Continuous Testing for DevOps Teams
Cab Aggregator: Taxi for all Times
Qapitol QA > E-commerce > Cab Aggregator: Taxi for all Times

Cab Aggregator: Taxi for all Times

A one-stop transportation app that aggregates all call taxi options into one nifty app. The users can book a taxi from Uber, Ola, Mega cabs, FastTrack and many more taxi operators right from this App. The users will also find point to point taxis, hourly taxi packages, airport taxis, shared taxis all in one place.

The Context

The Context Release readiness testing for the App that already underwent multiple rounds of Dev Testing and help the startup launch an MVP.

Challenges

  • No documentation available related to Requirement, Design and Development
  • Support for Android 4.0 onwards
  • Lower end devices popular in Bangalore were not covered
  • Multi App Integration and Interactions were to be tested for both Driver and Customer Apps
  • Founder was ready to launch the app with just developer testing

Our Approach

The process was initiated with Release Readiness testing using Exploratory Test Approaches. The tests were designed while exploring the app and the app functions were categorised into Stable, Partially Stable and Low stability areas.

A quick round of deep dive testing discovered issues ranging from users getting locked, incorrect driver details being provided, inaccurate distances covered, incorrect billing, issues related to error messages and inconsistent UI behavior. Given the issues, a Test Strategy based on Risk Assessment and Coverage was prepared to ensure functional stability of MVP as the first target and address the performance issues thereafter.

Focused teams to attack the app from all dimensions were formed:

• API Testing: To check targeted Business logic, distance, ETA, Fare calculations etc.

• Integration Testing: To test the integration of the Driver App (Android) to Customer App (Android & iOS), map integration, notifications, SMS, Mails etc.

• UI: To find inconsistencies in UI design, intuitiveness of the app etc.

• Device & Platform Coverage To test the apps against various form factors and OS versions.

• Field Testing: To identify issues related to end to end flows on real networks, network switching scenarios, user experience for all user touch points, calculations of ETA, Distance, Billing etc.

• Mobile NFT : To test Memory Leak suspects, Heap Analysis, Network Analysis, Battery Analysis.

Key Findings

Key blockers and issues were found related to ETA, billing calculations, app behaviour when running in background, multiple ride bookings etc. On the non-functional side issues related to duplicate content was found in network calls. While few out of memory crashes were unearthed it was also found that the CSS and JS were not minified properly. There were also too many GC calls on the main thread resulting in performance lag. It was also discovered that the app was consuming battery even when it was in the background.

Value Delivered

The startup was able to successfully launch the MVP with MVQ. The developers were sensitised to the mobile test framework & QA is now integrated tightly with release readiness. The App induced great confidence & received good feedback in Investor meetings. The Development cycles have become more effective with less time spent on rework and issue fixes leading to shorter delivery cycles and thus improving the cost of quality.