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Education LearningTop 10 Best Testing Pyramid Software of 2026
Ranked testing pyramid software for QA teams with side-by-side comparison of PactFlow, TestComplete, and Sauce Labs, plus key tradeoffs.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
PactFlow is the best fit for QA teams that need automated API contract checks wired into CI gates, while SmartBear TestComplete is a stronger alternative when you’re focused on controlled end-to-end UI regression automation with scripted extensibility.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
PactFlow
PactFlow manages consumer-to-provider pact lifecycle with verification status that QA can gate in CI.
Built for fits when QA teams need automated API contract checks wired into CI gates..
SmartBear TestComplete
Editor pickTestComplete’s built-in test object recognition maps UI elements into an object model for action reuse across builds.
Built for fits when QA teams need controlled end-to-end UI regression automation with scripted extensibility..
Sauce Labs
Editor pickJob provisioning and remote execution are controllable through Sauce Labs APIs for pipeline and custom orchestration.
Built for fits when browser-based QA suites need controlled environment variety with API-driven pipeline execution..
Comparison Table
PactFlow
API-firstContract testing software manages Pact contracts, verification results, and deployment checks.
PactFlow manages consumer-to-provider pact lifecycle with verification status that QA can gate in CI.
PactFlow’s core loop centers on publishing versioned pacts from consumer tests and then verifying those pacts in provider test runs. The product’s integration depth shows up in its CI-friendly execution model and in its ability to connect verification results to repository checks for fast feedback.
A key tradeoff is that it focuses on API contracts rather than orchestrating end-to-end browser or UI test suites. PactFlow fits best when contract boundaries can stabilize quickly and when provider pipelines can run verification frequently enough to keep the feedback loop tight.
- +Automates consumer contract publishing and provider verification across CI
- +Produces actionable verification output for pull request quality gates
- +Supports extensibility for custom matchers and contract rules
- +Fits contract-first workflows with clear consumer to provider traceability
- –Concentrates on API contracts instead of full UI end-to-end coverage
- –Requires disciplined contract versioning to prevent noisy failures
- –Test determinism depends on stable provider test environments
- –Setup effort rises when teams split contracts across many services
QA leads in microservices
Gate provider changes with pact verification
Fewer integration regressions
API platform engineering
Standardize contract testing across teams
Repeatable contract coverage
Show 2 more scenarios
Test automation engineers
Validate dynamic fields using matchers
Reduced false failures
Custom matchers encode allowed variability so providers can change safely.
Release managers
Track contract status per environment
More predictable deployments
Verification outputs provide roll-forward signals for release readiness in CI.
Best for: Fits when QA teams need automated API contract checks wired into CI gates.
SmartBear TestComplete
enterpriseUI automation supports web, desktop, and mobile application testing with script and keyword modes.
TestComplete’s built-in test object recognition maps UI elements into an object model for action reuse across builds.
TestComplete targets end-to-end test execution for desktop and web user interfaces with object recognition, checkpointing, and built-in test runners. It supports data-driven testing via parameterization and external data binding, which helps keep scenarios consistent while varying inputs. Automation can be extended by writing custom code around test lifecycle hooks and custom logging so test context stays attached to each run.
A tradeoff is that maintaining stable UI selectors often requires active governance when screens and controls change frequently. It fits teams that need fast authoring for UI regression checks and have clear rules for when to add UI tests versus lower-level tests.
- +Strong UI object model enables resilient control-level actions
- +Multiple scripting languages support team-specific automation standards
- +Data-driven runs reduce scenario duplication across regression suites
- +CI integration supports automated execution and build-based reporting
- –UI locator maintenance increases overhead during frequent UI churn
- –Best results depend on disciplined test isolation and environment control
- –API depth for programmatic test management can lag UI-first workflows
- –Scalability tuning for large suites requires careful parallel settings
Enterprise QA teams
UI regression checks after releases
Fewer release-day UI defects
Automation-first QA groups
Scripted maintenance for large suites
Faster triage for failures
Show 1 more scenario
Mixed-skill QA orgs
Keyword plus code automation
Shorter time to first test
Record and playback accelerates initial authoring while code handles edge cases and dynamic UI.
