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ACCELQ vs Micro Focus UFT – A Snapshot

Cloud based modern platform IDE based 1st Gen tool
User experience focused design, simple to use Old school complex and clunky interface
Intuitive and Natural UI flow enables Fast Adoption (~1-3 weeks) Needs specialized training and automation Engineers to write scripted tests using VB script for complex use cases.
Design first approach with Business process Application modelling Folder based object library approach with no relation to Application flow business
Test development exponentially accelerates when scaling up automation Script development becomes complex and slow when scaling up automation
Maintenance significantly reduces when scaling up automation Maintenance and Script duplicity significantly increases when scaling up automation.
Seamless extendible approach for Web-Mobile-API in one codeless flow Separate Add-ins/Plug-ins In need to be selected for the environment one needs to work on. Their current AI offering only supports Web and Mobile. It does not support Desktop.
Embedded asset collaboration and management for Smart Test Plans & Governance Disconnected Repository with no transparency of test asset management and planning.
One native platform built with no Silos Separate tools UFT One for functional testing. UFT Developer for shift left functional testing. No concept on inbuilt version control. UFT Mobile lab for real time devices and emulators. Also, AI Codeless Testing tool is a standalone tool and not part of UFT one.

Why ACCELQ is a better alternative to Micro Focus UFT?

In-sprint Automation & Shift-left

Application functional abstraction Not available
Design & author tests parallel to Application development enabling true shift-left Need a separate tool UFT Developer.
AI based Re-conciliation of abstraction Limited capabilities in primitive stage. AI offering is not supported for Desktop
API, DB and middleware Automation with UI Available with complex engine module, not seamless

Test Design

Universe based visual Application modelling Not available
Test scenarios are modularized into Pages and User Actions Scripted tests need knowledge of programming like VB Script or must be generated using record and playback visualizer.
Page objects are naturally & automatically centralized across test scenarios Object property identification and Name mapping is not centralized. Required manually creating and maintaining a global object repository.
Design is enforced with intuitive and automatic universe concept Design is manually implemented, and complex use case automation is limited with specialized "Architects" in team.
Data-driven scenarios and Test Case data is inherent to scenario design Data-driven is a disconnected step once test case is automated and adds overhead.
Parameterization with design alignment to input, environment, run-time, linking and more Technically oriented variable concept defined after the test case is defined, which reduces modularity.

Automation Development

Codeless natural English coupled with recording Scripted Tests require the need for programming language like VB Script or via unreliable record and playback visualizer. There current AI offering is not very much mature in terms of using NLP as recently launched and requires lot of feedback from customers for course correction.
Logic editor provides readymade conditional rule validations, loops etc.… for real life tests Basic and Limited validation Check points in place. Complex validations require to build scripted tests with need for programming using VB script
Logic editor provides seamless transition from UI to Mobile to DB to API to File etc. Less customizable Keyword Test flow. Difficult to edit in Keyword view. Action Editor requires knowledge on VB script to include conditions and customizations.
AI based robust object handling and self-healing (works seamlessly with Angular, iframes, Shadow DOMs, charts, SVG, canvas etc.) Traditional object interaction with limitations to handle complexity and newer tech stacks. No concept of Self-healing. AI assistance feature recently launched still not mature to handle complex tech stack.
Behavior driven predictive test designer for fast test creation and reusability Limited reusability capabilities and designing overheads.
Automated and AI based reconciliation for UI and Object changes No centralized handling, No reconciliation
AI driven data permutations auto-generates test cases providing accurate coverage Not available.
Capture the structure of test data based on business semantics. Ensure data abstraction is consistently driven across test scenarios. Is an additional step and is not seamless.
Seamlessly manage multiple variants of test data suitable for different test execution environments Available with limited capabilities
Cloud driven automatic extendibility to newer tech stacks (UI controls, DB, Mainframes, Files etc.) Manual process to create and add engines. Requires specialized skills.

