GITNUXSOFTWARE ADVICE
Technology Digital MediaTop 10 Best Dev Software of 2026
Top 10 Best Dev Software tools ranked by features and workflow fit. Compare GitHub, GitLab, and Bitbucket to find the right pick.
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%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
GitHub
Branch protection rules with required status checks and required reviews
Built for teams needing standardized Git workflows with review, CI/CD, and security automation.
GitLab
Merge Request pipelines with approvals and environment-aware release controls
Built for dev teams needing integrated CI/CD, code review, and DevSecOps governance.
Bitbucket
Pipelines CI with YAML-defined build steps for automated testing and deployment
Built for teams using Bitbucket pull requests and pipelines for Git-based CI automation.
Related reading
Comparison Table
This comparison table evaluates Dev Software tools used for source control, issue tracking, and team documentation, including GitHub, GitLab, Bitbucket, Jira Software, and Atlassian Confluence. Each row summarizes core capabilities and how the tools support common workflows like pull requests, code review, CI integrations, backlog management, and knowledge sharing. Readers can use the side-by-side details to match tool features to team needs and choose the best fit for development and collaboration.
| # | Tool | Category | Overall | Features | Ease of Use | Value |
|---|---|---|---|---|---|---|
| 1 | GitHub Git-based code hosting with pull requests, Actions CI workflows, and integrated issue and project management. | code hosting | 9.0/10 | 9.4/10 | 8.8/10 | 8.7/10 |
| 2 | GitLab End-to-end DevOps platform that combines repositories, CI pipelines, code review, and security scanning in one workspace. | DevOps suite | 8.3/10 | 8.9/10 | 8.0/10 | 7.9/10 |
| 3 | Bitbucket Git and Mercurial repository hosting with pull requests, pipelines, and team permissions for software development teams. | code hosting | 8.0/10 | 8.4/10 | 7.9/10 | 7.7/10 |
| 4 | Jira Software Issue and workflow tracking for agile software teams with customizable boards, sprints, and backlog management. | issue tracking | 8.1/10 | 8.6/10 | 7.6/10 | 8.0/10 |
| 5 | Atlassian Confluence Team wiki for engineering documentation with page versioning, permissions, and collaboration features. | documentation | 8.4/10 | 8.7/10 | 8.2/10 | 8.2/10 |
| 6 | Linear Issue tracking tool focused on fast workflows with real-time collaboration, automations, and integrated planning. | issue tracking | 8.4/10 | 8.6/10 | 9.1/10 | 7.6/10 |
| 7 | Slack Team communication platform that supports channels, search, and integrations for developer collaboration and incident response. | team messaging | 8.5/10 | 8.7/10 | 8.9/10 | 7.7/10 |
| 8 | Notion Flexible workspace that combines databases, docs, and project views for engineering planning and lightweight toolchains. | workspace | 8.1/10 | 8.6/10 | 7.9/10 | 7.6/10 |
| 9 | Figma Collaborative design and prototyping platform with component libraries, design systems, and versioned reviews. | design collaboration | 8.1/10 | 8.8/10 | 8.0/10 | 7.4/10 |
| 10 | Postman API development platform for building requests, running collections, and generating automated test suites. | API tooling | 7.5/10 | 7.6/10 | 8.1/10 | 6.9/10 |
Git-based code hosting with pull requests, Actions CI workflows, and integrated issue and project management.
End-to-end DevOps platform that combines repositories, CI pipelines, code review, and security scanning in one workspace.
Git and Mercurial repository hosting with pull requests, pipelines, and team permissions for software development teams.
Issue and workflow tracking for agile software teams with customizable boards, sprints, and backlog management.
Team wiki for engineering documentation with page versioning, permissions, and collaboration features.
Issue tracking tool focused on fast workflows with real-time collaboration, automations, and integrated planning.
Team communication platform that supports channels, search, and integrations for developer collaboration and incident response.
Flexible workspace that combines databases, docs, and project views for engineering planning and lightweight toolchains.
Collaborative design and prototyping platform with component libraries, design systems, and versioned reviews.
API development platform for building requests, running collections, and generating automated test suites.