Best for: Fits when QA teams need controlled end-to-end UI regression automation with scripted extensibility.
Sauce Labs
enterpriseCloud testing infrastructure supports web, mobile, API, and visual testing workflows.
Job provisioning and remote execution are controllable through Sauce Labs APIs for pipeline and custom orchestration.
Sauce Labs supports remote browser automation through a managed execution grid that runs tests against real browsers and devices, which helps teams validate cross-environment behavior without maintaining local infrastructure. Jobs can be configured from CI so pull request checks generate consistent run outputs, logs, and artifacts per environment. The automation surface includes an API for provisioning and job control, which supports programmatic coordination with pipeline steps.
A notable tradeoff is that test execution relies on external runtime capacity, so environment availability and queueing can affect end-to-end feedback timing. Sauce Labs fits teams that already run browser-based suites and need environment breadth plus run-level reporting for distributed QA workflows.
- +Remote browser and device execution managed through a CI-friendly grid
- +API-driven job orchestration supports automated provisioning for test runs
- +Per-run artifacts and logs make failures traceable across environments
- +Parallel execution helps reduce total runtime for environment-heavy suites
- –Feedback loop timing depends on external runtime capacity and queue behavior
- –Browser-grid execution can add overhead versus local-only test runs
- –Environment selection and tagging require consistent pipeline conventions
- –Debugging may require correlating logs across multiple parallel jobs
QA automation engineers
Run UI suites on many browsers
Fewer environment-specific blind spots
DevOps teams
Gate pull requests with remote tests
Consistent quality gates
Show 2 more scenarios
Test platform owners
Automate environment selection at scale
Reduced manual orchestration
Use API-driven configuration so pipelines pick targets and collect results programmatically.
Enterprise QA orgs
Standardize reporting across teams
Faster cross-team triage
Centralize execution outputs for parallel runs so teams can compare failures by environment and build.
Best for: Fits when browser-based QA suites need controlled environment variety with API-driven pipeline execution.
Playwright
developer-firstOpen-source automation supports Chromium, Firefox, and WebKit with browser, API, and component testing.
Trace Viewer bundles step-by-step browser actions with network and DOM snapshots for CI failure root-cause.
Playwright targets the UI testing layer with a browser automation engine that drives Chromium, Firefox, and WebKit through one API. It provides automatic waiting for DOM and network state, built-in browser context isolation, and deterministic tracing artifacts for debugging CI failures.
Its test runner integrates with CI workflows through consistent command-line execution, parallelization controls, and rich reporting hooks. Playwright works best as a UI test tier within a test suite composition that limits end-to-end scope and keeps faster checks in lower layers.
- +Unified API for Chromium, Firefox, and WebKit with consistent selectors
- +Browser context isolation prevents session bleed across tests
- +Trace viewer captures actions, network events, and DOM snapshots per run
- +Built-in retries and timeouts reduce flaky UI timing failures
- –UI-first model can encourage slow tests if lower tiers are underused
- –Network mocking and test data setup require custom fixtures and discipline
- –Cross-browser parity depends on app accessibility and stable UI semantics
- –Test suite maintainability can drop when selectors lack a formal strategy
Best for: Fits when QA teams need stable, parallel UI checks with trace-based CI debugging and browser coverage.
Cypress
developer-firstWeb testing software supports end-to-end, component, integration, and API testing.
Time-travel test debugging in the Cypress runner shows state changes step-by-step during a failure.
Cypress runs in a real browser to execute JavaScript end-to-end tests with automatic waiting and time-travel debugging for each failing step. It also supports component testing by mounting UI components directly and driving them with the same event loop controls used in end-to-end runs.
The Cypress runner exports detailed artifacts such as screenshots and video, and it integrates with common continuous integration setups through CLI configuration and environment variables. Cypress is most effective when the test suite can be kept deterministic through stable selectors and controlled network and time behaviors.
