Client Overview. Engagement Situation. Key Requirements
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- Andrew Short
- 10 years ago
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2 Client Overview Our client is a global leader in mobile and digital advertising technology. Their unified monetization platform combines an ad server and a real-time bidding ad exchange to help publishers generate revenue through a plethora of digitally connected screen. Our client has one of the largest Ad server engines for publishing content. Apart from this, our client has a portfolio of products for ad exchange, optimization, content valuation, etc. Engagement Situation Xoriant product engineering experts had developed a customer management portal that maintains ad management modules, a configuration interface for advertisement accounts and thorough categorization of ads and related information to attributes such as brand, genre, creative type, and language of the registered advertisement. To ensure appropriate data matching, categorization and end-to-end customer management, it was imperative to have a well defined QA process and assure accuracy of the application with that of the business requirements. For this our client was looking for a partner who has experience in media domain and capabilities of handling varieties of digital content with utmost attention to details. In the light of our client s experience with Xoriant on the product engineering front and considering Xoriant s expertise in QA automation space, client preferred to extend their existing engagement and chose Xoriant for the test automation execution of their customer portal. Key Requirements Determine system functionality for appropriate bucketing of the data as per the categories and attributes of the incoming media Functional automation testing for key functionalities of the portal to ensure performance of the reporting platform for modules like Monetization, Ad Server, Mobile etc.
3 Thorough testing of integration and collaboration of the system with the end users of the system including both publishers and demand partners Creating Sprint plan with bi-weekly sprint cycle to have timely execution and deliverables of different modules Xoriant Contribution Xoriant team worked closely with client to understand the requirements and created an engagement roadmap. Xoriant was involved in complete software testing lifecycle process of automating the application, following SCRUM as agile execution methodology without any compromise on time-to-market goals. Considering client needs and complexities, intricacies of the data dealt with in the customer management portal, Xoriant automation experts leveraged an in-house Xoriant Test Automation Framework(XTAF) and replicated it on Python as per the requirements. This framework was scalable to work seamlessly with MySQL and Vertica database as the backend systems. The team started with a thorough test plan and leveraged their skills on Robot Framework, TestNG, Bamboo and Maven. Key Contributions Prepared test plans in test case management system like Test Rails Automated end-to-end configuration of external MicroStrategy reports like the Ad Server Reports, Bid Performance Reports etc. Integrated UI with the Vertica database and MySQL to check for consistency Separated each page functionality with its own library and function keywords using Page object model Used Robot framework for test cases repository and test execution Developed MySQL library using Python to test UI and database integration scenarios Extending existing framework to support Angular.js application without affecting existing test cases and maintaining same structure at library level
4 Existing Architecture Tools & Technologies Python JavaScript MySQL Vertica Java TestNG Jira Git Selenium Bamboo
5 Engagement Results Increased efficiency of the clients product by automating almost 90% of the product screens Incorporating best practices and automation scripts led to quick time to market Improved the quality of the application through rigorous testing of end-to-end system functionality Improved customer service by 15-20% by allowing field personnel to access service data and take additional orders on-the-go Reduced backend process errors by about 30%
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