Enhancing Unit Testing in SAP CAP Java Applications with GitHub Copilot

Introduction
Building upon SAP’s guide to unit testing in CAP Java, this post explores how GitHub Copilot can streamline and accelerate the process of writing unit tests in SAP Cloud Application Programming (CAP) Java projects.

GitHub Copilot is an AI-powered coding assistant developed by GitHub and OpenAI. It helps developers by suggesting code snippets, functions, and even entire test cases in real time, based on the context of what you’re writing. Integrated into popular code editors, it speeds up development and reduces repetitive tasks.

Where GitHub Copilot Helps
GitHub Copilot assists by:

Autocompleting test scaLoldsSuggesting assertion logicHandling repetitive boilerplate (e.g., mocks and setup)Speeding up TDD cycles (Red → Green → Refactor)

How GitHub Copilot Can Help in Writing TDD Test Cases

In the context of SAP CAP Java, GitHub Copilot streamlines the process of writing unit tests, allowing developers to focus on defining behaviour and business logic.
Below we will demonstrate the example using a test case from SAP’s guide to unit testing in CAP Java. The test case is part of the method “validateBookAndDecreaseStock” , which was introduced and tested manually in this post.

Let’s now see how GitHub Copilot helps implement the same scenario using a TDD approach, covering prompts, completions, and code refinements.

Scenario: Book Does Not Exist – We want to write a test for the case where a book ID in an order does not exist in the database.

Red – Write the Failing Test First

Prompt Example:

“Write a JUnit 5 test for validateBookAndDecreaseStock(List<OrderItems>) when the book does not exist. Mock the persistence service to return empty result. Expect Service Exception with message – Book does not exist”

Copilot Suggestion:

This gives us a strong starting point — the structure, mocking, and assertions are generated instantly. We can now refine or expand it as needed.

 Green – Implement Minimal Code to Pass the Test

Once the test is in place and failing, we write just enough application code to make it pass.
How Copilot Helps:
• Copilot can suggest the implementation stub or completion for the service method.
• It recognizes context (e.g., entity names like Books, usage of persistence Service, and typical CAP patterns).

Prompt Example:

“Implement the validateBookAndDecreaseStock method so it throws a Service Exception when the book is not found.”

Copilot Suggestion:

While still minimal, this satisfies the failing test and progresses the TDD loop.

 Refactor – Clean and Improve Code

Once the test passes, the code can be cleaned up. Copilot can assist by:
1. Suggesting improved variable naming

2. Identifying reusable logic (e.g., extracting methods)
3. Completing more idiomatic Java or CAP Java constructs

Prompt Example:

“Refactor validateBookAndDecreaseStock to extract book lookup into a separate private method.”

Copilot Suggestion:

GitHub Copilot provides several other ways to improve our development workflow. Below is a table showcasing additional use cases and how it can support us throughout the process:

Way Copilot Helps

Description

Prompting

Provides code suggestions based on the context of your work, helping you quickly generate code snippets and complete tasks.

Auto-completion

Suggests auto-completions for common code patterns like variable declarations, method signatures, or class instantiations, reducing the need to write repetitive code.

Refactoring Suggestions

Suggests improvements in code structure, like method extraction or renaming variables, for cleaner and more maintainable code.

Context-Aware Suggestions

Generates code that fits with the specific libraries or frameworks you’re using, ensuring adherence to best practices.

Error Handling Recommendations

Helps identify and handle potential exceptions or edge cases by suggesting relevant error handling and assertions.

Conclusion

In conclusion, GitHub Copilot significantly enhances the unit testing process in SAP CAP Java applications by providing real-time code suggestions, automating repetitive tasks, and ensuring comprehensive test coverage. By streamlining the creation of test cases, mocking dependencies, and improving code structure, Copilot accelerates the TDD workflow, allowing developers to focus more on business logic and less on boilerplate code. Its ability to suggest improvements and handle edge cases ultimately leads to cleaner, more maintainable code and a more efficient development process.

Disclaimer

The views and opinions expressed in this blog post are those of the author and do not necessarily reflect the official policy or position of SAP or its affiliates. This content is provided for informational purposes only, based on the author’s personal experience and understanding.

This blog references the use of GitHub Copilot, an AI-powered coding assistant. The suggestions generated by Copilot are not guaranteed to be accurate, complete, secure, or compliant with any specific coding standards or organizational policies. Developers are responsible for reviewing, validating, and testing all code before use in any production or sensitive environment.

SAP makes no representations or warranties, express or implied, regarding the suitability or accuracy of the information or tools mentioned herein.