- +Time-travel debugging with per-step state makes failures faster to reproduce
- +Automatic waiting reduces flaky retries for DOM readiness and async UI flows
- +Component testing can mount UI in isolation with the same Cypress command model
- +First-class screenshots and video artifacts integrate cleanly into CI feedback
- –Reliable test determinism requires strict control of clock and network behavior
- –Large suites can hit execution-time limits without disciplined test selection and sharding
- –Cross-browser coverage depends on external browser availability and CI runner configuration
- –Test architecture can drift toward end-to-end patterns without enforced pyramid boundaries
Best for: Fits when teams want fast, browser-driven feedback and can maintain deterministic selectors and mocked network behavior.
Postman
API-firstAPI software supports request testing, automated collections, contract workflows, and monitoring.
Postman collections with JavaScript pre-request and test scripts support environment-aware, data-driven API assertions.
Postman supports an API-first test workflow built around collections, environments, and automated runs that QA teams can trigger in CI. Test execution is driven by Postman’s collection runner and can be integrated with CI systems through Postman’s command-line tooling.
For a testing pyramid fit, it is strongest at API and integration layers where deterministic request and response assertions matter. It is less direct for unit-level test distribution and code-adjacent checks that live inside application test runners.
- +Collection-based tests reuse the same request suite across environments
- +JavaScript scripting enables dynamic assertions and request parameterization
- +Command-line runs support CI pull request checks for API layers
- +Pre-request and test scripts reduce duplication in large request graphs
- –Unit-test execution inside the app test harness is not its core model
- –Large suites need careful fixture and variable hygiene to reduce flakiness
- –Test results are more API-centric than deep application coverage artifacts
- –Advanced governance requires disciplined team conventions for shared collections
Best for: Fits when QA teams standardize API and integration tests with reusable collections and CI automation.
pytest
developer-firstPython testing software supports unit, functional, fixture-based, and plugin-driven automation.
pytest fixtures provide dependency-injection style setup that can parameterize test data and environments without manual wiring.
pytest differentiates itself from many testing pyramid tools by focusing on a Python-first test runner with a fixture system that shapes test data and environment setup. It composes test suite execution with collection rules, assertions introspection, and extensible plugins through a documented hook API.
Its core capabilities support unit and component testing workflows, while still integrating into pull request checks via standard CI test commands. The ecosystem adds reporting formats and parallel execution options for broader test distribution control in large repositories.
- +Fixture system centralizes setup, teardown, and parameterized test data
- +Rich assertion introspection reports failure diffs for Python expressions
- +Plugin hooks enable custom collection, reporting, and execution control
- +Native test collection supports deterministic suite composition
- –No built-in governance layer for RBAC or centralized audit logging
- –Parallel execution typically requires extra tooling or runner configuration
- –HTML and CI reports depend on plugins for many formats
- –Cross-language contract testing workflows require external frameworks
Best for: Fits when Python test suites need fixture-driven structure and CI-friendly execution control.
Jest
developer-firstJavaScript testing software provides unit testing, mocking, snapshot testing, and coverage reporting.
Snapshot testing with update and diff workflows is built into Jest’s runner, making output regression checks routine.
Jest is a JavaScript test runner built around a full test framework, which makes it distinct from tools that focus only on test orchestration. It provides test execution, assertion APIs, and mocking utilities in one package, which is useful for shaping a test suite composition and speeding the test feedback loop in CI.
Its snapshot mechanism and built-in coverage reporting help teams catch unintended output changes without adding separate tooling. Jest also includes utilities for controlling timers and isolating module behavior, which supports deterministic tests across repeated runs.
- +Built-in mocking and assertions reduce external test helper dependencies
- +Snapshots provide fast regression checks for UI markup and serialized output
- +Parallel test execution improves pull request check turnaround
- +Integrated coverage reporting works with common CI pipelines
- –Large suites can hit memory ceilings without test sharding discipline
- –Global mocking patterns can create hidden coupling between test files
Best for: Fits when QA teams need fast JavaScript unit and component feedback with strong mocking and snapshot tooling.
BrowserStack
enterpriseCloud infrastructure runs automated web and mobile tests across browsers, devices, and operating systems.
Session-based interactive testing that coexists with automated cloud runs, with artifacts suitable for rapid failure reproduction.
