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QualityKiosk’s AI-driven Overhaul of API Testing Delivers 100% Coverage and Faster Time to Market for a Leading Bank

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Industry & Segment

Banking & Financial Services

Objective

To modernize and scale API testing for a leading bank by implementing an AI-driven automation framework that ensures end-to-end test coverage, accelerates release cycles, and enhances overall system reliability.

Platform

qRace

Client Overview

Our client, one of India’s largest banks, faced challenges in their API testing process. The bank generated multiple test cases daily, each involving multiple fields and permutations, with frequent changes in specifications and fields, making it manually impossible to manage effciently. To address this challenge, we harnessed the power of automation, leveraging our proprietary test management tool (qRace) with generative AI to streamline the test case generation process based on API specification.

Business Challenges

Massive test case generation

The client's API ecosystem consisted of multiple fields, with various test cases generated for each, resulting in a large volume of combinations daily. Manually handling this volume of test cases was not only error-prone but also consumed significant time and resources.

Specification changes

Frequent updates and modifications to API specifications demanded rapid testing cycles. Manual testing struggled to keep pace, leading to potential delays in identifying and resolving issues.

Test management overhead

Storing, tracking, and managing the vast number of generated test cases in their test management tool posed a significant administrative challenge. The bank needed a solution to generate or modify test cases based on API specification without manual intervention and seamlessly integrate with their existing test management tool.

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QualityKiosk’s Strategy

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A robust validation strategy was established to ensure end-to-end accuracy, reliability, and completeness of API responses across all scenarios.


OpenAI Python library:

We harnessed the power of Python to automate the test case generation process. Leveraging Open AI’s Python libraries, we developed a code/utility to interpret API specifications and dynamically generate the requisite test cases per any test management format, in this case, qRace artifacts.

This utility not only:

Drastically reduced the time needed but also eliminated human errors from generating the test cases.

qRace Integration:

We integrated our in-house test management tool, qRace, with the client’s API testing environment. qRace provided a standardized format for storing and managing test cases, ensuring alignment with the bank’s existing processes. Generated test cases were uploaded in the qRace without manual intervention.

Key Strategies

OpenAI Python library
We harnessed the power of Python to automate the test case generation process. Leveraging Open AI's Python libraries, we developed a code/utility to interpret API specifications and dynamically generate the requisite test cases per any test management format, in this case, qRace artifacts.
This utility not only
Drastically reduced the time needed but also eliminated human errors from generating the test cases.
qRace Integration
We integrated our in-house test management tool, qRace, with the client's API testing environment. qRace provided a standardized format for storing and managing test cases, ensuring alignment with the bank's existing processes. Generated test cases were uploaded in the qRace without manual intervention.

Business Outcomes

100% Coverage

The automated field-level test case generation achieved a remarkable 100 percent coverage of all elements defined in the API specifications. This eliminated the risk of oversight and ensured exhaustive testing.

Faster Delivery

With the manual testing bottleneck removed, the bank experienced enhanced speed and eciency in execution. Test cases were generated and executed in a fraction of the time it would have taken manually, allowing for quicker identification and resolution of issues.

Aligned Test Case Format

All test cases seamlessly conformed to the format of the test management tool, qRace. This alignment reduced administrative overhead, improved organization, and enhanced the overall testing process

Faster Time to Market

The streamlined API testing process translated into a faster time to market for the bank's products and services. By reducing the testing phase's duration, the bank gained a competitive advantage in delivering innovations promptly.

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