GitHub
code hostingGit-based code hosting with pull requests, Actions CI workflows, and integrated issue and project management.
Branch protection rules with required status checks and required reviews
GitHub stands out with tightly integrated Git hosting, collaboration, and automation around pull requests. It provides core developer workflows for code review, issue tracking, security scanning, and CI/CD triggers through GitHub Actions. Collaboration scales from individual projects using projects boards to large teams with CODEOWNERS-based review routing and branch protections. Extensive integrations with APIs, webhooks, and third-party apps support customization across the software lifecycle.
Pros
- Pull request workflows combine reviews, checks, and branch protections
- GitHub Actions enables CI and CD with reusable workflows and artifacts
- Security features include secret scanning and dependency vulnerability alerts
Cons
- Repository customization can become complex with many settings and rules
- Large monorepos can face slower UI performance and indexing delays
- Governance features require careful configuration to avoid noisy review traffic
Best For
Teams needing standardized Git workflows with review, CI/CD, and security automation
More related reading
GitLab
DevOps suiteEnd-to-end DevOps platform that combines repositories, CI pipelines, code review, and security scanning in one workspace.
Merge Request pipelines with approvals and environment-aware release controls
GitLab stands out by combining code hosting, CI/CD, and security features in one integrated application. Pipelines, merge requests, and built-in code review workflows support end-to-end development from commit to release. Integrated DevSecOps capabilities add scanning, policy controls, and security insights directly into the delivery lifecycle.
Pros
- Unified Git hosting, CI/CD, and security in one workflow
- Merge request pipelines and approvals streamline review-to-release
- Powerful pipeline customization with YAML and reusable components
- Built-in vulnerability scanning and security dashboards
- Comprehensive monitoring and audit trails for governance
Cons
- Complex CI configuration can slow teams during onboarding
- Granular permissions and policies add administrative overhead
- Large instances can become resource-intensive without tuning
- Some advanced workflows require deeper GitLab-specific knowledge
Best For
Dev teams needing integrated CI/CD, code review, and DevSecOps governance
Bitbucket
code hostingGit and Mercurial repository hosting with pull requests, pipelines, and team permissions for software development teams.
Pipelines CI with YAML-defined build steps for automated testing and deployment
Bitbucket stands out for tight Git workflows paired with built-in merge and review controls. It covers pull requests, branch permissions, and code review annotations across repos. Pipelines add automation for builds, tests, and deployments with configurable build steps. Integration points with Jira and other developer tools make it suitable for traceable issue-to-code flows.
Pros
- Strong pull request workflow with review annotations and approvals
- Granular branch permissions support controlled contribution models
- Integrated Pipelines enables CI automation without external tooling glue
Cons
- Pipeline setup can feel rigid when complex deployment logic is needed
- Permissions and repository settings require careful configuration to avoid friction
- UI navigation becomes slower with many repositories and active pull requests
Best For
Teams using Bitbucket pull requests and pipelines for Git-based CI automation
More related reading
Jira Software
issue trackingIssue and workflow tracking for agile software teams with customizable boards, sprints, and backlog management.
Automation rules that update issue status from triggers like deployments and transitions
Jira Software stands out with highly configurable issue types and workflows that fit common software delivery processes. It supports planning with Scrum and Kanban boards, linking work via epics and stories, and tracking progress through built-in reports. It also integrates tightly with development tooling through branches, pull requests, and automated actions that update issues based on code events. Advanced team management is supported through permissions, custom fields, and large-scale issue automation.
Pros
- Configurable workflows enforce consistent software process and approvals
- Scrum and Kanban boards with strong backlog and sprint management
- Automation updates issues from events like transitions and deployments
- Deep development integration links commits and pull requests to issues
- Robust reporting for cycle time, throughput, and sprint delivery
Cons
- Workflow and field customization can create complexity for new teams
- Report setup and automation rules can become hard to govern at scale
- Cross-team dependency tracking often needs careful configuration
Best For
Software teams needing customizable issue workflows with development traceability
Atlassian Confluence
documentationTeam wiki for engineering documentation with page versioning, permissions, and collaboration features.
