With the emergence of agile, coupled with a proliferation of software platforms and hardware devices, ensuring UX and scalability can be a major hurdle. Qualitest’s Hybrid Automation case study provides a guide to developers and testers on how to ensure both UX and maximum scalability at a price point that makes financial sense.

Client Overview

The client is one of the world’s largest multinational tech companies and the specific business that Qualitest provided services for was their navigation application. The application is one of the world’s most downloaded applications and is deployed across a myriad of devices and a number of software platforms. The platform is constantly being updated with user reports and follows a demanding agile development schedule which sees frequent updates.

Business Needs and Objectives

The client had a requirement to ensure that their current platform has the maximum amount of scalability and compatibility. Concurrently, they wanted the solution to address regression resource issues of their in-house team, which would allow for a shift towards new integrations and increased performance. They needed to be certain their new testing solution:

  • Ensured the scalability of their navigation application across a plethora of software platforms without the need for different coding languages to be employed
  • Resulted in maximum coverage on devices using a hybrid lab combining simulation capabilities and popular physical devices
  • Significantly decreased the number of coding errors, improving the functionality and user experience of the application
  • Allowed their in-house team not to be bogged down with regression testing
  • Met security requirements pertaining to data transmission, logging in, etc.

The Qualitest Solution

Our senior technical specialists provided a comprehensive approach to the client, which encompassed both hardware and software platforms. The team addressed both functional and non-functional requirements, prioritizing the application’s compatibility and scalability by leveraging cross platform solution methodology, as well as cross platform solutions for scalability. The Qualitest solution was deployed in accordance with the Qualitest’s automation development model using newly redesigned testing frameworks to deliver optimum results within an agile delivery methodology.

We sought to achieve the above results by deploying a tailored set of testing services, which included the following:

  • Increasing the amount of test planning and the number of testing resources
  • Increasing the code repository that can be utilized for automated test scripts
  • Increasing the number of setups (i.e. the number of devices that a feature can be set up on)
  • Increasing the amount of behavioral feedback on an update (i.e. what is its behavior on Chrome vs. Firefox)

Our team of senior technical specialists and testers were embedded with the client and proposed several approaches for achieving the client’s desired results. These included:

  • The utilization of Qualitest’s Hybrid Lab, which includes physical devices, VMs and Emulators deployed under a Hybrid Manager Engine
  • The implementation of an automation-as-workflow (E2E) methodology covering areas such as test planning, scripting and infrastructure
  • Transitioning from the traditional CI-CD DevOps process to a Qualitest model based on Jenkins pipelining
  • Code coverage integrated into the DevOps process aimed a continuous observation of code efficiency, functionality and scalability
  • The deployment of user-friendly open source tools

Qualitest then implemented these proposals via both testers and specialists in coordination with in-house teams employed directly by the navigation application client. In addition, Qualitest continues to provide ongoing support and automated testing solutions that ensure consistent results across the constantly-expanding iterations of the application.

Key Benefits

Qualitest’s Hybrid Automation solution ensures:

  • A decrease in the number of platforms
  • Maximal compatibility vis-à-vis both hardware devices and software
  • Significantly faster understanding of issues
  • A decrease in coding errors