Test automation

Modern enterprise applications require an integrated approach to quality that traditional post-development testing cannot provide. Historically, testing was manual, reactive, and caused delays. Pega Platform addresses these limitations by embedding quality throughout the development lifecycle. This AI-augmented quality engineering approach treats testing as a continuous, intelligent activity that adapts to evolving business needs.

With Pega Platform, this shift is amplified through predictable AI agents, generative AI-powered test generation, and governed automation that ensures every AI-assisted action is traceable and auditable. Pega combines reasoning AI at design time with deterministic, governed automation at run time, creating a reliable and explainable testing ecosystem.

Generative AI, design-aligned test coverage, and automated CI/CD workflows enable earlier validation, faster feedback, and consistent alignment with critical business logic. These features reduce defect risk, improve delivery efficiency, and support predictable application quality.

AI-augmented quality engineering includes the following key pillars:

• Continuous quality: Validation begins during design and continues through deployment to ensure consistent coverage.
• AI-driven automation: AI assists with test generation, test data creation, and suite management to reduce manual effort and accelerate feedback cycles.
• Blueprint integration: Microjourneys® and design artifacts guide test coverage to maintain alignment with intended business behavior.
• Governance and explainability: Predictable AI agents and the Agent Tracer enable full auditability of AI-driven logic used in testing or run-time decisions to help provide safe, compliant, and reliable automation at scale.

Unit tests in Pega validate individual rules, which are the smallest units of application logic. These tests detect configuration issues early and support reliable, low-risk changes. As the most cost-effective layer of the test pyramid, unit tests should run frequently. Lead System Architects promote a “test early and often” approach to maintain quality.

Pega Platform supports parallel test runs through the PegaUnit API. This feature allows multiple test cases to run at the same time, which reduces the overall test duration in CI pipelines.

Use these Pega Platform features to strengthen unit testing:

• PegaUnit framework: Provides reusable test cases for multiple rule types. The framework supports assertions, setup and cleanup routines, simulations, test suites, and CI/CD execution. Tests can run locally or in automated pipelines without user interaction.
• Run/record to test Case: Converts ad hoc rule runs or process recordings into stable, versionable test cases with defined assertions and controlled data setup. This feature transforms ad hoc runs, such as running an activity from Dev Studio, into structured test cases that are distinct from UI interaction recordings.
• Design alignment: Organize unit tests around Microjourneys and evolving business rules to ensure coverage remains aligned with application design and scales effectively.

For more information, see PegaUnit testing.

UI functional and scenario tests validate end-to-end user journeys and expected UI behavior. As the highest layer of the test pyramid, these tests should focus on critical flows because they require more maintenance. Reliability improves when you use stable selectors and well-defined assertions.

Use these Pega Platform features to support UI functional and scenario testing:

• Scenario testing: Record UI interactions within the application, store tests in a dedicated Ruleset, add explicit assertions, and manage suites and coverage through a centralized landing page.
• Pipeline integration: Run recorded scenario tests in CI/CD pipelines by using REST endpoints or Deployment Manager tasks. When invoked from Deployment Manager, tests run through Selenium or supported cloud providers such as BrowserStack, Sauce Labs, CBT, or standalone grids.
• Constellation support: Constellation’s structured design system and TestID-based selectors provide stable locators, improving the resilience of UI automation across updates.
• AI-assisted authoring: Pega Autopilot™ can generate Business Actions and Application Tests that include UI automation (Playwright) and API steps. This approach keeps UI test coverage aligned with business workflows and simplifies maintenance.

For more information, see Tools for testing the UI.

You can use the TestID property to uniquely identify a user interface element. This approach enables dependable automated UI-based tests for any Pega Platform application.

API tests validate backend case processing and integrations without the UI. These tests provide fast regression coverage and maintain stability when the front end changes. Favor API tests for headless validations, orchestration paths, and integration contracts because they represent the middle tier of the test pyramid.

Use these Pega Platform features to support API testing:

• Pega API and DX API: Use model-driven, versioned REST endpoints to create and progress Cases or assignments and render UX metadata for custom front ends. This approach keeps channel logic centralized and minimizes UI fragility.
• Generative AI/Autopilot authoring: Autopilot can generate Application Tests that include API steps matched to Business Actions, keeping headless tests aligned with Case lifecycle goals.
• Pipeline integration: Run API suites in Deployment Manager or CI tools to enforce integration contracts, perform security checks, and gate promotions.

For more information, see Integrating with APIs and services.

An automation test suite should combine unit, API, and UI tests following the test pyramid: a large number of fast unit and API tests, complemented by a smaller set of critical UI scenarios. Suites should run early, continuously, and automatically to detect regressions and maintain alignment with application design.

Pega Platform uses governed pipelines in Deployment Manager with support for parallel Pega Unit runs, Autopilot-generated test suites, and security and performance quality gates built into the release workflow.

Integration with CI/CD and Deployment Manager supports continuous testing and predictable releases. Generated Playwright test scripts integrate with standard CI/CD pipelines. Playwright-based automation works with tools such as Jenkins and Deployment Manager. Deployment Manager can trigger Jenkins jobs to run Playwright scripts as part of the pipeline. Automated quality gates ensure tests run before promoting changes to the next environment. These features enable continuous integration and deployment with reliable outcomes.

Deployment Manager now supports parallel PegaUnit runs, Autopilot-generated API and UI Application Tests, and expanded quality gate governance for more predictable releases.

Use these Pega Platform features to manage automated test suites:

• Deployment Manager and CI/CD: Run different test sets at appropriate stages—unit and integration tests during CI, broader regression tests during CD—while applying quality gates for guardrails and test results.
• Scenario test orchestration: Run recorded UI suites by using Deployment Manager tasks or REST endpoints with Selenium Grid or supported browser providers, while capturing history and coverage.
• AI-assisted suite maintenance: Autopilot can generate business actions and application tests to expand test coverage and reduce manual scripting effort, with the option to refine generated Playwright code.

Non-functional testing ensures that an application meets performance, security, accessibility, and reliability expectations beyond functional correctness. In Pega Platform, these tests are embedded in CI/CD pipelines, supported by Predictive Diagnostic Cloud (PDC), and complemented by automated compliance checks for continuous oversight.

Types of non-functional testing include:

• Performance: Measures responsiveness and speed under normal and peak loads.
• Load: Verifies system stability under varying transaction volumes and user counts.
• Usability: Evaluates user-friendliness and accessibility.
• Compatibility: Validates behavior across browsers, devices, and environments.
• Security: Detects vulnerabilities and ensures compliance with security standards.
• Scalability: Evaluates system behavior as user demand and data volume grow.
• Portability: Assesses how easily the application can be moved or deployed across different environments.
• Disaster recovery: Determines how effectively the system restores functionality after failures or unexpected disruptions.

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