GITNUXSOFTWARE ADVICE
Data Science AnalyticsTop 10 Best Usb Testing Software of 2026
Top 10 ranking of Usb Testing Software tools for QA teams, comparing Jira, TestRail, and Katalon TestOps features and test workflows.
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
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Atlassian Jira Software
Workflow Designer supports transition conditions, validators, and post-functions that drive controlled test-stage progression.
Built for fits when teams need governed test tracking with API automation and auditable workflow changes..
TestRail
Editor pickAPI-driven test run provisioning and result posting with traceable case-to-execution links.
Built for fits when teams need schema-driven test execution tracking with automation via documented API and RBAC governance..
Katalon TestOps
Editor pickEnvironment and build-linked execution model that correlates results to context for structured failure analysis.
Built for fits when teams run Katalon automation and need environment-aware traceability for device testing..
Related reading
Comparison Table
This comparison table evaluates USB testing software across integration depth, focusing on how each tool connects to issue trackers, CI pipelines, and device labs via API and provisioning. It also compares the data model and schema for test artifacts, along with automation and API surface for execution, reporting, and extensibility. Admin and governance controls are evaluated through RBAC, audit log coverage, and configuration options that affect throughput and sandboxed environments.
Atlassian Jira Software
workflow automationDrive test workflows with a structured data model, automation rules, webhooks, and extensive integration surfaces to connect test planning to execution and reporting.
Workflow Designer supports transition conditions, validators, and post-functions that drive controlled test-stage progression.
Jira Software models work as issues tied to workflows, schemes, and custom fields that function as a durable data model for reporting and automation. REST APIs expose issue CRUD, workflow transitions, permission checks, and Agile board operations, while webhooks notify external systems on state changes. Jira Automation covers configuration-time rules for assigning, commenting, and transitioning without custom code, and it complements API-driven provisioning in connected environments.
A key tradeoff is that Jira’s governance and data model require deliberate scheme design so that automation, integrations, and reporting remain consistent across projects. Jira fits a USB testing workflow where equipment and test defects map to issue fields, and lab runs update status via API while approval steps route work through controlled transitions. Admin teams can use project permissions and role-based controls to prevent test data changes by unauthorized roles, while audit log entries provide traceability for workflow and field edits.
- +Configurable workflows enforce test-stage transitions and approvals
- +REST API plus webhooks support bidirectional test system sync
- +Automation rules trigger on field changes and workflow events
- +RBAC with project permissions reduces unauthorized issue edits
- –Complex scheme design can slow setup for many teams
- –Workflow rule sprawl can be harder to audit than code
QA operations teams
Track USB test defects by workflow stages
Faster triage and closure
Lab automation engineers
Push lab run statuses via REST API
Reduced manual reconciliation
Show 2 more scenarios
IT and platform admins
Control access with RBAC and audit logs
Better compliance traceability
Apply project permissions and review audit entries for workflow and field changes.
Integration teams
Synchronize Jira and manufacturing systems
Consistent status across systems
Combine webhooks with API calls to keep defect states aligned across tools.
Best for: Fits when teams need governed test tracking with API automation and auditable workflow changes.
More related reading
TestRail
test managementManage test cases and runs in a schema you can configure, automate reporting via API, and enforce access controls for projects and test artifacts.
API-driven test run provisioning and result posting with traceable case-to-execution links.
TestRail fits teams that need repeatable test execution tracking with consistent schemas for projects, suites, cases, and results. Its core data model links test cases to test runs and maps outcomes to specific executions so reporting stays traceable. Integration depth is driven by an API surface that covers planning, run creation, result publishing, and retrieval for downstream reporting.
A concrete tradeoff is that TestRail automation depends on the available API and integration patterns, so high custom orchestration usually requires engineering work. Teams with shared quality ownership benefit most when multiple products and environments feed results into a common reporting structure.
Admin and governance controls are detailed enough for multi-team usage because configuration can separate projects, control visibility via permissions, and standardize fields across the execution workflow.
