Accelerating DevOps maturity through automated test coverage
An Australia-based logistics leader tackled DevOps challenges by boosting unit test coverage across legacy systems, overcoming resource limits and code complexity to advance its transformation goals.
The challenge
The organization faced significant hurdles in improving its DevOps maturity, particularly around unit test coverage. Key challenges included:
- Large volumes of legacy source code that are spread across multiple IT landscapes
- A target mandate to raise unit test coverage to 80% across all source files
- Limited developer bandwidth, with most resources focused on ongoing projects and BAU activities
- Developers lacked familiarity with legacy codebases, requiring additional time to understand complex logic before writing unit tests
These issues created bottlenecks in achieving higher test coverage and risked delaying the overall DevOps transformation agenda.
The objective
To accelerate the creation of unit tests for legacy code without overburdening developers, an automated approach was required that could reduce manual effort, minimize ramp-up time on unfamiliar codebases and support bulk test generation to meet coverage targets efficiently.
The solution
A Python-powered automation framework was developed to streamline the process:
- Bulk upload capability: Developers can upload multiple source files at once into the system
- One-click unit test generation: With a single action, the script generates comprehensive unit test cases for all uploaded files
- AI-powered logic understanding: By leveraging large language models, the system interprets the source logic, enabling the automated creation of meaningful unit tests aligned to coverage goals
- Developer-friendly: The generated tests can be refined, executed and integrated into existing CI/CD pipelines, ensuring smooth adoption
The impact
The solution delivered substantial improvements in efficiency and coverage:
- Rapid increase in unit test coverage towards the 80% target without consuming extensive developer hours
- Freed up developer capacity to focus on higher-value BAU and project activities.
- Reduced dependency on deep legacy code knowledge by automating logic interpretation
- Accelerated DevOps maturity through consistent, scalable and automated unit test generation
- Established a repeatable framework that can be extended to future codebases and evolving coverage goals
AWS services used
- Amazon Bedrock
- AWS CloudTrail
- Amazon CloudWatch
- Amazon VPC