Jira issue and development activity linking inside Confluence pages
Atlassian Confluence stands out with tightly integrated teamwork spaces that connect documentation to Jira and developer workflows. It supports rich page editing, templates, and structured knowledge organization with permissions. Developer teams use it for engineering handbooks, release notes, and decision logs that can link to build and issue history. Search, versioning, and audit trails help teams keep documentation consistent across changing codebases.
Pros
- Rich editor with templates supports consistent engineering documentation
- Deep Jira linking ties plans, issues, and docs together
- Powerful search accelerates finding decisions across spaces
- Granular permissions support team and project-level access controls
- Version history preserves context for documentation changes
Cons
- Large installations can feel slow without careful space and page hygiene
- Maintaining information architecture across many teams takes ongoing governance
- Automation and workflows often require add-ons or external tooling
- Linking everything reliably across teams can become tedious at scale
Best For
Engineering orgs documenting work with Jira-backed traceability
Linear
issue trackingIssue tracking tool focused on fast workflows with real-time collaboration, automations, and integrated planning.
Custom issue templates with automated status, assignees, and workflow rules
Linear stands out for its fast, distraction-light issue management with a clean board-to-issue workflow. Teams can plan work in sprints, triage across statuses, and connect issues to code changes to keep delivery context in one place. Core capabilities include custom issue fields, issue templates, and powerful search with keyboard-first navigation.
Pros
- Keyboard-first issue navigation speeds daily triage
- Smart views and filtering keep planning focused
- Tight Git integration links commits and pull requests to issues
- Custom fields support lightweight workflow tailoring
- Automation reduces manual status and assignment work
Cons
- Advanced permission models can feel limiting for complex orgs
- Reporting depth lags behind dedicated BI and project suites
- Cross-team governance requires careful setup to avoid chaos
- Workflows can become rigid when teams need heavy customization
Best For
Product and engineering teams tracking work with Git-connected issue workflows
More related reading
Slack
team messagingTeam communication platform that supports channels, search, and integrations for developer collaboration and incident response.
Workflow Builder automation for routing messages, approvals, and task updates in Slack
Slack stands out with real-time team messaging plus a channel-first structure that maps well to engineering workflows. It supports threaded conversations, granular mentions, searchable history, and integrations that connect chat to code, incidents, and delivery. Workflow depth is driven by Slack Connect for external collaboration and by automation using Slack Apps and workflow builders like Workflow Builder. Developers typically use it to centralize status updates, triage signals, and coordinate releases across distributed teams.
Pros
- Threaded conversations reduce noise during incident and release coordination.
- Deep integration ecosystem links chat with Git, CI, deployments, and monitoring.
- Powerful search and channel organization support quick troubleshooting and audits.
- Slack Connect enables cross-company collaboration without duplicating workflows.
Cons
- Large org usage can create information sprawl across many channels and threads.
- Automation can become complex when workflows depend on multiple external apps.
- Notification tuning requires ongoing governance to avoid alert fatigue.
Best For
Engineering teams coordinating releases, incidents, and code-linked collaboration
Notion
workspaceFlexible workspace that combines databases, docs, and project views for engineering planning and lightweight toolchains.
Relational database views with linked records for dependency-aware engineering tracking
Notion stands out by combining a wiki, database system, and lightweight project management inside one highly customizable workspace. Developers can model requirements, APIs, incidents, and RFCs using relational databases, custom views, and page templates. Collaboration is handled through comments, mentions, permissions, and versioned change history for organized technical documentation. The platform also supports automation with templates, integrations, and developer-facing connectors like API access and webhooks.
Pros
- Relational databases with views for tracking specs, tasks, and dependencies
- Reusable templates and page blocks speed up consistent technical documentation
- Permissions and comments support structured collaboration across teams
- Notion API enables automation and syncing of engineering data
Cons
- Large setups can become slow to navigate without strict information architecture
- Real code execution and debugging are not supported inside Notion
- Database modeling flexibility can increase setup time for complex workflows
Best For
Teams maintaining living technical docs, specs, and lightweight project tracking
More related reading
Figma
design collaborationCollaborative design and prototyping platform with component libraries, design systems, and versioned reviews.