- +REST API covers plans, runs, results, and suite structures for automation
- +Strong test case to execution mapping for traceable reporting
- +Project-level configuration and RBAC support multi-team governance
- +Milestones and test plans help coordinate throughput across releases
- –Complex workflow changes may require admin configuration and API orchestration
- –Highly custom reporting often needs an external integration layer
- –Automation throughput depends on integration design to avoid noisy updates
QA engineering leads
Coordinate test plans across releases
Cleaner release readiness reporting
SDET automation engineers
Push automated results into TestRail
Reduced manual reporting work
Show 2 more scenarios
Quality program admins
Standardize fields across projects
Lower data variance across teams
Use configuration and RBAC to enforce consistent schemas and controlled visibility.
Release managers
Track execution progress by milestone
Faster go no-go checks
Aggregate run outcomes by plan and milestone for decision-ready status updates.
Best for: Fits when teams need schema-driven test execution tracking with automation via documented API and RBAC governance.
Katalon TestOps
test execution analyticsTrack test execution results in a centralized model with API access, environment configuration, and automation features to manage suites and reporting.
Environment and build-linked execution model that correlates results to context for structured failure analysis.
Katalon TestOps is best when teams already run automated tests in Katalon Studio and want a consistent results schema across executions. The data model links test cases, test suites, builds, environments, and defects so stakeholders can correlate failures to specific execution context. Integration depth increases when CI servers and issue trackers feed execution and defect data into the same reporting flow.
A tradeoff is that governance and automation workflows are strongest around Katalon-centered assets rather than generic third-party test metadata. Teams get the clearest value when they need environment-level traceability, repeatable run provisioning, and automation hooks that map results back to the source test definitions. For USB testing, it fits when USB device behavior varies by target hardware profile and environment settings, so run comparisons stay structured and attributable.
- +Ties executions to environment and build context using a shared schema
- +API and automation hooks map results back to test definitions
- +Centralized traceability across tests, defects, and execution runs
- +Role-based access supports controlled collaboration across workspaces
- –Governance workflows focus on Katalon assets over generic artifacts
- –Extensibility requires aligning with TestOps data conventions
QA engineering leads
Track USB failures by environment
Faster root-cause comparisons
Automation engineers
Provision runs through API
Higher throughput reporting
Show 2 more scenarios
Release managers
Gate releases on run history
More reliable release decisions
Maps build-linked outcomes to prior executions so regressions in USB behavior are visible.
Test operations
Enforce RBAC and audit traceability
Lower governance risk
Applies workspace permissions and tracks changes across test assets and run outcomes.
Best for: Fits when teams run Katalon automation and need environment-aware traceability for device testing.
BrowserStack Test Management
test run analyticsStore and query test runs tied to devices and environments, integrate through APIs, and apply workspace governance controls for execution visibility.
Test Management API plus schema-driven mapping to execution results for run evidence consistency.
BrowserStack Test Management focuses on managing test plans, runs, and cases across browser and device sessions, with tight workflow alignment to automation execution. It uses a structured data model for test entities and supports API-based automation for provisioning, updates, and synchronization between test management artifacts and test runs.
Admin controls include role-based access and governance features that support audit-ready operation in shared environments. Extensibility centers on integrations with BrowserStack execution assets and automation pipelines rather than standalone desktop orchestration.
- +API-driven provisioning of test plans, runs, and case updates
- +Role-based access controls for shared test management workspaces
- +Structured schema that maps test entities to execution evidence
- +Audit-friendly governance around changes to test management objects
- –Automation surface centers on test management entities, not device-side execution control
- –Complex mappings are required for teams with custom test taxonomies
- –Sync behaviors can require careful configuration across execution and management layers
Best for: Fits when test-management state must stay synchronized with BrowserStack execution via API automation.
Qase
API-first test mgmtCentralize test cases and runs in a configurable schema, integrate via API, and manage access controls for projects and reports.
API-driven provisioning of plans, runs, and results for CI and lab systems that must post structured USB test data.
Qase manages USB testing workflows by modeling test cases, runs, and results with configurable fields for device and firmware context. It supports test management execution via structured plans and automated run creation, which keeps hardware test throughput consistent across teams.
Qase integrates with issue trackers and CI systems so test results can be linked to tickets and builds through its API and webhooks. Governance is handled through workspace roles and audit history for key configuration and data changes.