BrowserStack runs tests against real browsers and real devices through cloud-hosted environments, including interactive web testing in addition to automated runs. It is distinct for its coverage of WebDriver-compatible browser execution plus session-based workflows that support visual and manual reproduction alongside CI-driven execution.
The automation layer centers on starting sessions, executing test code in those sessions, and collecting artifacts like logs and video for debugging. Governance and integration show up through account-level controls and API-driven orchestration that QA teams can wire into existing pipelines.
- +Real browser and device execution supports deterministic cross-environment reproduction
- +Session artifacts like logs and video speed triage during CI failures
- +API-driven execution fits pipeline automation and PR checks
- +Interactive browser sessions complement scripted runs for debugging
- –Test determinism depends on stable app state and explicit waits
- –Deep reporting and analytics require disciplined artifact naming and retention
- –Local dependency handling needs setup to route traffic correctly
- –Scaling large test suites demands careful parallelization and sharding strategy
Best for: Fits when CI needs real-device browser coverage with session artifacts for fast debugging.
Selenium
developer-firstOpen-source browser automation provides WebDriver APIs and grid execution for major browsers.
Selenium Grid lets WebDriver sessions route through a centralized hub for distributed, parallel browser runs.
Selenium is a browser automation framework that fits QA teams building UI test suites around real web browsers and WebDriver-compatible drivers. It provides a code-first API for driving interactions, waiting for conditions, and collecting results across major browsers.
Selenium Grid supports distributed execution for parallel runs and test distribution across nodes, which can shorten test execution time. The ecosystem also supports page object patterns and test runner integration, which affects test maintenance and test feedback loop speed.
- +WebDriver API maps directly to browser controls and DOM interaction
- +Grid enables parallel execution across multiple machines and browser versions
- +Strong ecosystem of language bindings and test runner integrations
- +Debugging via real browser execution reduces simulator mismatch
- –Flaky test risk rises without careful waits and test isolation discipline
- –No built-in RBAC or audit log for cross-team governance
Best for: Fits when QA teams need real browser automation with distributed execution and custom CI integration.
Conclusion
After evaluating 10 education learning, PactFlow stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right testing pyramid software
Testing pyramid software helps QA teams distribute tests across unit, component, and higher-level layers so feedback stays fast while coverage stays meaningful. This guide covers PactFlow for contract verification gates, TestComplete for UI object-model automation, Sauce Labs for API-driven remote browser provisioning, and Playwright, Cypress, Postman, pytest, Jest, BrowserStack, and Selenium for additional execution patterns.
The tools in scope differ in where they enforce test boundaries. PactFlow focuses on consumer-to-provider pact lifecycle with verification status built to wire into pull request quality gates. TestComplete and Playwright focus on UI automation mechanics and failure debugging, while Sauce Labs and BrowserStack focus on remote execution control and session artifacts.
Testing pyramid software that enforces layered test strategy with CI-ready automation
Testing pyramid software coordinates test execution and results across multiple levels such as contract checks, UI automation, and general-purpose test runners so teams can manage test feedback loop time without collapsing everything into end-to-end runs. PactFlow concentrates on consumer-to-provider pact lifecycle and produces verification output that QA can gate in CI.
Other tools in this category anchor different layer mechanics. Playwright uses trace-based CI debugging with browser context isolation for parallel UI checks, while Sauce Labs exposes API-driven job provisioning to run browser tests across environments through a CI-friendly grid.
Contract and execution controls that keep the test pyramid fast
Testing pyramid software succeeds when it enforces boundaries at the layer where failures originate. PactFlow turns consumer-to-provider pact lifecycle into verification status that QA can gate in pull request quality checks.
Execution tools matter when they make layered feedback loop time predictable under CI load. Sauce Labs and BrowserStack provide remote execution with CI-friendly artifacts, while Playwright and Cypress focus on CI debugging signals that speed up root-cause analysis without forcing full end-to-end runs.
CI gates for consumer-to-provider contract verification
PactFlow manages consumer contract publishing and provider verification across CI and outputs actionable verification results for pull request quality gates. This keeps contract failures from hiding behind slower UI test runs.