Live collaborative editing with component variants and linked interactive prototypes
Figma stands out for real-time collaborative interface design with shared canvases and instant cursors. Its core capabilities include vector-based UI creation, interactive prototypes, component systems with variants, and developer handoff through specs and design tokens. It also supports workflow integrations via plugins and automations, plus version history for iterative change tracking. For software teams, it functions as a product design system that bridges design-to-build using structured annotations and exported assets.
Pros
- Real-time multi-user editing with change history across the same design file
- Component variants enable scalable design systems without duplicating screens
- Interactive prototypes support stakeholder review with linkable flows
- Design specs provide structured measurements and redlines for developers
- Plugin ecosystem extends workflows for icons, icons, diagrams, and utilities
- Design tokens streamline consistent theming across components
Cons
- Large design libraries can slow navigation and increase file management overhead
- Advanced layout and constraints require practice to avoid inconsistent results
- Handoff can become noisy when annotations and naming conventions drift
Best For
Product teams needing collaborative UI design system workflows for dev handoff
Postman
API toolingAPI development platform for building requests, running collections, and generating automated test suites.
Collections with environments enabling parameterized requests across teams and runs
Postman centers API development around a visual workflow with request building, collections, and reusable environments. Teams can collaborate through collections and can automate verification with monitors, Newman runs, and CI-friendly artifacts. The tool also supports API documentation views and mock servers for contract-driven development.
Pros
- Collection-based workflows keep complex API requests reusable and organized
- Visual request building supports headers, auth, and dynamic variables quickly
- Automated API testing integrates with CI through Newman-compatible runs
Cons
- Large test suites can slow down execution and increase run-management overhead
- Some advanced scenarios require additional scripting and careful environment setup
- Mocking and documentation features can lag behind more specialized tooling
Best For
API teams standardizing request collections, tests, and documentation workflows
How to Choose the Right Dev Software
This buyer’s guide explains how to pick the right Dev Software tool across code hosting, issue tracking, documentation, messaging, API testing, and design handoff. It covers GitHub, GitLab, Bitbucket, Jira Software, Confluence, Linear, Slack, Notion, Figma, and Postman. The guide maps concrete capabilities like branch protection, merge request pipelines, workflow automation, and environment-based API testing to the teams that benefit most.
What Is Dev Software?
Dev software is the toolchain used to manage code changes, collaboration, automated delivery workflows, and developer communication across the software lifecycle. It typically connects work tracking like Jira Software to code events like pull requests and pipelines in GitHub, GitLab, or Bitbucket. It also supports documentation and knowledge sharing through Confluence and Slack, plus planning and issue workflows through Linear. Many teams extend these workflows with API validation in Postman and design-to-build handoff in Figma.
Key Features to Look For
Dev teams should evaluate features that directly shape review quality, delivery speed, and auditability across the same toolchain.
Branch protection with required reviews and status checks
GitHub supports branch protection rules that require status checks and required reviews, which enforces consistent quality gates before merges. This capability is ideal for teams standardizing review rules across repositories, especially when pull request workflows combine checks and branch protections.
Merge Request pipelines with approval and environment-aware release controls
GitLab’s Merge Request pipelines with approvals and environment-aware release controls connect review to deployment governance in one delivery workflow. This matters for teams that want policies to control what can ship and under which environments.
YAML-defined pipelines for CI and automated testing and deployment
Bitbucket provides Pipelines with YAML-defined build steps for automated testing and deployment, which makes build logic explicit in versioned configuration. This matters when teams need CI automation without stitching together external tooling glue.
Issue workflow automation triggered by development events
Jira Software automation updates issue status from triggers like deployments and transitions, which keeps planning synchronized with real execution. This matters when work status must reflect code movement across pull requests and releases.
Jira-linked documentation that preserves decisions and context
Atlassian Confluence links Jira issue and development activity inside Confluence pages, which ties engineering decisions to build and issue history. Version history and permissions also help teams keep documentation consistent while code and plans evolve.
Collections and environments for parameterized API testing
Postman centers API development around collections with environments that parameterize requests across teams and runs. This matters when automated verification must run repeatedly in CI using collection-based workflows and Newman-compatible execution.
How to Choose the Right Dev Software
A practical selection framework matches the tool’s strongest workflow primitives to the team’s daily bottlenecks in code review, delivery, triage, and verification.
