis, which will be covered in a subsequent video.
Mindmap
Keywords
💡Equivalence Partitioning (EP)
💡Test Cases
💡Valid Partition
💡Invalid Partition
💡Boundary Value Analysis
💡Range of Data
💡Input
💡Probability
💡Minimum Effective Number of Test Cases
💡Boolean Value
💡Specific Value
Highlights
Introduction to the Equivalence Partitioning (EP) technique for black box testing.
EP is utilized for testing user input within a specific data range, such as a text field accepting numbers from 1 to 100.
Explanation of the inefficiency of writing 100 test cases for every number in a range.
The concept of dividing data inputs into two partitions: Valid and Invalid.
The valid partition includes numbers within the data range, while the invalid includes numbers outside the range.
Selecting one number from each partition as a sample for testing purposes.
The rationale behind reducing the number of test cases to cover all probabilities effectively.
Applying EP technique to the example of testing a range of numbers from 1 to 100.
Creating three partitions: one valid for 'in-range' numbers, and two invalid for numbers above and below the range.
The principle that testing one number in a partition is equivalent to testing all numbers in that partition.
Choosing specific numbers for test cases to represent the entire group within each partition.
The high probability that if a test case passes, all numbers in the same group are likely to pass.
The high probability that if a test case fails, all numbers in the same group are likely to fail.
Different cases of input division, such as for the number of sets or Boolean values.
The approach to inputs requiring a specific value, dividing into one valid and two invalid partitions.
Conclusion of the Equivalence Partitioning technique and its suitability for software with a range of data.
The importance of combining EP with boundary value analysis for effective testing.
Transcripts
The first Black box technique we will train on it
is the Equivalence Partitioning
and its abbreviation is (EP)
It is used when we test the probability that
the user's input is for a range of data.
such as: a text field takes
inputs of numbers from 1 to 100.
if we find such a range of data,
there is no logic in writing
100 test case to
test all numbers.
so how many tests will you make to
test this range of numbers?
Equivalence Partitioning Technique says:
we will divide the data inputs into
2 partitions: Valid & invalid
the valid partition is for numbers
inside the range of data.
and the invalid is for numbers outside the range of data
we will take one number
from each partition, as a sample
for the group it belongs to,
to use in my test case. Therefore,
instead of making a great number of test cases,
we will shorten their number
to the least number to cover all the probabilities.
when we test this chosen number
using the test case
it is the same as if we tested
all the numbers of this partition.
Lets get back to our example
to apply this technique on it.
The range of numbers to be tested
is from 1: 100, and the user may
add a number from this range
or bigger than this range or smaller
than the range. so we should make
a valid partition for the numbers
that "in range of data"
and an invalid partition for the numbers
that user may input
above 100. and finally,
the numbers that user may input
less than 1 to be the third partition
and it will be invalid partition.
In the first partition, when
we test 1, it will be the same as
testing 50, 43, or 100.
so we 'll choose one number from the
valid partition first to test in
my first test case. Then we'll choose
from the second "out of range" partition
any number more than 100, to test
in the second test case. And same thing for
the final "out of range" partition,
I'll choose any number less than 1
and it will be enough to represent the whole group.
so with the EP technique
we can know that:
if the group's test case results "pass",
so there is a very high probability
to all numbers of the same group
to result "pass". if this test case
results a bug, so there is a very high
probability to all numbers of the same
group to result a bug. In the previous
example, we did 3 test cases
which is the Minimum effective number
of test cases that can represent each
part of the range of data, but we have to notice that
the division of input is not always
into 3 partitions like range,
but we'll find many different
cases, such as:
if the input is Number of sets,
then we'll make only 2 partitions.
a valid partitions for the group of
the right numbers and we'll choose
one number of them, and invalid partition
for any number out of this
group of numbers. Also,
if the input is Boolean value ,
we'll make only 2 partitions
a valid partitions for the right value
which is (true), and an invalid partition
for the other values which is (false).
finally, if the input requires
a specific value, we'll deal with it
like range. we'll divide it into
one valid partition for the identified value
and two invalid partitions;
one for the bigger numbers, and one for the smaller numbers
than this value.
And by now, we have finished the first technique of
Black box technique which is Equivalence Partitioning.
we have to remember that it is suitable
for the software with range of data,
in which we divide the input into partitions
and we choose numbers from it
to represent their groups,
to be able to write the minimum
number of effective test cases.
The EP technique is not used separately
but it is used with boundary value analysis
which we will apply in the next video.
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