- +Structured test case and run model fits hardware-specific assertions and context
- +API supports automated provisioning of plans and results for CI-triggered USB testing
- +Issue-tracker links map test failures to tickets for faster triage
- +Webhook delivery enables near-real-time synchronization to external lab dashboards
- +RBAC separates permissions across test authors, executors, and admins
- –USB device metadata fields need careful schema design to avoid inconsistent tagging
- –Bulk edits across runs can be slower when result volume grows large
- –Automation requires API familiarity to reach full end-to-end provisioning
Best for: Fits when teams need controlled USB test execution with an API-first data model and ticket-linked reporting.
PractiTest
release test governanceUse structured test and defect data models with API integrations, configurable workflows, and admin governance for release-level execution tracking.
Execution traceability that links test cases, runs, and defect outcomes for audit-ready USB test evidence.
PractiTest is a test management system centered on manual and automated testing workflows for USB verification teams. It supports traceability from test cases to executions, outcomes, and defects, so USB-specific test runs remain auditable.
PractiTest places automation hooks and integrations around a defined test data model, including configuration and structured execution results. Admin features focus on governance through roles, project boundaries, and activity records that support review and compliance workflows.
- +Strong traceability from test cases to executions, results, and defects
- +Clear test data model for maintaining USB test case structure and outcomes
- +Automation-oriented execution records suitable for API-driven workflows
- +Role-based project access supports separation between test programs
- –USB-specific field modeling can require schema setup and ongoing maintenance
- –Automation depth depends on how far workflows extend beyond core execution
- –High-volume result storage needs careful indexing and retention planning
- –Cross-project reporting can require custom configuration work
Best for: Fits when USB testing programs need governed traceability and automation-driven execution reporting.
IBM Engineering Test Management
ALM test automationManage test artifacts with configurable schemas and integration capabilities, including automation-friendly interfaces for linking requirements to execution results.
Traceability-first data model connects test cases, executions, and outcomes to upstream engineering artifacts.
IBM Engineering Test Management centers on test lifecycle governance with a data model designed for traceability across planning, execution, and results. It emphasizes integration depth through APIs and configurable workflow hooks that connect test artifacts to broader engineering delivery systems.
Automation and extensibility are driven through an API surface and administrative configuration controls that support repeatable runs and environment mapping. Governance relies on RBAC and audit logging patterns suitable for regulated validation and multi-team release coordination.
- +Traceability schema links requirements, test plans, runs, and results
- +API and automation hooks support repeatable execution patterns
- +RBAC and audit log support controlled collaboration across teams
- +Configurable workflow lets teams enforce stage gates and approvals
- –Complex setup for data model mapping across existing ALM artifacts
- –Automation requires careful permission and workflow configuration
- –UI operations can lag behind scripted workflows at high throughput
- –Environment provisioning steps can become brittle across many testbeds
Best for: Fits when enterprise teams need traceable test governance with API-driven automation and strict RBAC controls.
SpiraTest
requirements-to-testModel test plans and results with configurable artifacts, integrate via APIs and exports, and control access through user roles for projects.
Requirement to test case to test execution traceability keeps lineage consistent across planning, runs, and reporting.
SpiraTest is a test management system that ties test cases, executions, and requirements into a single traceability workflow. It supports planning and execution management with configurable statuses, reusable fields, and reporting built from its underlying data model.
Automation is driven through integrations and an API surface that covers key entities needed for provisioning and ongoing synchronization. Governance is handled through workspace roles and audit-oriented change tracking across test artifacts and their relationships.
- +Traceability links connect requirements, test cases, and executions in one model
- +REST API supports automation around core entities for provisioning and sync
- +Configurable workflow fields and statuses fit different test processes
- +Role-based access controls restrict edits by artifact type and project scope
- –Complex schemas take careful setup before automation can stay stable
- –High-volume reporting can require tuning of queries and filters
- –Granular governance for sub-entities depends on project configuration
- –Automation coverage varies by entity type and relationship edge cases
Best for: Fits when teams need requirement-to-test traceability with API automation and controlled workflows.