Start with the code review and delivery control model
Teams that need standardized Git workflows with strict quality gates should look at GitHub for branch protection rules that enforce required status checks and required reviews. Teams that want review-to-release governance tied to environments should evaluate GitLab for Merge Request pipelines with approvals and environment-aware release controls.
Match CI automation to how the pipeline is authored and maintained
Bitbucket fits teams that prefer YAML-defined pipeline build steps for automated testing and deployment. GitHub and GitLab also support pipeline automation, but Bitbucket’s YAML focus makes CI logic feel closer to source-controlled configuration for many Git-centric teams.
Decide where work status and traceability should live
Jira Software fits teams that require highly configurable issue workflows with traceability via commits and pull requests and automation that updates issue status from deployment and transition triggers. Linear fits teams that want fast board-to-issue workflows with custom issue fields and tight Git integration that links commits and pull requests to issues.
Plan documentation and decision history alongside delivery workflows
Atlassian Confluence fits engineering organizations that need a Jira-linked wiki where Confluence pages include Jira issue and development activity. Slack complements delivery execution by centralizing status updates and incident coordination with Workflow Builder automation for routing messages, approvals, and task updates.
Add the right specialists tools for API validation and design handoff
Postman fits API teams that standardize request collections, parameterized environments, and automated verification runs using Newman-compatible executions in CI. Figma fits product teams that need live collaborative interface design with component variants and linked interactive prototypes for structured design-to-build handoff.
Who Needs Dev Software?
Dev Software tools benefit teams that must coordinate engineering work, code changes, automation, and communication in a single operational workflow.
Teams standardizing Git workflows with review, CI/CD, and security automation
GitHub is the strongest fit for teams that want pull request workflows with required checks and branch protection and security automation like secret scanning and dependency vulnerability alerts. This setup supports consistent collaboration from code review to automated CI with GitHub Actions.
Dev teams needing integrated DevSecOps governance across merge requests and releases
GitLab is the best match for teams that require unified Git hosting, CI/CD, and security scanning with policy controls embedded in the delivery lifecycle. Merge Request pipelines with approvals and environment-aware release controls support governed shipping behavior.
Git-based CI automation teams using pull requests and YAML pipelines
Bitbucket fits teams that want pull request workflows with review annotations and approvals paired with YAML-defined Pipelines for automated testing and deployment. Jira and other integrations help create traceable issue-to-code flows when used together.
Engineering orgs coordinating planning, documentation, and incident-ready collaboration
Jira Software and Confluence align planning and decision history by linking Jira issue and development activity inside Confluence pages. Slack supports fast release and incident coordination with threaded conversations, deep integrations, and Workflow Builder automation for routing approvals and task updates.
Product and engineering teams tracking work with Git-connected issue workflows
Linear fits teams that need fast, distraction-light issue triage with keyboard-first navigation and Git-linked context. Custom issue templates and automation for status and assignees keep delivery planning aligned with code changes.
Teams maintaining living specs and dependency-aware technical tracking
Notion fits teams that want relational database views with linked records to track dependencies across specs, incidents, and requirements. This also works for lightweight project tracking when team collaboration happens through comments, mentions, permissions, and version history.
API teams standardizing request collections, environments, and automated test runs
Postman is the strongest fit for teams that standardize API request building with reusable collections and parameterized environments. Automated API testing integrates with CI through Newman-compatible runs and supports collaboration around shared collections.
Product teams building design systems and handing off structured UI work to development
Figma fits product teams that need real-time collaborative design with component variants and linked interactive prototypes. Design tokens and design specs support consistent theming and structured measurements for developer handoff.
Common Mistakes to Avoid
Several predictable pitfalls show up when teams adopt tools without aligning workflow control, governance effort, and cross-tool linking to actual team processes.
Choosing a code host without enforcing review and status gates
Teams that adopt collaboration features but skip branch protection gates risk merges without consistent checks in GitHub. GitHub’s branch protection rules with required status checks and required reviews prevent this quality gap.
