Glossary
To help you get the most out of Pie and understand the world of software quality, here’s a list of key terms.
AI Agent: The autonomous software that explores your app, executes tests, and analyzes results.
Assertion: A check within a test case to verify that a specific condition is true.
Example: After clicking “Login,” an assertion would be “Verify the user is on the dashboard screen.”Bug (or Defect): An error or flaw in the application that causes it to produce an incorrect or unexpected result.
CI/CD (Continuous Integration/Continuous Deployment): The practice of frequently merging code changes into a central repository (CI) and then automatically releasing them (CD). Pie integrates into this pipeline to automate testing for every change.
Contextual Model: The AI’s internal, structured representation of an application. It serves as a comprehensive map of the app’s screens, UI elements, features, and their relationships, enabling contextual understanding and self-healing tests.
Discovery: The initial automated crawl where an AI Agent builds the Contextual Model.
End-to-End (E2E) Testing: A testing method that validates an application’s workflow from beginning to end, mimicking a real user journey. Pie specializes in autonomous E2E testing.
Finding: A single, raw instance of a potential bug detected by an AI Agent.
Functional Testing: Testing that verifies the application’s features work according to their specified requirements. It answers the question: “Does this feature do what it’s supposed to do?”
Issue: A curated, deduplicated report representing a unique, underlying bug, created by grouping related findings.
Readiness Score: An overall quality metric (0–100%) summarizing a build’s health for a go/no-go decision.
Regression Testing: The process of re-running tests to ensure that recently added code changes have not broken any existing functionality. Pie automates this entirely.
Self-Healing Test: A test that automatically adapts to UI changes, eliminating test maintenance.
Severity vs. Priority:
- Severity: Measures the technical impact of a bug on the application (e.g., a “Critical” severity bug might be a crash).
- Priority: Measures the urgency of fixing the bug from a business perspective (e.g., a typo on the homepage might be “Low” severity but “High” priority).
Smoke Testing: A preliminary set of tests run on a new build to ensure its most critical functionalities are working. A failed smoke test usually means the build is rejected immediately.
Usability Testing: Testing focused on how easy and intuitive the application is for a real user. Pie’s AI can identify usability issues like confusing navigation or poorly designed layouts.