Testlink
open-source test mgmtOrganize test suites and executions in a structured system with configurable reporting and integration options for tracking results across runs.
Traceability via test plans and structured result objects that link cases to execution outcomes.
Testlink is test case and execution management software that records USB verification runs, results, and evidence per product and release. It models test artifacts with plans, suites, test cases, runs, and results, which maps directly to traceability workflows.
The data model supports configurable permissions, custom fields, and structured execution status tracking. Integration depth centers on extensibility points and a documentation-oriented interface for automation around test lifecycle and reporting.
- +Clear data model for plans, suites, cases, runs, and results
- +Role-based access control supports scoped governance per project
- +Custom fields and templates help align evidence and statuses
- –Automation surface is limited compared with API-first test platforms
- –USB run modeling depends on how evidence is attached per execution
- –Higher-volume reporting can require database and index tuning
Best for: Fits when teams need controlled test management with a documented data model and evidence capture per run.
Azure DevOps Test Plans
ALM test plansUse work item data models for test cases and plans, connect via REST APIs and webhooks, and apply RBAC plus audit logging for governance.
Test Plans REST APIs for creating and executing test runs with results linked to test suites.
Azure DevOps Test Plans fits teams that run test work inside Azure DevOps and need traceable artifacts tied to work items, suites, and plans. It uses the Azure DevOps data model for test suites, test cases, and test runs, then renders them through the Test Plans interface.
Integration depth is high because test management, work items, and CI pipelines share the same project and permissions context. Automation and API surface comes from Azure DevOps REST APIs that create and execute test runs and read test artifacts for reporting.
- +Deep integration with work items for traceability from requirements to test runs.
- +REST APIs support provisioning and execution of test runs and retrieval of results.
- +RBAC and project scoping align test permissions with the broader Azure DevOps governance model.
- +Consistent schema for test suites, cases, and runs reduces drift across environments.
- –Test management customization depends on Azure DevOps extensibility patterns and UI workflows.
- –Large test matrices can create throughput bottlenecks in run generation and result writes.
- –Automation relies on REST API flows that require careful handling of state and artifacts.
- –Cross-project reporting needs additional configuration to normalize identifiers.
Best for: Fits when teams need test artifacts, permissions, and results to live inside Azure DevOps automation.
How to Choose the Right Usb Testing Software
This guide covers USB testing software patterns across Atlassian Jira Software, TestRail, Katalon TestOps, BrowserStack Test Management, Qase, PractiTest, IBM Engineering Test Management, SpiraTest, Testlink, and Azure DevOps Test Plans.
It focuses on integration depth, the underlying data model, automation and API surface, and admin and governance controls that affect auditability and throughput for USB test execution records.
The recommendations map specific mechanisms like workflow transitions, test run provisioning, and environment-linked execution models to the needs of hardware validation teams.
USB device validation test management that stores runs, evidence, and traceability for execution automation
USB testing software organizes USB verification work as test plans, suites, test cases, and executions, then captures results and evidence with device and firmware context.
Teams use these tools to keep test-stage state consistent across lab execution and reporting, and to link execution outcomes back to work items, tickets, requirements, or defects.
Tools like TestRail and Qase show this category in practice by modeling test cases and runs in a structured schema and supporting REST API automation for provisioning and result posting tied to traceable execution links.
Evaluation criteria for USB test execution systems with API automation and governed test-stage state
USB testing tooling differs most in how the data model connects plans, runs, evidence, and context like device or environment.
The right fit depends on whether automation and API surfaces can create and update test entities in a controlled order and whether admin governance features can prevent uncontrolled changes across teams.
API-driven provisioning of test runs and result posting
For controlled hardware throughput, platforms like TestRail and Qase support API-driven test run provisioning and result posting so execution systems can create plans and submit structured USB outcomes programmatically. This matters when lab automation must write results at volume without manual data entry and when result writes must preserve case-to-execution traceability.
Structured test-stage workflow with transition validators
Atlassian Jira Software uses workflow Designer capabilities like transition conditions, validators, and post-functions to enforce controlled test-stage progression. This matters when USB test stages need approvals and when status changes must be prevented until required evidence fields are populated.