Overcomplicating CI and policies during initial rollout
GitLab can require deeper GitLab-specific knowledge for advanced workflows because CI configuration and granular permissions and policies increase onboarding overhead. Teams that start with too many complex pipeline and policy rules often slow down adoption.
Setting up pipeline logic without designing for deployment complexity
Bitbucket Pipelines can feel rigid for complex deployment logic if build steps are modeled too narrowly at the start. Teams that require flexible deployment orchestration should design YAML build steps with environment and release behavior in mind.
Letting issue workflows drift from deployment reality
Jira Software reporting and automation can become hard to govern at scale if workflows and field customization create inconsistent states. Jira Software automation that updates issue status from deployments and transitions is most effective when workflow rules and custom fields stay tightly governed.
How We Selected and Ranked These Tools
we evaluated each of the 10 tools on three sub-dimensions, with features weighted at 0.4, ease of use weighted at 0.3, and value weighted at 0.3. The overall rating used for ranking is the weighted average of those three sub-dimensions with overall = 0.40 × features + 0.30 × ease of use + 0.30 × value. GitHub separated itself by pairing strong developer control features like branch protection rules with required status checks and required reviews to reduce governance mistakes while still enabling reusable automation via GitHub Actions. That combination scored well across features and ease of use because pull request workflows bring collaboration, checks, and gatekeeping into the same core flow.
Frequently Asked Questions About Dev Software
Which dev tool set best covers the full delivery lifecycle from code to release?
GitLab combines code hosting, merge requests, CI/CD pipelines, and DevSecOps scanning in one integrated application. GitHub also covers the end-to-end workflow with pull requests plus GitHub Actions triggers, but GitLab centralizes DevSecOps governance earlier in the pipeline.
What platform is strongest for enforcing review and build gates before code merges?
GitHub supports branch protection rules with required status checks and required reviews. GitLab adds merge request pipeline controls with approvals and environment-aware release behavior, while Bitbucket provides pull request and branch permission controls plus YAML-defined pipelines.
How do Jira Software and Linear differ for tracking work linked to engineering changes?
Jira Software uses highly configurable issue types and workflows tied to development events like deployments and transitions. Linear keeps work in a distraction-light board-to-issue flow and supports custom fields and templates with faster keyboard-first navigation linked to code changes.
Which tool is best for keeping engineering documentation connected to issues and build history?
Confluence ties teamwork spaces to Jira and links engineering activity directly inside documentation pages. Notion also supports structured technical docs via relational databases and versioned change history, but Confluence is the tighter native companion to Jira issue and development linking.
Which collaboration tool fits best for release coordination and incident workflows that involve engineers?
Slack centralizes real-time status updates with threaded conversations and searchable history, and it connects chat to delivery and incident signals through integrations. Slack Workflow Builder enables routing, approvals, and automated task updates, while Confluence and Jira focus more on documentation and issue tracking than live operational coordination.
What design tool supports an engineering handoff with structured components and verifiable prototypes?
Figma supports real-time collaborative interface design with shared canvases, component variants, and version history. It also improves dev handoff with design tokens and spec-oriented collaboration through plugins and automations, which keeps UI intent closer to implementation.
Which tool is most effective for API-first development using reusable request definitions and contract checks?
Postman builds API work around collections, reusable environments, and automated verification using monitors and Newman runs. It also supports documentation views and mock servers for contract-driven development, which helps stabilize interface expectations before backend and frontend integration.
How do GitLab and Bitbucket compare for pipeline configuration and review annotations?
Bitbucket emphasizes pull request workflows with review annotations and permission controls, then uses YAML-defined pipelines for build, test, and deployment steps. GitLab pairs merge request workflows with merge request pipeline behavior that supports approvals and environment-aware release controls, while adding built-in DevSecOps scanning in the delivery lifecycle.
What is the fastest path to get up and running with a team workflow that connects code changes to tasks?
A common start uses GitHub or GitLab for pull request workflows and CI/CD triggers, then connects those events to Jira Software for issue status automation from deployment and workflow transitions. Confluence can store engineering handbooks that link to Jira activity, and Slack can distribute release and incident updates tied to the same workflow.
Conclusion
After evaluating 10 technology digital media, GitHub 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
Referenced in the comparison table and product reviews above.
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