How do you test different types of value objects, such as money, date, or address?

Testing value objects like money, date, or address involves: Equality Checks: Verify objects are equal if their attributes match, and not equal if any attribute differs. Immutability Tests: Ensure objects don’t change after creation - any operation should result in a new object. Validation Rules: Confirm that creation logic enforces correct format and range (e.g., valid currency codes for money, sensible dates, valid address formats). Behavior Testing: For operations that involve calculations or changes (like adding amounts of money, or calculating days between dates), ensure the behavior is as expected. Boundary Conditions: Test the extremes, such as very high or low monetary values, leap years, or maximum address line lengths.

Understanding the purpose behind creating a value object is of utmost importance. Your contract is distinctive and tailored to your specific requirements, which is precisely why you are investing effort into its creation. Avoid the temptation to pursue an ideal "money object." Instead, focus on designing the essential functionalities that meet your precise needs. Strive for precision and clarity in your approach.

Assume we have a Money value object. Define a contract specifying that the amount should always be positive, and the currency should follow a specific format. public class Money { public decimal Amount { get; } public string Currency { get; } public Money(decimal amount, string currency) { // Contract: Amount should be positive if (amount < 0) throw new ArgumentException("Amount must be positive", nameof(amount)); // Contract: Currency should follow a specific format if (!Regex.IsMatch(currency, "^[A-Z]{3}$")) throw new ArgumentException("Invalid currency format", nameof(currency)); Amount = amount; Currency = currency; } }

Your test code deserves the same level of attention and care as your production code. Utilizing user-friendly test builders or factories enables you to create concise and intentional tests. Just as you wouldn't blindly copy and paste a 10-line initializer code in your service, it shouldn't feel acceptable to do so in your test suite either. In reality, if your tests become inflexible, they lose their relevance and purpose over time. It's essential to clean them up and adopt practices like using builders, factories, or initializers to ensure your tests remain as maintainable and DRY (Don't Repeat Yourself) as your production code. Prioritize your test requirements over complicated builders.

At first, the idea of using randomized test data may appear unconventional, but it does not lead to non-deterministic tests. Property-based testing employs data randomization within the confines of your specifications. In my view, the primary advantages lie in eliminating magic constants and enabling the implementation of adaptable behaviors from the outset. This approach compels you to consider the entire range of data that your code should handle. However, it is crucial to be aware of potential risks: Never dismiss failures as mere "random" occurrences; always investigate their root cause. Otherwise, you may inadvertently foster an atmosphere of negligence, akin to the "broken window" effect.

Although it may be satisfying to receive a green checkmark for the comparison "1$ < 2$", it is important to prioritize testing combinations that are relevant to your specific scenario. Consider whether comparing dollars with euros should be allowed or prohibited. Both outcomes are valid and warrant thorough testing. In addition to investigating unusual combinations of value object properties, it is crucial to pay attention to edge values. These values are often not covered by property-based testing, which typically generates "well-behaved" values. Focusing on these edge cases will help ensure comprehensive test coverage.

Domain-specific assertions are better avoided in my expirience, mainly for these reasons: 1. Non-trivial: Assertions often rely heavily on the specifics of the framework, requiring a deep understanding for creating and maintanance. 2. Difficult to change: They tend to be used inherently on many places, making changes challenging without introducing regressions. They tend to bloat with options & customizations for individual needs. 3. Lack of clarity and reviewability: Unlike explicit assertions, domain-specific assertions can be harder to name, understand, review, and maintain. While they specify the WHAT, the HOW is "implementation detail", where bugs breed. It is important to consider these factors.

In the case of a Money value object, assert that currency conversion follows the expected rules: [Fact] public void TestMoneyCurrencyConversion() { var moneyUsd = new Money(100, "USD"); var moneyEur = moneyUsd.ConvertCurrency("EUR", 0.85); Assert.Equal(85, moneyEur.Amount); Assert.Equal("EUR", moneyEur.Currency); }

It is important to reassess the value object API and question its initial assumptions. Don't settle for the first guess; instead, continuously challenge the purpose and usage over time. Pay careful attention to how the object is utilized within the codebase and take a step back to evaluate if it aligns with the intended usage. Seek feedback from your team to avoid tunnel vision and gain different perspectives. It is common for junior developers to gravitate towards obscure APIs when working on new use cases, rather than considering the existing abstractions within the codebase. Encourage a mindset that promotes thoughtful abstraction and understanding of the broader context.

Neglecting to use value objects for relevant data in your application can lead to pitfalls such as duplicated knowledge and unclear testing responsibilities. On the other hand, utilizing them in inappropriate scenarios can introduce unnecessary abstractions that hinder development. Instead, leverage the capabilities of your standard library and employ value objects only when they provide genuine value. For instance, if your requirement is simply to compare dates and serialize them into an ISO string, creating a value object for it might be excessive, potentially causing unnecessary complexities in very near future. It's important to strike a balance and assess the actual benefits before incorporating value objects into your codebase.