​ IntroductionBuilding upon SAP’s guide to unit testing in CAP Java, this post explores how GitHub Copilot can streamline and accelerate the process of writing unit tests in SAP Cloud Application Programming (CAP) Java projects.GitHub Copilot is an AI-powered coding assistant developed by GitHub and OpenAI. It helps developers by suggesting code snippets, functions, and even entire test cases in real time, based on the context of what you’re writing. Integrated into popular code editors, it speeds up development and reduces repetitive tasks.Where GitHub Copilot HelpsGitHub Copilot assists by:Autocompleting test scaLoldsSuggesting assertion logicHandling repetitive boilerplate (e.g., mocks and setup)Speeding up TDD cycles (Red → Green → Refactor)How GitHub Copilot Can Help in Writing TDD Test CasesIn the context of SAP CAP Java, GitHub Copilot streamlines the process of writing unit tests, allowing developers to focus on defining behaviour and business logic.Below we will demonstrate the example using a test case from SAP’s guide to unit testing in CAP Java. The test case is part of the method “validateBookAndDecreaseStock” , which was introduced and tested manually in this post.Let’s now see how GitHub Copilot helps implement the same scenario using a TDD approach, covering prompts, completions, and code refinements.Scenario: Book Does Not Exist – We want to write a test for the case where a book ID in an order does not exist in the database.Red – Write the Failing Test FirstPrompt Example:”Write a JUnit 5 test for validateBookAndDecreaseStock(List<OrderItems>) when the book does not exist. Mock the persistence service to return empty result. Expect Service Exception with message – Book does not exist”Copilot Suggestion:This gives us a strong starting point — the structure, mocking, and assertions are generated instantly. We can now refine or expand it as needed. Green – Implement Minimal Code to Pass the TestOnce the test is in place and failing, we write just enough application code to make it pass.How Copilot Helps:• Copilot can suggest the implementation stub or completion for the service method.• It recognizes context (e.g., entity names like Books, usage of persistence Service, and typical CAP patterns).Prompt Example:“Implement the validateBookAndDecreaseStock method so it throws a Service Exception when the book is not found.”Copilot Suggestion:While still minimal, this satisfies the failing test and progresses the TDD loop. Refactor – Clean and Improve CodeOnce the test passes, the code can be cleaned up. Copilot can assist by:1. Suggesting improved variable naming2. Identifying reusable logic (e.g., extracting methods)3. Completing more idiomatic Java or CAP Java constructsPrompt Example:”Refactor validateBookAndDecreaseStock to extract book lookup into a separate private method.”Copilot Suggestion:GitHub Copilot provides several other ways to improve our development workflow. Below is a table showcasing additional use cases and how it can support us throughout the process:Way Copilot HelpsDescriptionPromptingProvides code suggestions based on the context of your work, helping you quickly generate code snippets and complete tasks.Auto-completionSuggests auto-completions for common code patterns like variable declarations, method signatures, or class instantiations, reducing the need to write repetitive code.Refactoring SuggestionsSuggests improvements in code structure, like method extraction or renaming variables, for cleaner and more maintainable code.Context-Aware SuggestionsGenerates code that fits with the specific libraries or frameworks you’re using, ensuring adherence to best practices.Error Handling RecommendationsHelps identify and handle potential exceptions or edge cases by suggesting relevant error handling and assertions. ConclusionIn conclusion, GitHub Copilot significantly enhances the unit testing process in SAP CAP Java applications by providing real-time code suggestions, automating repetitive tasks, and ensuring comprehensive test coverage. By streamlining the creation of test cases, mocking dependencies, and improving code structure, Copilot accelerates the TDD workflow, allowing developers to focus more on business logic and less on boilerplate code. Its ability to suggest improvements and handle edge cases ultimately leads to cleaner, more maintainable code and a more efficient development process.DisclaimerThe views and opinions expressed in this blog post are those of the author and do not necessarily reflect the official policy or position of SAP or its affiliates. This content is provided for informational purposes only, based on the author’s personal experience and understanding.This blog references the use of GitHub Copilot, an AI-powered coding assistant. The suggestions generated by Copilot are not guaranteed to be accurate, complete, secure, or compliant with any specific coding standards or organizational policies. Developers are responsible for reviewing, validating, and testing all code before use in any production or sensitive environment.SAP makes no representations or warranties, express or implied, regarding the suitability or accuracy of the information or tools mentioned herein.   Read More Technology Blog Posts by SAP articles 

#SAP

#SAPTechnologyblog