Environment and build-linked execution correlation
Katalon TestOps correlates execution outcomes to environment and build context in a shared schema so failures can be analyzed with the exact device and test context that produced them. This matters for teams that run the same USB suite across multiple lab environments and need consistent mapping from execution to environment state.
Test management to execution synchronization via management APIs
BrowserStack Test Management supports a Test Management API and schema-driven mapping that keeps test management objects synchronized with execution evidence. This matters when test management state must stay consistent with BrowserStack execution artifacts, and when custom test taxonomies require careful field mapping.
Traceability-first data model linking test cases to defects and upstream artifacts
PractiTest focuses on execution traceability that links test cases, runs, and defect outcomes for audit-ready USB test evidence. IBM Engineering Test Management extends traceability by connecting test cases, executions, and outcomes to upstream engineering artifacts, which matters for regulated validation workflows.
Governance controls with RBAC, project boundaries, and audit-oriented change history
RBAC and audit logging show up as governance foundations across Jira Software, TestRail, Katalon TestOps, BrowserStack Test Management, Qase, PractiTest, IBM Engineering Test Management, SpiraTest, Testlink, and Azure DevOps Test Plans. This matters when test authors, executors, and admins must have different permissions and when workflow or configuration changes must be traceable for compliance and review.
Select USB testing software by matching the data model to the execution lifecycle and governance workflow
The choice should start with how test plans, test cases, runs, and results map to USB hardware evidence and device or firmware context.
Then the selection should confirm that automation can provision and update those objects in the right order through documented APIs and that governance can control who can change what.
Map the USB evidence lifecycle to the tool’s core data objects
If USB evidence must be tied to case-to-execution outcomes, TestRail and Testlink both model plans, suites, test cases, runs, and results in a structured way that supports evidence capture per execution. If the USB program needs environment and build correlation, Katalon TestOps links executions back to environment context using its centralized execution model.
Validate automation and API coverage for provisioning and updates, not just reporting
For CI-driven USB test throughput, Qase and TestRail support API-driven provisioning of plans and runs and result posting that preserves structured links from cases to execution. For lab and execution synchronization needs, BrowserStack Test Management provides a Test Management API and schema mapping designed to keep evidence consistent with execution runs.
Enforce stage gates with explicit workflow mechanisms and transition safeguards
When test-stage transitions require approval logic and field validation, Atlassian Jira Software provides workflow Designer transition conditions, validators, and post-functions that control progression. For teams that rely on requirement-to-test lineage, SpiraTest and Azure DevOps Test Plans provide traceability structures that connect planning artifacts to execution results through their underlying models.
Check governance fit: RBAC scope, project boundaries, and audit traceability for configuration changes
For multi-team programs, TestRail governance centers on project-level configuration and RBAC and maintains audit-friendly change history across entities. For regulated or enterprise traceability, IBM Engineering Test Management combines RBAC with audit logging patterns and a traceability-first data model linked to upstream engineering artifacts.
Test the integration surface with the systems that already own work items, defects, or environment state
When execution outcomes must link back to work items inside Azure DevOps, Azure DevOps Test Plans uses Azure DevOps REST APIs and webhooks so test artifacts share the same project and permission context. When USB test results must connect to issues and CI systems outside the test tool, Qase and TestRail provide API and webhook integration hooks to link results to tickets and builds.
Who should use USB testing software tools with API automation and governed execution traceability
USB testing software tools fit teams that track repeated device validation runs and must preserve structured links between test definitions, executions, and evidence.
The strongest demand comes from organizations where automation writes results and where governance controls prevent uncontrolled changes to test-stage state or configuration.
Teams building CI or lab automation that must create runs and post results programmatically
Qase and TestRail fit when CI systems need API-driven provisioning of plans and runs and automated result posting tied to case-to-execution links. These tools also support webhook or integration hooks that keep external systems synchronized with near-real-time updates.
Test programs that need environment-aware failure analysis across devices, builds, and testbeds
Katalon TestOps fits when the execution model must correlate results to environment and build context for structured failure analysis. This is especially relevant for device testing where the same tests run across multiple lab setups.
