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Today, let's explore the `ProcessOrder(orderValue, customerTier)` function. Can anyone tell me its purpose?
It processes an order and applies discounts based on the order value and customer tier.
Exactly! Now, what do you think we should consider when validating the `orderValue`?
It should be within the specified range, right?
Correct! The `orderValue` must be between 100.00 and 10000.00. Remember this range as we move forward. Can anyone summarize what we discussed?
We talked about the function's purpose and the importance of validating the order value within a certain range.
Great job! Let's dive deeper into how we can apply equivalence class testing to validate our function.
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Now, let's identify the equivalence classes for `orderValue`. Who can explain the valid and invalid classes?
The valid equivalence class ranges from 100.00 to 10000.00. Invalid categories include anything less than 100.00 or greater than 10000.00.
Exactly! We have one valid class and two invalid classes. Can someone give me examples of values in each class?
Valid: 5000.00; Invalid less than: 50.00; Invalid greater than: 12000.00.
Well done! Remember how these specific ranges will guide our testing. Let's move on to the customerTier.
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Letβs turn our attention to `customerTier`. What are the valid and invalid classes for this parameter?
Valid tiers include 'Bronze', 'Silver', and 'Gold'. An invalid example could be 'Platinum'.
Good observation! So, under these classifications, how can we derive our test cases effectively?
We want to ensure we create test cases where only one input is invalid at a time.
Exactly my point! This approach helps maintain focused testing while covering all scenarios. Can someone summarize the equivalence classes for customerTier?
Valid: 'Bronze', 'Silver', 'Gold'; Invalid: 'InvalidTier'.
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Now that we have our equivalence classes for both parameters, how do we create our test cases?
We can combine valid and invalid classes to generate multiple scenarios.
Exactly! Let's draft our test cases. What might an all-valid scenario look like?
It could be `orderValue = 5000.00` and `customerTier = 'Silver'`.
Great example! Now, what about scenarios that involve invalid inputs?
We could test with `orderValue = 50.00` with `customerTier = 'Silver'`, which is invalid.
And `orderValue = 5000.00` with `customerTier = 'InvalidTier'`.
Excellent! Youβre understanding how to effectively validate multiple paths. Let's recap our entire session.
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Today, we explored the `ProcessOrder` function. What are the major takeaways regarding input validation?
We identified the importance of validating `orderValue` and `customerTier` using equivalence classes.
And how to generate effective test cases from both valid and invalid equivalence classes.
It's critical to focus on having only one invalid input in our tests to maintain clarity.
Excellent observations! These strategies not only optimize our testing but also enhance our confidence in the softwareβs functionality.
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The section demonstrates the use of Equivalence Class Testing for a ProcessOrder function that determines discounts based on the order value and customer tier. It outlines the valid and invalid equivalence classes for both parameters, and how to derive effective test cases covering various scenarios.
In this section, we delve into the practical application of Equivalence Class Testing (ECT) through the example of a ProcessOrder(orderValue, customerTier)
function. This function applies conditional discounts based on the numeric order value and the customer tier, which can be either 'Bronze', 'Silver', or 'Gold'. The core requirement is to validate the inputs: the orderValue
, which must fall within a specified numeric range of [100.00, 10000.00], and the customerTier
, which must be one of the valid string values. The section explores how to identify valid and invalid equivalence classes for these inputs effectively and illustrates how to derive test cases using the weak ECT approach. By ensuring that we create test cases where only one input is invalid at a time or all inputs are valid, we achieve wide coverage of potential input scenarios while optimizing the testing effort.
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Consider a ProcessOrder(orderValue, customerTier) function that applies discounts based on order value and customer tier.
The ProcessOrder function processes orders by taking two parameters: orderValue
, which is a numeric value within the range of 100.00 to 10000.00, and customerTier
, which can be one of three defined strings: 'Bronze', 'Silver', or 'Gold'. The requirements state that this function must not only fulfill valid parameter inputs but also handle invalid cases effectively. For example, if a user inputs an orderValue
that is lower than 100.00 or higher than 10000.00, or if customerTier
does not match any of the allowed values, the function should manage these inappropriate inputs gracefully, likely by returning an error message or default behavior.
Consider this function like a restaurant ordering system. Imagine if a customer tries to place an order for a menu item but enters a quantity that is too high or too low, like trying to order 1,000 burgers or just one half of a burger. The system needs to inform the customer that their request is unacceptable and guide them to a proper range of ordering options. Similarly, the ProcessOrder function checks the order and customer status before processing it.
