OpenText DevOps Aviator and GitHub Copilot Extensions
Unlock trusted AI for faster, safer software delivery in enterprise DevOps
Challenges in Enterprise DevOps
Organizations in highly regulated and complex industries—such as automotive, finance, and healthcare—face significant challenges in software delivery. Manual documentation, fragmented test generation, and siloed defect tracking slow down development and complicate compliance within iterative, fast-paced release cycles.
Introducing OpenText DevOps Aviator and GitHub Copilot Extensions
OpenText™ DevOps Aviator™, now integrated with GitHub Copilot Extensions, transforms how teams manage these challenges. As part of the OpenText™ Core Software Delivery Platform, this combined solution embeds AI for DevOps, empowering developers to accelerate delivery without compromising on quality, traceability, or compliance.
Using natural language prompts, developers can automatically generate functional and compliance-ready tests, create accurate documentation on the fly, and decompose complex features into clear, manageable tasks. All of this happens within the developer's native workflow—streamlining processes, surfacing risks early through proactive testing, and enhancing overall delivery efficiency.
Key Benefits
- Unify and streamline automated UI testing
- Fortify CI/CD pipelines with built-in security
- Boost workflow productivity and control
- Resolve defects seamlessly with contextual insights
- Clarify requirements for testable outcomes
Detailed Capabilities
AI-generated UI testing
Leverage Java and Selenium to automate UI testing, significantly reducing manual effort and potential errors in your testing processes.
AI-generated unit testing
Implement JUnit tests to rigorously validate every fix, ensuring functionality and preventing regressions.
BDD requirements generation
Transform ambiguous instructions into structured, executable BDD scenarios using Gherkin syntax, ensuring precise test coverage and rapid validation.
Defect analysis
Convert bug reports and discussions into clear, actionable steps, enabling quick and accurate issue resolution.
Task generation
Break down complex features into smaller, well-defined tasks, simplifying project management and execution.
Vulnerability detection
Integrate STRIDE-based threat modeling directly into your CI/CD pipeline to identify and mitigate security risks early in the development cycle.
OpenText DevOps Aviator Deployment Options
Run anywhere and scale globally in the OpenText public cloud.
DevOps Aviator runs on the OpenText Core Software Delivery Platform in the OpenText Public Cloud with a user subscription.
AI in Action: Practical Examples
Breaking User Stories into Tasks
The system assists in decomposing complex user stories into smaller, manageable tasks. For instance, a story identified as '[SDM/SDP Shift] Initial Analysis for Entity Filtering in Shift's GUI' can be broken down into specific tasks such as analyzing existing entity selector logic, designing the GUI for entity filtering, defining necessary data structures and API endpoints, conducting STRIDE threat modeling, assessing performance implications, and creating a comprehensive technical design document.
Generating Automated Test Suggestions
AI provides suggestions for automated tests using Java. This includes setting up WebDriver (e.g., ChromeDriver), maximizing the browser window for consistent behavior, implementing explicit waits, navigating to the application's GUI, and interacting with elements like entity selectors. Example code snippets demonstrate how to write unit tests for functionality, such as entity selection within the Shift GUI, ensuring rigorous validation of fixes.
Suggesting Strategies to Fix Defects
AI can suggest strategies to fix defects. For a defect such as '[SDM/SDP Shift] Users migrated as default user and not flagged by integrity check', a suggested strategy involves a two-pronged approach: Phase 1 (Mitigation) includes enhanced logging for default user mappings during migration and user notifications, while Phase 2 (Resolution) focuses on implementing long-term user mapping functionality.
