#test data automation

[yethiconsulting]

How AI-Powered QA Testing Tools Are Revolutionizing Software Quality Assurance

Introduction

Highlight the evolving role of AI in software development and QA testing.

Explain how AI-powered tools are addressing the challenges of speed, complexity, and accuracy in modern software testing.

Benefits of AI-Powered QA Testing Tools

Enhanced Test Automation

AI algorithms generate and execute test cases automatically, reducing manual effort.

Improved Bug Detection

Machine learning models identify hidden patterns and predict potential defects.

Dynamic Test Coverage

AI adapts to code changes and ensures comprehensive api automation testing of new features.

Faster Test Execution

AI optimizes test workflows, reducing execution time significantly.

Continuous Learning

AI-powered tools learn from past test results to refine and improve future testing strategies.

Popular AI-Powered QA Tools

Applitools: For visual testing with AI-driven baseline comparisons.

Testim: Uses machine learning for creating and maintaining stable test cases.

Functionize: Offers self-healing tests and NLP-driven test creation.

Challenges and Considerations

High initial investment and the need for team upskilling.

Balancing AI automation with human oversight for critical testing areas.

Conclusion

Summarize how AI-powered QA tools are reshaping the testing landscape.

Encourage teams to embrace AI tools to stay competitive and deliver quality software efficiently.

[yethiconsulting]

Optimizing Core Banking & Internet Banking Solutions

Greek Bank Leverages Yethi's Testing Services to Maximize Solution Performance Across Two of its European Subsidiaries

The Client

A leading bank in Greece offering a wide range of high-quality financial products and services in the domestic and international market.

The Challenge

With a growing customer base and implementation of new services via various disruptive digital banking channels, the client wanted to ensure that their Core Banking Solution (FLEXCUBE) and internet/mobile banking solution (OBDX) were robust and scalable enough to handle these augmentations.

The Solution

We carried out a comprehensive test to identify performance bottlenecks across Web, Application, Middleware, and Database Servers by verifying and validating the performance parameters of the following key applications/interfaces:

FCUBS Online Transactions

Payment Interface through MQ

ATM Interface

BO Queries + SMS Gateway Query

The Approach

Yethi performed two rounds of testing with Load Test (100%), Stress Test (125%), and Endurance Test (6+ Hours) comprising the following activities:

The following processes were evaluated.

Verification of performance engineering parameters including throughput, latency, load distribution, and memory usage

Identification of maximum business load and volume processing benchmarks as per the pre-defined scope of work

Establishing the break points of application in scope

Creation of scripts and execution of multiple rounds of load tests, designed to mirror the client’s live production environment, user loads, business patterns, and throughput, including projections for future scalability

Preparation of a detailed report summary outlining the potential risk areas and recommendations

The Benefit

The client was able to optimize their application based on our reports to maximize solution performance across two of its European subsidiaries.

Why did client select Yethi?

The client chose Yethi because of our experience in handling similar projects for other banks as well as our in-depth knowledge of the BFSI industry and the supporting technology systems.

About Yethi

Yethi is a leader in Quality Assurance solutions for the global banking and financial services industry. Founded by Fintech professionals with decades of domain experience, Yethi is invested in building the next generation of solutions to improve the quality of digital technologies being adopted within enterprises. One such solution is a robotic functional test automation platform, Tenjin, that follows a unique approach focussed on ease of use and maintenance.

[yethiconsulting]

Reducing Testing Bottlenecks with Effective Test Asset Management

Introduction

Define testing bottlenecks and their impact on project timelines and quality.

Introduce test asset management (TAM) as a solution to streamline testing processes.

Common Testing Bottlenecks

Highlight issues such as lack of standardized test assets, duplicate test cases, and difficulty in locating relevant scripts or data.

Discuss the impact of unmanaged test assets on test automation and manual testing efforts.

How Effective TAM Reduces Bottlenecks

Centralized storage: Ensure all team members can access updated and organized test assets.

Reusability: Promote the reuse of scripts, data, and reports to save time and effort.

Version control: Prevent confusion caused by outdated or redundant test assets.

Integration: Ensure TAM tools integrate seamlessly with CI/CD pipelines for faster feedback loops.

Key Practices for Effective TAM

Adopt tools for asset management and documentation.

Regularly review and update test assets to keep them relevant.

Train teams on efficient TAM practices.

Conclusion

Emphasize the role of TAM in reducing bottlenecks and accelerating the testing process.

Encourage investing in TAM as a critical component for streamlined QA workflows.

[yethiconsulting]

Maximizing Test Coverage with Cross-Browser UI Test Automation

Cross-browser UI test automation is critical in today’s diverse digital landscape, where users access applications through various browsers and devices. Ensuring seamless performance across environments maximizes test coverage and enhances user experience.

Key Considerations:

Comprehensive Browser Matrix:

Identify the most commonly used browsers and versions among your target audience. Focus on popular options like Chrome, Firefox, Edge, and Safari, and include mobile browsers for complete coverage.

Cloud-Based Testing Platforms: Tools like Tenjin Online and Tenjin AI enable automated testing across multiple browsers and devices simultaneously. This scalability saves time and ensures real-world accuracy.

Responsive Design Testing: Use tools to validate how your UI adapts to different screen sizes and resolutions, ensuring a consistent experience for users on desktops, tablets, and smartphones.

Parallel Test Execution: Run tests in parallel to significantly reduce testing time while maintaining high coverage. Frameworks like Selenium Grid or cloud-based solutions support this approach.

Dynamic Test Strategies: Regularly update your test suite to include new browser versions and configurations, adapting to technological advancements and user preferences.

By incorporating these practices, organizations can identify and resolve browser-specific issues, deliver a polished product, and build trust with their users, ultimately achieving maximum test coverage efficiently.

[testdatamanagement-blog]

Top 4 Test Data Management Challenges in Healthcare Industry

Healthcare applications are well-known for their inherent complexity, heterogeneous structure, variety in data leading to data integration issues and most importantly, the challenge of maintaining a variety of medical plans, enrolments and annual contracts. All of these lead to difficulty in finding adequate test data to support testing for the frequent IT releases.

Reasons that make test data management a challenge in healthcare:

Upstream and downstream dependencies: Dependencies between different systems like provider environment, claims processing, patient records and static data like ICD10 codes, diagnostic codes etc. make it difficult to pull the required test data. Changes made for any release are never solitary in terms of system impact. Due to the interdependency between systems, any minor change has cross-system impacts, at least where testing is concerned.

Healthcare Standards and Laws:

Like banking and insurance, healthcare is also governed by state and federal laws like HIPAA that make it mandatory for all stakeholders to guard and protect patient information. These laws vary from country to country. Healthcare insurance firms that have a presence across nations need to ensure their applications are always in compliance.

Gender and age specific processing:

Most processing in healthcare is specific to gender and age of patient. Contracts, treatments, diagnostic codes all differ based on gender and age.

Contracts and payments:

Healthcare applications are characterised by their massive size, variety and complexity. Contracts also frequently change due to changing patient preferences and market trends.

Better testing through better test data management

The success of your testing depends on how good your test data is. A good test data set mirrors your production data and is correctly proportioned to your testing needs.

The Blog Top 4 Test Data Management Challenges in Healthcare Industry appeared first on on Software Testing Blog by Cigniti Technologies