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In order to effectively test the orderValue
parameter, we define equivalence classes (EC). The primary valid equivalence class (Valid EC) consists of values ranging from 100.00 to 10000.00, representing acceptable order values. For invalid cases, two classes are identified: invalid EC 1 gathers numbers less than 100.00, like 50.00 or -10.00, while invalid EC 2 consists of numbers exceeding 10000.00, such as 12000.00. By categorizing inputs into these equivalence classes, we can ensure that only one test case from each class will be needed to verify whether the function performs as expected under various circumstances.
Think of this as a ticket booking system for a concert. If tickets are priced between $100 and $10,000, the valid EC is any ticket price within that range. If someone tries to book a ticket for $50, that's invalid because it's below the minimum price, and if someone wants a $12,000 ticket, that's also invalid since it exceeds the maximum allowed price. Just as the system checks for proper prices, the ProcessOrder
function verifies that orderValue
is within the acceptable range.
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For the customerTier
, equivalence classes are established to ensure that valid and invalid inputs are tested. The valid equivalence classes include 'Bronze', 'Silver', and 'Gold', representing different tiers within the system. Additionally, an invalid equivalence class is defined with examples like 'Platinum' or 'None', which are not acceptable values for this parameter. Each of these classes allows us to test the functionality for both valid and invalid customer tiers once, rather than testing each potential input manually.
Imagine a loyalty program at a store where customers can be categorized into different tiers based on their spending: 'Bronze' for new members, 'Silver' for moderately loyal customers, and 'Gold' for the most valued customers. If a customer tries to sign up as 'Platinum', which doesnβt exist within the store's tiers, the system must reject this entry. Thus, just like the loyalty tier system, the ProcessOrder
function verifies that the input tier aligns with its predefined classes.
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We aim to create test cases where, ideally, only one input is invalid at a time, or all are valid.
Total test cases: 6 (using a weak approach, covering all classes at least once).
Using the weak equivalence class testing approach, we systematically derive test cases from the defined equivalence classes. First, we create one test case where both inputs are valid. Second, we design two test cases that feature invalid orderValue
while maintaining a valid customerTier
. Third, we create a test case for an invalid customerTier
paired with a valid orderValue
. Lastly, we ensure we cover representatives from each valid tier. This rigorous but straightforward approach results in a total of six meticulously crafted test cases, guaranteeing that each equivalence class is tested at least once.
Consider preparing for a fitness class that has a minimum age requirement. If the class requires participants to be at least 18 years old, you would validate that eligible students who show up can attend (valid scenario). However, if someone arrives and claims they are 16 years old (invalid age), they cannot join. By covering various cases and ensuring each age tier is tested, like having representatives of suitable age brackets show interest in joining, you create a comprehensive pictureβmuch like crafting our test cases for the ProcessOrder
function.
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Key Concepts
Equivalence Class Testing: A testing technique for dividing inputs into equivalent classes for testing.
Valid and Invalid Classes: Classification of inputs based on meeting or failing to meet specified requirements.
Deriving Test Cases: The process of creating test cases based on identified equivalence classes.
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Valid orderValue example: 5000.00 is valid, while 50.00 is not.
Valid customerTier example: 'Gold' is valid, while 'Platinum' is invalid.
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OrderValue high or low, must between one hundred flow, otherwise it wonβt go!
Imagine a marketplace where customers carry gold, silver, and bronze coins. To buy an item, their coins must sum between $100 and $10,000, or they can't place their order.
VOWS: Valid orderValue [100.00, 10000.00], invalid orderValue [<100, >10000].
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Review the Definitions for terms.
Term: Equivalence Class Testing (ECT)
Definition:
A black-box test case design technique that divides input data into partitions that are expected to be processed similarly.
Term: orderValue
Definition:
A numeric input representing the total monetary value of an order, which must meet specified criteria.
Term: customerTier
Definition:
A string input representing the category of the customer (e.g., 'Bronze', 'Silver', 'Gold').
Term: Valid Equivalence Class
Definition:
A set of inputs that satisfy the requirements for correct processing within the software.
Term: Invalid Equivalence Class
Definition:
A set of inputs that do not satisfy the software's requirements, leading to failure or incorrect processing.