Audible, an Amazon company, is a leading producer and provider of audio storytelling. With a vast library of over 1,000,000 titles, including audiobooks, podcasts, and Audible Originals, each marketplace offers curated selections. Audible makes it easy to transform everyday moments into extraordinary opportunities for learning, imagination, and entertainment through immersive audio experiences. Robust testing is critical to ensure millions of end users enjoy a seamless experience across devices.
Remember the last time you inherited a software application codebase with minimal test coverage? Or perhaps you’ve written code in a rush to meet a deadline, promising yourself you’d add tests “later”? We’ve all been there. Testing is crucial but can often gets deprioritized when deadlines loom. That’s where Amazon Q Developer‘s agentic workflows come in, transforming the way developers approach test generation. This blog explores how Audible used Amazon Q Developer to boost their unit test coverage.
Business Use Case for Software Testing
In high velocity development environments, testing cycles can often times get compressed under tight deadlines, increasing quality risks. Amazon Q Developer transforms this paradigm by accelerating testing while maintaining comprehensive standards. Through automated test generation, edge case identification, and fix suggestions, teams execute thorough testing in reduced timeframes, delivering expedited releases, optimized QA resources, and enhanced production readiness.
Each function that does not have the appropriate testing implemented, represents the potential for a rework, bugs, and maintenance challenges. Additionally, inherited codebases present particular challenges: developers must choose between spending weeks writing tests for existing functionality or continuing the cycle of untested code.
Amazon Q Developer addresses these challenges by reducing the time and effort required for proper test coverage, transforming testing from a burdensome chore into a streamlined process that allows teams to focus on delivering new features while helping to ensure code quality.
Amazon Q Developer: Expanding test coverage for your codebase
Amazon Q Developer introduces an advanced approach to software testing generation through its agentic workflows. Unlike traditional test generation tools that produce generic tests, Amazon Q Developer analyzes your code’s intent, business logic, and edge cases. It doesn’t just generate tests; it creates meaningful test suites that validate your code’s behavior comprehensively.
Beyond the dedicated test generation workflow we’ll explore today, Amazon Q Developer offers multiple ways to assist with testing. You can use conversational prompts for test plan generation, request test improvements for existing code, or even pair-program with Amazon Q Developer as you write tests. The flexibility to integrate AI assistance throughout your testing workflow makes Amazon Q Developer a versatile companion for developers.
Amazon Q Developer workflow architecture
The following architecture diagram illustrates how Audible leveraged Amazon Q Developer for both test generation and code transformation:
The Amazon Q Developer workflow demonstrates two key capabilities:
- Test Generation: Amazon Q Developer analyzes Java classes and creates comprehensive test suites including unit tests, edge case tests, and exception handling tests.
- Code Transformation: Amazon Q Developer performs automated migration tasks including
JDK 8toJDK 17/21upgrades, handling language version compatibility,JUnit 4toJUnit 5conversion, modernizing test framework syntax and annotations, syntax migration, updating deprecated APIs and code patterns.
What makes this workflow particularly powerful is how it combines AI capabilities with human expertise, allowing expert developers to leverage AI in their day-to-day workflow. Amazon Q Developer analyzes your codebase and uses it as a context, identifies edge cases, and performs automated transformations, while developers apply their domain knowledge to ensure the outputs align with business requirements and expected behavior.
Audible’s Approach to harness the potential of Amazon Q Developer
The Audible teams followed the below steps to harness Amazon Q Developer to boost test coverage.
Code Submission: The Audible team leveraged Amazon Q Developer to enhance their test coverage by generating additional unit tests for Java classes, including static methods and methods with existing test cases. This approach complemented their robust testing strategy. Amazon Q Developer has the ability to examine classes, methods, parameters, return types, and exceptions. Amazon Q Developer is helpful in automatically identifying unit tests to cover edge cases that can easily be overlooked, such as null input checks and empty string checks.
