Understanding Digital Transformation 

Digital transformation isn’t merely about adopting new technologies; it represents a comprehensive overhaul of business processes, organizational culture, and customer interactions. Its objective is to harness the power of technology to optimize operations, enhance decision-making, and create exceptional customer experiences. This all-encompassing approach leverages data, analytics, cloud computing, artificial intelligence, and other digital tools to drive efficiency and innovation, reshaping businesses for the digital age. 

The Need for Quality Engineering in Digital Transformation 

Today’s organizations grapple with challenges like shortened development cycles, frequent updates, and the imperative of maintaining a seamless user experience. Quality Engineering emerges as the linchpin in addressing these challenges, ensuring the reliability, security, and performance of software and systems undergoing transformation. 

Quality Engineering is a multi-faceted discipline encompassing various principles and practices that enable organizations to achieve their digital transformation objectives: 

1. Continuous Testing: Continuous testing involves running tests at every stage of software development, from design to deployment. This ongoing process detects issues early, reducing the time and cost of fixing bugs and ensuring a more streamlined development cycle.
2. Test Automation: Test automation utilizes specialized tools and scripts to execute test cases automatically. This not only speeds up the development process but also increases test coverage, leading to more robust and reliable software.
3. Shift-Left Testing: In shift-left testing, testing activities are moved to the beginning of the SDLC, ensuring that issues are identified and resolved as early as possible. This approach minimizes the need for extensive rework later in the development process, saving resources and time.
4. Performance Testing: Quality Engineering focuses on performance testing to assess how software applications perform under various conditions. It helps identify and address performance bottlenecks, ensuring that the application can handle expected loads without degradation.
5. Security Testing: Security testing is a critical aspect of QE, aiming to identify and mitigate vulnerabilities that could compromise sensitive data. By prioritizing security, organizations can safeguard their digital assets and maintain trust with their customers.

Quality Engineering is a multi-faceted discipline encompassing various principles and practices that enable organizations to achieve their digital transformation objectives. Two key tenets of QE that deserve special mention are: 

Extreme Automation: 

One of the pillars of Quality Engineering is extreme automation. Automation not only accelerates the testing process but also ensures repeatability and consistency in testing activities. QE leverages automation frameworks to streamline the execution of test cases, reducing manual intervention and human error. This not only saves time and resources but also allows teams to focus on more complex and strategic aspects of quality assurance. By embracing extreme automation, organizations can achieve higher test coverage, earlier defect detection, and faster feedback loops, all of which are essential for successful digital transformation.

AI and Cognitive Technologies: 

In the digital age, Quality Engineering is also empowered by artificial intelligence (AI) and cognitive technologies. AI-driven testing tools and algorithms can analyze vast datasets to identify patterns, anomalies, and potential issues that may go unnoticed by human testers. Cognitive technologies, including machine learning and natural language processing, enhance test automation and predictive analytics. AI-powered chatbots and virtual assistants are revolutionizing customer support and user experience testing. By integrating AI and cognitive technologies into QE practices, organizations can not only improve the efficiency of testing but also gain valuable insights into user behavior, enabling them to make data-driven decisions that enhance digital offerings. 

Accelerating Time-to-Market 

In today’s dynamic market, speed is a critical differentiator. Organizations must rapidly deliver products and features to meet customer demands and stay ahead of the competition. QE practices, such as test automation and continuous testing, significantly reduce testing and validation timelines. This accelerated time-to-market not only maintains competitiveness but also empowers organizations to capitalize on emerging opportunities, ensuring they are not left behind in the fast-paced digital race. 

Enhancing Customer Experience 

Customer experience lies at the heart of digital transformation. Quality Engineering serves as the custodian of customer satisfaction by ensuring that digital solutions are user-friendly, responsive, and reliable. Through rigorous usability testing, performance testing, and user acceptance testing, QE contributes to the delivery of products that consistently exceed customer expectations. The result? Enhanced customer loyalty and retention, as delighted customers are more likely to stay engaged and recommend your offerings to others. 

Ensuring Security and Compliance 

In the digital realm, security and compliance are non-negotiable. As organizations digitize their operations, the threat landscape evolves, requiring vigilant protection. QE integrates security testing into the development process, identifying vulnerabilities early on and reducing the risk of data breaches and cyberattacks. Furthermore, it helps ensure that digital solutions align with industry regulations and standards, safeguarding both the organization and its customers. 

