DeviQA Case Study: DataSport
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DataSport

The work we have done to set up a highly efficient QA process and streamline the development process for a sports event management system.

>5k

Feature/bug tickets processed

>1.6k

Automaton tests created

>100

API tests created

>70

DB-related issues found

About project

Datasport is a cutting-edge digital platform dedicated to streamlining the organization of sports events, marathons, and competitions. This comprehensive solution empowers event organizers with the flexibility to manage numerous aspects of sports event management in one place. Whether it's fine-tuning event schedules, selecting venues, coordinating teams, or handling data storage, Datasport provides a seamless and intuitive solution.

The platform is designed to cater to the diverse needs of administrators and lets them configure roles tailored to specific user responsibilities. From the super admin with unparalleled control to users with read-only permissions, restricted date modification, and limited access to certain admin functionalities, Datasport ensures a nuanced and secure user experience.

With Datasport, event organizers can orchestrate successful sports competitions, all while enjoying the convenience of a user-friendly platform.

Before DeviQA

  • There was no formal QA process

  • There was a lack of QA resources to test all platforms and product areas

  • The test documentation was incomplete

  • Testing was executed by developers

  • User stories were poorly structured. 1-2 weeks were needed to develop a user story.

  • There were serious performance issues

  • The communication between development, PO/PM, and QA teams was insufficient

With DeviQA

  • Agile QA process was built from scratch

  • Manual story testing and verification was built from scratch

  • Web automated testing was built from scratch

  • API automated testing was built from scratch

  • 99% of the application was covered with test cases and the smoke and regression checklists

  • <1 hour was needed to run smoke testing

  • <2 days were needed to run full regression testing

  • A well-structured test plan enabling thorough validation was created

  • >3,000 detailed test cases were created for a regression test suite

  • >350 detailed test cases were created for a smoke test suite

  • A fully autonomous QA process was set up where QA engineers were fully responsible for testing

  • >4k of critical and major bugs were found by the DeviQA team

  • All user stories were well-written and provided detailed information about implementation and acceptance criteria

  • <2 days were needed to write a detailed final version of a user story after a discussion with QA specialists

  • Load tests for 4 main user workflows with more than 60 different requests were created and executed, which allowed a team to identify and fix performance issues

  • Agile-based communication between all teams was introduced

Our contribution

Team

2 Manual QA Engineers, 1 Automation QA Engineer

Project length

Since 2020

Technologies and tools

Jira

TestRail

Confluence

Swagger UI

SQL DB

Figma

k6

Postman

Mocha

TypeScript

Apache JMeter

GitHub

Allure

Axios

WebdriverIO

Our engagement

Datasport needed to establish a quality control process for the project. Therefore, our QA engineers were brought in to build an efficient QA process based on both manual and automated testing.

First of all, we had to test critical areas of the app manually and then automate smoke tests. So, we started by discussing the critical areas of the app with a PO/PM and development leads. Based on these conversations and our experience in building QA cycles, we created a smoke test suite and automated it. Then we decided to improve a regression test suite and create additional test cases. As of now, it contains more than 3,000 detailed test cases.

Synchronously, we worked on ongoing sprint tasks. Our manual QA engineers thoroughly tested the new and upcoming features. All DeviQA engineers participated in all agile meetings (daily standups, planning, etc.). To optimize the work of the team, we proposed to combine grooming meetings for frontend and backend developers. This helped us identify inconsistencies and issues with new features in the grooming stage and resolve important questions in one meeting.

Also, our QA engineers suggested introducing the practice of scheduling individual meetings with a PO or designer and discussing requirements in detail at the stage of creating user stories. This way, they could create more understandable user stories and better UI/UX designs, while we spent less time testing new stories due to being aware of all the details.

The involvement of our QA specialists let Datasport not only set up a QA process from scratch, but also improve the development process, story planning, story writing, and so on.

Services provided

Web Automated Testing

Our automation QA engineer created a web automation solution from scratch. About 1,600 regression automated tests that covered critical software areas were executed on 10 threads on CI. After each failed test run, a message with test results was sent to Teams to notify the team about issues on production.

Web Testing

DeviQA team has managed to cover 99% of the web application, admin panel, and online registration service with test cases. We delivered 2 successful releases per month, maintained the product by testing it on production, and handled customer issues and requests promptly.

API Automated Testing

In addition to the web automated tests, the DeviQA team developed more than 100 API automated tests and integrated them into the CI process. Due to the architecture design and distributed execution, test results could be captured in less than 3 minutes.

Load Testing

Our experts created load tests that covered different user flows for the old website version. The test suite allowed us to measure server load with hundreds of concurrent requests. A separate test suite was created for the new website version and ensured its high performance and ability to address more requests at the same time. By executing load testing, we also found 15% of server-side issues.

Dedicated QA Team

2 manual QA engineers and 1 automation QA engineer successfully cooperated with frontend and backend developers, designers, and BA/PO/PM to improve the quality of user stories, streamline the development process, implement the best UI/UX practices, execute comprehensive testing, and, as a result, ensure excellent product quality.

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