API-first orchestration for remote browser jobs
Sauce Labs exposes job provisioning through its APIs so pipelines can provision environments and schedule runs with CI integration. BrowserStack also supports interactive sessions alongside automated cloud runs with artifacts for rapid reproduction.
Trace and artifact debugging for CI failure root-cause
Playwright bundles Trace Viewer with step-by-step browser actions plus network and DOM snapshots to support CI failure debugging. BrowserStack provides session artifacts such as logs and video to triage timing-sensitive failures.
UI automation mechanics with explicit object modeling
TestComplete maps UI elements into a built-in test object recognition model so actions can be reused across builds. This shifts UI automation from locator scripts toward control-level actions that remain consistent across runs.
Deterministic browser feedback loop with runner-level guidance
Cypress uses time-travel test debugging in the runner to show state changes step-by-step during a failure. Its automatic waiting reduces flaky retries for DOM readiness and async UI flows.
Collection-based API test reuse with environment-aware scripts
Postman uses collections with JavaScript pre-request and test scripts to standardize API and integration checks across environments. This supports data-driven assertions while keeping request suites reusable.
Test structure and mocking support for fast developer cycles
pytest fixtures provide dependency-injection style setup that can parameterize test data and environments without manual wiring. Jest adds built-in snapshot testing with update and diff workflows for fast regression checks.
Layering fit for contract gates, UI automation, and remote execution
Choosing testing pyramid software works best when the evaluation starts at the layer that needs strongest enforcement. PactFlow addresses contract enforcement directly with verification outputs for pull request quality gates, while TestComplete and Playwright center on UI automation mechanics and failure debugging.
The second axis is how the platform shapes test execution boundaries in CI. Sauce Labs and BrowserStack focus on remote browser job provisioning and session artifacts, while Cypress and Playwright prioritize runner-level debugging signals that keep the feedback loop short for browser checks.
Start with the layer that must fail fast in CI
If consumer-to-provider contracts must gate pull requests, PactFlow routes pact verification into CI-ready status that QA can use in quality gates. If the critical risk is UI regression, TestComplete or Playwright shift the focus to stable UI automation mechanics and CI debugging signals.
Choose runner debugging depth based on failure reproduction needs
If CI failures must include replayable browser context, Playwright Trace Viewer provides network and DOM snapshots tied to step-by-step browser actions. If the team wants step-by-step state during browser runs inside the test runner, Cypress time-travel debugging shows state changes during failures.
Pick remote orchestration when environments must vary per run
If each pipeline run needs controlled environment variety through an execution grid, Sauce Labs provides API-driven job provisioning for CI scheduling. If cross-device coverage with session artifacts is the priority, BrowserStack supports deterministic reproduction via real browser and device session artifacts.
Select UI automation mechanics that match UI churn tolerance
If UI automation needs resilient control-level actions, TestComplete’s UI object recognition maps elements into an object model for action reuse across builds. If the team relies on browser context isolation and unified selectors, Playwright provides consistent selectors across Chromium, Firefox, and WebKit.
Standardize API checks when the suite is collection-driven
If API tests are already organized as reusable request collections with parameterization, Postman collections with JavaScript pre-request and test scripts support environment-aware assertions. If the suite is Python or JavaScript unit-style, pytest fixtures and Jest snapshot workflows shape fast developer feedback without contract-specific enforcement.
Run parallel browser checks only with explicit isolation and selection discipline
Playwright browser context isolation prevents session bleed across tests, which supports stable parallel UI checks under CI. Cypress can also support large suites, but deterministic selectors and disciplined test selection and sharding are required to avoid execution-time limits.
QA teams that need enforcement at the right layer
QA teams should match testing pyramid software to the enforcement mechanism they need at each layer. PactFlow fits QA workflows that gate pull requests on consumer-to-provider verification outputs instead of waiting for slower UI failures.
UI-focused QA teams also need debugging speed in CI when failures are timing-sensitive. Playwright and Cypress emphasize trace or runner replay, while Sauce Labs and BrowserStack emphasize remote execution control and session artifacts for reproduction across environments.