Enterprises that require governed stage gates, approvals, and auditable workflow changes
Atlassian Jira Software fits when test-stage progression requires transition validators and workflow Designer post-functions to enforce controlled state changes. IBM Engineering Test Management fits when strict RBAC controls and audit logging patterns must wrap traceability across planning, execution, and results.
Organizations that must keep test management records synchronized with a specific execution platform
BrowserStack Test Management fits when test-management state must stay synchronized with BrowserStack execution via Test Management API and schema-driven mapping. This matters for teams that rely on consistent run evidence across both management and execution layers.
Teams that operate inside Azure DevOps and require traceability tied to work items
Azure DevOps Test Plans fits when test suites, cases, and runs must live inside Azure DevOps project governance and link directly to work items. This keeps permissions and traceability aligned with the broader Azure DevOps automation context.
Common implementation pitfalls in USB test management with automation and governance
USB testing implementations break when the data model and automation order do not match the real execution lifecycle.
They also break when workflow governance is informal, which causes state drift between lab execution and reporting.
Designing schemas or fields that do not match USB device and firmware context
Qase and Testlink both support custom fields and structured context, but inconsistent tagging of device metadata can produce unreliable reporting when runs mix incompatible field values. A corrective step is to lock the schema design early so device and firmware context fields are standardized across all test suites and plans.
Over-relying on workflow states without explicit validators and traceable change history
Jira Software can prevent invalid test-stage progression using transition conditions, validators, and post-functions, but workflow rule sprawl can be harder to audit when not kept under control. A corrective step is to keep workflow changes limited and ensure stage transitions are protected by validators that require evidence fields to be present.
Assuming the test management API can update everything without careful entity ordering
TestRail supports API-driven provisioning and result posting, but complex workflow changes may require admin configuration and careful API orchestration. A corrective step is to validate the update sequence by scripting plan creation, run creation, result posting, and suite mapping in the exact order used by lab automation.
Treating automation as entity-agnostic when mapping relationships is required for traceability
BrowserStack Test Management and SpiraTest depend on schema-driven mapping and relationship edges, and complex mappings can be required for custom test taxonomies. A corrective step is to define relationship rules for test cases, runs, and evidence so automation writes do not create orphan records or broken traceability links.
Ignoring throughput and storage constraints for high-volume result posting
PractiTest and Testlink can require indexing and retention planning when result volume grows large, because high-volume result storage can impact reporting queries. A corrective step is to plan retention and verify that reporting filters and queries remain stable at the expected execution throughput.
How We Selected and Ranked These Tools
We evaluated Jira Software, TestRail, Katalon TestOps, BrowserStack Test Management, Qase, PractiTest, IBM Engineering Test Management, SpiraTest, Testlink, and Azure DevOps Test Plans on three criteria that map to real USB test execution work: features, ease of use, and value, with features carrying the biggest influence on the overall score while ease of use and value each account for the next largest share.
This editorial research used the mechanisms and governance capabilities described for each tool, then converted them into comparable scoring across automation and API surface, data model structure, and admin controls like RBAC and audit-oriented traceability.
Atlassian Jira Software separated itself from lower-ranked options by combining a workflow Designer that includes transition conditions, validators, and post-functions for controlled test-stage progression with strong REST API plus webhooks support for bidirectional synchronization.
That combination pushed its features factor higher and directly aligns governance depth with automation and integration breadth, which matters most for USB teams that need auditable workflow changes tied to execution status.
Frequently Asked Questions About Usb Testing Software
How do Jira, TestRail, and Qase model USB test data for traceable execution results?
Which tools support API and webhook-driven automation for provisioning USB test runs?
How do these tools integrate with issue trackers and CI pipelines for closed-loop defect reporting?
What RBAC and audit logging controls exist for regulated USB validation workflows?
Which platform is best for USB testing labs that need environment and build context correlation?
How do tools handle test data migration when moving USB test management from spreadsheets or legacy systems?
What admin controls and configuration governance matter most for multi-team USB test programs?
Which tools support requirement-to-test lineage for USB verification evidence?
Where does extensibility work best for teams that need custom automation around USB test execution?
Conclusion
After evaluating 10 data science analytics, Atlassian Jira Software 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.
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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