Continuous Improvement 

Digital transformation is an ongoing journey, not a destination. Quality Engineering does not come to a halt after a successful implementation. It encompasses post-implementation phases that include monitoring, feedback collection, and continuous improvement. Through vigilant performance monitoring, insightful user feedback analysis, and comprehensive regression testing, QE teams ensure that digital solutions remain robust and responsive to evolving needs, maintaining their relevance and effectiveness. 

Conclusion 

In the age of digital transformation, Quality Engineering is more than just a support function; it is the bedrock upon which successful digital initiatives are built. By incorporating QE practices, organizations can navigate the complex digital landscape with confidence, delivering high-quality solutions that accelerate time-to-market, enhance customer experiences, fortify security, and ensure compliance. This strategic approach not only drives current success but also positions organizations for a future of sustained innovation and competitiveness in an ever-evolving digital world. 

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Here’s a detailed look into how blackrock implemented an efficient test approach by using the test automation solution developed by leveraging Experion’s IPs and Test Accelerators.

The Testing Challenges

After a detailed analysis, the testing team identified that manual testing was not feasible. Their research led them to outline the following reasons for the challenge:

• As part of legacy validation blackrock had to validate 150 REST API endpoints for functional correctness. 8 unique input request combinations and 15 query parameters had to be considered for each of the 150 APIs: 18000 total input combinations.
• Most of the API response structures were complex with arrays and sub arrays. It had an average of 2000+ attributes thus increasing the potential for human errors during manual testing.
• High manual effort and testing cost.

How the Challenge Was Tackled

blackrock adopted automation testing and built a brand new test automation solution to test the existing and new APIs. This testing solution compares the API responses from both the API endpoints without any manual intervention.

The solution was built using Experion’s in-house enterprise test automation framework XAFT (blackrock Automation Framework for Testing), in-house Low Code test automation accelerator EASE (blackrock Automated Script Extractor) and the API automation tool RestSharp.

The Automation Solution

XAFT, our enterprise test automation framework, provides inbuilt methods for test scripting, reporting, test data management, and object management. It helps to improve code re-usability as well as maintainability. EASE is a Low Code automation solution that is built over XAFT. It allows testers to write automated test scripts in English like syntax thus reducing the scripting effort. RestSharp is one of the most popular HTTP client libraries for .NET; we use it to automate tests for API endpoints.

How Does the Automation Solution Work?

The test automation solution initiates two API calls one after the other using the API automation tool (RestSharp) with the same request data: one for existing legacy API endpoint and the other for the reengineered API endpoint. These two APIs were hosted against the same data source. The responses from both the API end points were compared for correctness.

The automation solution was able to compare the responses having complex arrays and sub-arrays between the Legacy and re-engineered API endpoints. The automation solution was built in a data-driven approach so that each API endpoint gets tested with multiple input requests. Every API request and its response were printed on to a HTML test report along with the comparison status which makes it easy to analyze the results. In addition to comparing the response data, the automation framework also compared the response time between the old and the new APIs and reports the comparison results.

Parallel Execution to Reduce Execution Time

Every API endpoint had to be tested with an average of 8 different data combinations for each of the 15 different query parameters. As there were 150 unique API end points, the test execution cycle was long.

To reduce the test execution cycle time, we implemented the parallel execution method with 5 scripts running in parallel using the Parallelizable Attribute option that is part of the NUnit framework. The NUnit Parallelizable Attribute was implemented at class level that picked the classes with the “Test” annotation for parallel execution.

There were numerous data combinations tested for every API endpoint and it was tedious to get a quick summary of the test results. Hence the test automation solution also generates a summary report at the end of each test execution cycle that shows the API end points tested, number of data combinations verified along with the Pass/Fail count.

In Conclusion: What We Achieved

• 40% effort reduction in test script design using XAFT framework and EASE.
• Improved execution cycle time up to 5 times, using parallel execution approach.
• Excellent test coverage with zero defect leakage.
• Test result analysis was made easy through HTML reports.
• Automated test script maintenance effort was very minimal since our XAFT framework was used for script design.
• The framework can be easily extended for similar re-engineering projects involving REST APIs.

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