QA engineering teams running pull request quality gates for APIs
PactFlow outputs consumer-to-provider pact verification status that QA can wire into pull request quality gates. This keeps contract failures aligned with CI-level enforcement instead of pushing them to end-to-end runs.
QA teams building resilient browser regression suites with CI debugging
Playwright Trace Viewer provides step-by-step actions with network and DOM snapshots for CI debugging. Cypress time-travel debugging shows state changes inside the runner when failures occur.
QA organizations that must run the same suite across many browser and device targets
Sauce Labs provides API-driven job provisioning for controlled environment variety through its execution grid. BrowserStack provides real browser and device execution with session artifacts for rapid failure reproduction.
QA teams standardizing UI automation using a shared object model
TestComplete’s built-in test object recognition maps UI elements into an object model for action reuse across builds. This supports scripted extensibility in multiple scripting languages.
QA teams standardizing API and integration assertions around reusable collections
Postman collections combine JavaScript pre-request and test scripts with environment-aware variable handling. This supports reusable request suites across environments for integration testing.
Common pyramid breakdowns caused by execution misalignment
Testing pyramid software can still fail when teams treat all layers as equivalent and skip boundaries. A contract tool that only runs locally or a UI tool that lacks isolation can turn fast feedback into noisy CI failures.
Several pitfalls show up repeatedly across layered test strategies. They cluster around locator churn, governance gaps for cross-team control, and reliance on remote capacity for predictable CI timing.
Gating pull requests on end-to-end UI checks instead of contract verification
PactFlow exists to manage consumer-to-provider pact lifecycle and produce verification outputs suited for CI quality gates. Moving contract checks earlier reduces the rate of slow failures that mask the real fault.
Overlooking UI automation fragility during frequent UI churn
TestComplete reduces locator-heavy scripting by mapping UI elements into a test object model, but the object model still needs maintenance when UI structure changes. Cypress and Playwright also require deterministic selectors and fixture discipline to prevent flakiness.
Assuming remote browser runs are deterministic without isolation and explicit waits
BrowserStack session outcomes depend on stable app state and explicit waits to keep behavior deterministic. Sauce Labs feedback loop timing can also reflect external runtime capacity and queue behavior.
Using fixtures without planning for governance and shared CI execution control
pytest fixtures structure setup and teardown for Python suites, but pytest has no built-in RBAC or centralized audit logging for cross-team governance. Selenium Grid centralizes WebDriver routing but does not provide built-in RBAC or audit logs, so separate governance layers are needed.
How We Selected and Ranked These Tools
We evaluated PactFlow, TestComplete, Sauce Labs, Playwright, Cypress, Postman, pytest, Jest, BrowserStack, and Selenium on features coverage, ease of applying those features to CI, and value for layered test distribution. Features counted for 40% because CI gate outputs for contracts, browser execution controls, and trace or runner debugging depth directly determine whether the pyramid stays balanced.
Ease and value each counted for 30% because test execution time feedback loop improvements require practical wiring such as API-driven job orchestration, CI artifacts, and reusable automation mechanics. PactFlow set the ranking pace through consumer-to-provider pact lifecycle management and verification outputs designed for pull request quality gates across CI.
Frequently Asked Questions About testing pyramid software
How does PactFlow fit into a test pyramid for CI quality gates?
Which tool works best for deterministic browser UI checks with trace artifacts in CI?
When should Cypress be used for component testing instead of end-to-end automation?
What breaks in a testing pyramid when Postman is used as a unit-test runner?
How does Sauce Labs change test execution time when parallelization is required?
What security controls and account governance matter when using BrowserStack for regulated environments?
How does SmartBear TestComplete support UI automation while preserving lower-layer unit and component coverage?
How do pytest fixtures affect test isolation and test data management in a pyramid setup?
Which tool is better for contract testing across services, PactFlow or Postman collections?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
- Technology Digital MediaTop 10 Best Code Testing Software of 2026
- Technology Digital MediaTop 10 Best Quality Assurance Testing Software of 2026
- Technology Digital MediaTop 10 Best Tree Testing Software of 2026
- Technology Digital MediaTop 10 Best Bug Testing Software of 2026
- Education LearningTop 10 Best Test Preparation Software of 2026
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