Effective Strategies for Testing Complex Calculations in Software Development

Effective Strategies for Testing Complex Calculations in Software Development

3 July 2024 Stephan Petzl Leave a comment QA

Testing complex calculations in software development can be challenging, especially when both manual and automated quality assurance (QA) methods are involved. This guide provides a comprehensive approach to ensure the accuracy and reliability of such calculations, drawing from best practices and expert recommendations.

Understanding the Basics

All engineers, whether application developers or automation testers, typically test algorithms by providing known inputs and verifying the expected outputs. This verification can be achieved through manual calculations or by utilizing different algorithms.

Approaches to Testing Complex Calculations

Manual Calculations and Alternative Algorithms

One effective method is to perform manual calculations to establish expected results. Alternatively, different algorithms can be used to cross-verify the outputs. This dual approach helps in identifying discrepancies and ensuring the reliability of the calculations.

Behaviour-Driven Development (BDD)

Another approach is Behaviour-Driven Development (BDD), which involves testing the algorithm with simple inputs and gradually increasing the complexity. For example, start by verifying the output for an input of “1”, then “2”, and so on. This method helps in discovering the design and ensuring that the algorithm behaves as expected across a range of inputs.

Test-Driven Development (TDD)

Test-Driven Development (TDD) is also a valuable approach. By breaking down complex calculations into smaller, manageable steps, you can test each part separately. For instance, a calculation like (1 + 2) / 3 can be divided into two steps: addition and division. Conducting end-to-end tests for these smaller parts reduces the likelihood of errors.

Peer Review and Cross-Validation

Peer review is essential for verifying the correctness of formulas and calculations. Creating a table with inputs and expected outputs using tools like Excel can help in comparing results. Testing inputs at or near boundary values ensures that the algorithm handles edge cases effectively.

Advanced Testing Techniques

Contract Testing

For stored procedures, contract testing can be employed. This involves using a set of intelligently mutated input and output pairs to focus on the specific effects of the procedure, rather than on SQL quirks.

Property Testing

Property testing is useful for functions with highly variable parameters. This method attempts to run all meaningful combinations of inputs and observes specific properties, such as uniqueness or entropy, to ensure the function behaves correctly.

Practical Example

Consider a scenario where you need to test a complex financial calculation. You might start with simple, known inputs and verify the outputs manually. Next, use an alternative algorithm to cross-check the results. Implement BDD to test the calculation incrementally, and use TDD to break down the calculation into smaller steps. Finally, employ peer review and property testing to validate the results comprehensively.

Leveraging Automated Testing Tools

Automated testing tools can significantly streamline the testing process. For instance, virtual test devices can be used to simulate various input scenarios, while test exception handling ensures that edge cases are managed effectively.

Enhancing Testing with Repeato

For those looking to simplify and expedite their testing processes, Repeato offers a no-code test automation tool for iOS and Android. Leveraging computer vision and AI, Repeato allows you to create, run, and maintain automated tests quickly and efficiently. This can be particularly beneficial for testing complex calculations, as it reduces the time and effort required to verify outputs across a range of inputs. Learn more about Repeato’s capabilities here.

By following these strategies and utilizing the right tools, you can ensure the accuracy and reliability of complex calculations in your software projects.

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