Targeted Requests: The Audible team specifically asked Amazon Q Developer to provide:
- Suggestions for unit tests to cover the given method within a Java class
- Recommendations for unit tests targeting untested edge cases
- Recommendations for test cases addressing error handling and exception scenarios
The Audible team achieved significant improvements using Amazon Q Developer for both test generation and code transformation. The key to their success was providing rich context along with targeted prompts in a systematic workflow.
Developer Workflow
Audible adopts a human in the loop approach to review the output from automation tools. The above workflow shows the complete process: (1) open a class file in their IDE, (2) select a specific method and add their prompt, (3) submit this combined context to Amazon Q Developer, (4) receive generated tests, and (5) review and integrate the tests into their codebase.
Effective Prompts and Approach
The Audible team followed a structured approach, using targeted requests that Amazon Q Developer could act upon:
Code Submission: The team provided Java classes to Amazon Q Developer with code to generate tests for individual methods, including static methods and those that already had some tests but lacked full coverage. Amazon Q Developer examined classes, methods, parameters, return types, and exceptions, automatically identifying unit tests to cover edge cases like null input checks and empty string checks.
Below are generic Sample Prompts for Specific Requests:
Please include tests for: – Valid input scenarios – Null input checks – Empty string validations – Exception handling
Note: While Amazon Q Developer’s code transformation feature can handle
JUnit4toJUnit5migration automatically across entire codebases, Audible also used the conversational interface for manual, targeted conversions as shown above. Both approaches are available. Refer to documentation for automated transformation details.
Test Generation: Based on the team’s requests, Amazon Q Developer generated specific test suggestions addressing these areas with appropriate assertions and test methods.
Implementation: The development team implemented the suggested tests after review.
Documentation: Amazon Q Developer has the ability to add comments to explain the purpose of the test, area of the functionality that the test is covering. In addition, Amazon Q Developer also has the ability to generate documentation related to other aspects like read-me files and project documentation.
Quantifiable Results
By leveraging Amazon Q Developer, the Audible team achieved:
- Over 10 key packages received comprehensive unit test coverage
- ~1 hour saved per test class (typically containing 8-10 individual tests)
- 5,000+ test cases successfully migrated from
JUnit4toJUnit5using both Amazon Q Developer’s code transformation and manual conversational assistance - 50+ hours of manual work saved during the
JDK8toJDK17migration using Amazon Q Developer’s code transformation - Reduced human errors through AI-assisted transformations
Key Capabilities Demonstrated
Amazon Q Developer excelled in several areas that can be overlooked in manual testing:
Comprehensive Exception Testing: Beyond standard null input checks and empty string validations, it automatically suggested tests for IllegalArgumentException, NullPointerException, and custom business exceptions, including verification of both exception throwing and specific error messages. This systematic approach made test coverage more complete and error handling more robust.
Automated Edge Case Detection: Amazon Q Developer made inline suggestions for null pointer exception handling without prompting, making the process smoother and faster.
Manual Framework Migration with AI Assistance: Amazon Q Developer’s pattern recognition accelerated the migration process through conversational assistance. The team could ask Amazon Q Developer through the chat to convert test syntax from JUnit4 to JUnit5 manually. For example, their previous setup had JUnit4 syntax with @UseDataProvider and @DataProvider annotations. All they had to do was highlight the code block, Send to Prompt, and ask Amazon Q Developer to make the test JUnit5 compatible. Within seconds, it generated a reliable JUnit5 test with ParameterizedTest annotation and Stream of Arguments that they could manually implement.
Contextual Analysis: Amazon Q Developer analyzes the existing codebase and recognized patterns and generated tests that matched the team’s coding style and testing conventions.
Conclusion
Amazon Q Developer transforms the test generation process from a time-consuming chore into a streamlined workflow, enabling teams to achieve comprehensive test coverage with minimal effort. This allows developers to focus on higher-value activities while improving code quality and reliability.
The business impact is substantial: As testing becomes less burdensome, teams naturally adopt better testing practices, creating a positive feedback loop that enhances overall code quality, and creates an opportunity for faster development cycles, and reduced time spent on maintenance.
