THOUGHT LEADERSHIP
CASE STUDY
Scalable Test Automation using DCqaf Framework for a Leading US Plus Size Fashion Retailer
Retailers who are marching towards the digital future must make sure to have a solid and sound testing system to strengthen their innovations. With a high customer-interaction rate and exponentially increasing competition, Retail industry has ensured that it has a very low appetite for risks. Therefore, the systems associated with it should be tested adequately in a short span of time to assure there is no scope for errors. Hence, the need of the hour is Test Automation.
With an experience of more than 20 years serving several retailers, we understand their IT needs quite well. Aspire provides testing services across the entire retail landscape of Buy (Merchandising and Sales Audit), Sell (POS, E-Com, Mobile), Move (Warehouse Management) and Plan (Financial Planning, Demand Forecasting, and Inventory). Our offerings in retail testing services include:
DCqaf is a flexible and secure automation testing framework built to empower retailer’s end-to- end retail landscape that includes front-end, back-end of eCommerce application and POS systems in one fabric.
Unify Ecommerce, Mcommerce, POS & API-enabled Applications testing in one fabric
Pre-packaged End-to-end Test Automation Suite
Easy Multi-platform Integration
Faster Time to Market
Achieve up to 90% Minimized Testing Costs
Minimal team required for maintenance
Improve Reusability with higher ROI
Big Data Testing
Highly skilled QA Automation specialists with expertise in Retail
While most of the POS Testing challenges can be addressed with automation, not 100% automation can be achieved because of few limitations like scanning a bar code, swiping a card, pin-pad-entry, etc. Automation is capable of supporting only cash payments and other UI test cases, thereby covering only 60% of test cases, while 30% for any POS is EMV. To resolve this issue, Aspire has come up with an innovative test automation solution that uses a robotic arm for testing critical E2E scenarios like EMV in lesser time. Consequently, retailers can have 90% of automation done, which is a 30% boost in automation coverage.
With its latest update called Robotic Arm 2.0 iPOT, Retailers can now conduct complex EMV test cases on a much faster scale. With performance speed enhancements, iPOT can now handle 40 actions within an hour thereby reducing automation efforts drastically compared to its predecessor version Robotic Arm 1.0 iArm.
Enhanced Coverage
Automates transactions of all credit/debit cards
Continuous Automation
Scheduled triggers enable automation at night for uninterrupted manual POS Testing during day
Enhanced Features
Allows signature, swipe, tap, insert and keypad entry for all credit card types
Reliability
Enables GUI-based status for each transaction, minimizes human errors and improves scalability
Integrated with DCqaf
Reduces implementation time
Reduced Cost
Requires nominal maintenance thereby reducing the overall testing cost
Our team’s strong domain expertise and quality delivery helps us to retain customers across multiple locations. Our Test Automation framework, DCqaf help to achieve better CoQ and customer experience
Our in-house Robotic Arm solution helps with end-to-end testing of POS Systems and scales up the POS Test Automation coverage from traditional 60% to 90%
Our strategic partnerships with multiple technology providers, cloud service providers, and system integrators like Oracle, SFCC, SauceLabs and many others help us deliver best-in-class solutions
Reusable methods
Innovative technologies
Automation coverage
Reusable components
Aspire Systems is a global technology solution provider and over the last 20 years we have been helping software Hi-tech companies and enterprises accelerate their application development using Hyper-Testing, an end-to-end testing strategy consisting best practices of agile, DevOps and Shift-Left methods with best in class automation frameworks – AFTA 3.0, APTf 2.0, DCqaf and iPOT, Robotic Arm Testing solution.
©1996- Aspire Systems
