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Client Background

In the ever-evolving landscape of digital innovation, where the roots of technology intertwine with the complexities of plant management, our client, a pioneering platform provider, embarked on a journey to revolutionize their Quality Engineering (QE) processes. They faced challenges encompassing the need for efficient automated regression testing. This meant getting multiple aspects right, from tools and processes, automation scripting productivity, infrastructure and computing resource availability to ensuring effective release management, meeting compliances, decoded scattered requirements amidst the evolving project dynamics.

The Challenge

With evolving project dynamics, the first challenge was navigating through multiple requirement documents and JIRA user stories, that created a gap in understanding of the application’s documentation. Creating manual test cases for a project with ever-changing requirements across diverse teams would lead to daily bottlenecks, introducing the risk of missed test coverage and impeding the agility of the QA processes. Additionally, the time-consuming bug documentation further exacerbated the challenges, causing a backlog of reported issues and delaying critical decision-making.

The need for rapid knowledge transfer to the technology partner added an additional layer of complexity, as the evolving nature of the project and scattered documentation made onboarding new team members a time-intensive process. Recognizing the impact of these challenges on overall efficiency, our client sought a solution.

Key Solutions

Leveraging our experience in Quality Engineering (QE), the Xoriant team identified the nuances of the client's struggles and provided a tailored and strategic approach to address the intricacies. To tackle these challenges, we implemented a series of inbuilt prompt templates powered by iQEAssist – an advanced generative AI tool for QE, fully developed at Xoriant and secured in Xoriant’s robust Azure infrastructure. iQEAssist proved instrumental in streamlining and enhancing the efficiency of QE processes, marking a transformative step in overcoming the challenges faced by our client. This included:

  • Client Assessment with a Custom Questionnaire: A tailored client assessment was introduced, employing a custom questionnaire. This method aimed to not only understand the client's objective but also assess their capability in adopting Gen AI-based Quality Engineering (QE) services.
  • Leveraging Gen AI's Language Model Capabilities: Building on this initial assessment, iQEAssist’s capabilities were harnessed for Requirement Automation. The team seamlessly extracted Behavioral-Driven Development (BDD) features, ensured requirement testability, identified gaps and took a significant stride by automatically generating functional and end-to-end test cases by uploading documents of .pdf, .txt, .csv, and .docx formats. This streamlined the testing process and alleviated the burden of manual test case creation.
  • Enhanced Test Coverage and Time Efficiency: By leveraging automated processes for test case generation, we significantly augmented the overall test coverage, addressing the persistent challenge of missed test scenarios and achieved a remarkable 70% reduction in time during the test design phase.
  • Q&A Bot Functionality: We introduced Q&A Bot functionality, recognizing the need for quick knowledge transfer and efficient onboarding of our team members. This addressed frequently asked questions, ensuring a seamless integration process.
  • Streamlined Bug Report Generation: An automated process expedited bug reporting and enabled contextual test data generation from provided test cases. This led to an all-round improvement in operational efficiency.
  • Accelerated Automation through Code Generation: We implemented automated code generation from manual test cases, producing code in the required language and framework. This initiative accelerated automation test scripting by an impressive 50%. The generated code came complete with detailed explanations and comments, streamlining the development process.
  • Smart Code Reviews with AI Insights: Introducing AI-driven code reviews marked a paradigm shift. The system generated insightful comments on code, aiding in error identification, suggesting best practices, and offering optimized code versions. This not only ensured the correctness of the code but also provided samples aligned with industry-standard best practices for both framework and language, fostering a culture of excellence in coding practices.

    In essence, the efforts addressed the immediate challenges faced while positioning the client for increased efficiency, improved accuracy, and a more strategic focus on high-value tasks within the digital plant management platform.

In essence, the efforts addressed the immediate challenges faced while positioning the client for increased efficiency, improved accuracy, and a more strategic focus on high-value tasks within the digital plant management platform.

Business Value

The strategic approach and adoption of our Gen AI-based solution, iQEAssist, heralded a significant transformation for our client, ushering in a multitude of business benefits.

  • Comprehensive Test Coverage: With a substantial 70% coverage achieved in test case generation, we ensured a thorough examination of the entire documentation, providing a comprehensive shield against potential vulnerabilities.
  • Improved Accuracy:The infusion of Gen AI resulted in a remarkable 80% boost in accuracy. freeing up manual testing efforts for exploratory testing, and effective handling of edge cases contributing to the robustness of the plant management platform. It was also leveraged in test case reviews to understand missing coverage in testing.
  • Increased Testing Efficiency:The implementation elevated overall testing efficiency to new heights, powering the QA team to redirect their focus towards high-value tasks, ultimately contributing to the success of the digital plant management platform.

Xoriant’s expertise and tailored approach became a pivotal force in enabling the client to achieve greater efficiency, accuracy, and agility in their process.

Technology Stack

Python, Azure AI, Azure AD, Azure Storage, Azure Search, Azure Functions, Azure Web App, React, Javascript

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