Automation Execution

Cloud and Local Execution agents allow just-in-time execution against any tech stack Cloud agent not natively supported
Cross OS, Cross browser, Cross Mobile execution natively packaged with same agent Limited support
Inbuilt parallel execution with robust high performance agent providing scalability Requires a lot of configuration to setup not seamless.
Secured and Encrypted communication between Agent and Cloud to test inside firewalls without any special VPN's or network restrictions Repository based workspace sharing with traditional report, not real time and dynamic.
Docker support for Agent farm expansion with dynamic scalability and parallelization Not supported
Integration with 3P cloud infrastructure farms like sauce labs, browser stacks Not supported.

Change Management

Naturalized model with referential integrity across pages, test steps, objects, suites automates the change impact process efficiently propagating changes across test assets No referential integrity possible between test assets
Objects are centrally managed in correlation with Application pages, and object changes are automatically reflected across all tests Objects are managed in library manner. AI object identification feature is not mature yet.
Collaborative platform on cloud with real time sharing, version control, branching with intuitive design not requiring any special training or "source control" management skills Offline repository for black-box script database. No real time asset sharing, no audit history tracking, no live version compares, no branching

CI/CD & Tool Integrations

Bi-directional and natively built synchronizer for Traceability tracking, coverage analysis and requirements based Test suite planning on a modern Web Interface on cloud No clear visibility on overall test coverage
Two-way Defect creation, synchronization, and status tracking for full suite management Lacks full blown suite management
CI job execution with pre-set configurations automatically execute test suites. Adapters support Jenkins, Team city, Bamboo, AzureDevOps, AutoRabit, Copado, Command line API etc. Not a seamless technical integration
Workflow orchestration with CI workflows Complex workflow orchestration needing tech expertise

Technology Extendibility

Open concept of user extensibility to expand scope of existing technology stack, as well as build-import to extend for new technology stack Limited user extendibility and business logic customization capabilities.
Cloud based community expansion is significantly rapid Offline concept duplicates effort and high overhead and dependency of support
No impact from upgrades Needs migrations and upgrades

Governance & Reporting

ACCELQ's app universe and analytic based algorithms drive automated Test Planning ensuring coverage No intelligence in test planning and suite creation, folder style traditional planning
Dynamic live results views with actionable reports to trigger reruns Static Report is dumped into an offline folder type repository.
Umbrella style re-run capability for suite re-executions and roll up tracking Not available

The ACCELQ difference

Simple to adopt and elegantly designed, with the power to give your testing real acceleration

API and UI automated in the same flow

Unique capability to integrate API and UI testing in the same flow, enabling true end-to-end validation without handoffs. API testing at the same simplicity and regression maturity as UI automation.

Automated test case generation and data planning

Design your data behavior on a canvas and let ACCELQ take care of automated test case generation with proven risk coverage assurance. Centrally manage data changes without impacting test cases.

Seamless CI/CD integration and natural traceability

Native integration with CI/CD tools such as Jira, Jenkins ensure test automation is integral to development lifecycle. Traceability is redefined with the intelligent, connected test repository.

Salesforce Release

Being an ISV partner, ACCELQ is aligned to Salesforce releases to ensure smooth Salesforce upgrades with robust Automation testing

Automation Support

Automation support for diverse technology stack for end-to-end Salesforce process validations

In-sprint automation without need for programming

Develop automation test logic in plain English, concurrently with application development. Address in-sprint volatility with intelligent change management and powerful reconciliation engine.

Enable manual testers to automate testing

Powerful natural language editor allows you to write test automation logic in plain English. Design-first approach on UX driven platform allows manual testers to scale up without learning curve.

Visual application model for lifecycle automation

ACCELQ’s Universe is a visual blueprint of your application and drives automation across quality lifecycle with business process focus. Develop test scenarios with predictive analytics.

Self-healing autonomic test automation

ACCELQ’s analytic runtime engine ensures a reliable test execution by intelligently adapting to unexpected application changes. Design-first approach ensure Robust element ID based on AI.

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